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AI, Trust, and the Future of Threat Intelligence

In this post, we explore how AI is reshaping cyber threat intelligence and why governance, transparency, and trust are becoming increasingly important as organizations rely more heavily on AI-generated insights and autonomous capabilities.

Artificial intelligence has quickly become embedded across cyber threat intelligence workflows.

Throughout research and analysis, enrichment, prioritization, and operational response, AI is helping organizations process large volumes of information and move more quickly from collection to action. As these capabilities mature, the conversation is moving beyond what AI can do, toward how organizations can trust, validate, and govern AI-generated intelligence.

Flashpoint has been recognized in the 2026 Gartner® Top 5 Vendors for AI Capabilities in Cyberthreat Intelligence Technologies: Governance & Trust research. Flashpoint was also named a Challenger in the 2026 inaugural Gartner Magic Quadrant for Cyberthreat Intelligence Technologies. The report recognizes five top vendors, including Flashpoint, across AI foundational elements within CTI and examines the governance, oversight, and trust mechanisms that help organizations use AI responsibly within intelligence operations.

Gartner notes in the report that “as organizations increasingly depend on autonomous agents from CTI vendors, the need for robust governance and trust frameworks has become critical.”

Trust Has Always Been the Foundation of Threat Intelligence

For intelligence teams, trust is not a new concept.

Analysts regularly evaluate the credibility of sources, validate claims, assess confidence levels, and determine whether reporting is relevant to their organization’s mission. The quality of intelligence has never been determined solely by how much information is available. It depends on whether that information is precise, timely, and accurate enough to move the needle and safely drive an operational decision.

AI, however, introduces a new layer to that process.

Organizations are increasingly leveraging AI to assist with enrichment, summarization, prioritization, and analysis. Those capabilities can accelerate workflows significantly, but they also introduce new questions. 

• How was a recommendation generated? 
• What evidence informed it? 
• How confident should an analyst be in the result? 
• What safeguards exist when the output is used to drive operational decisions?

Ultimately, these are questions of operational risk and data integrity, not just technology features. Analysts must be able to interrogate a system’s reasoning just as they would any other source.

Governance Is Becoming a Core Requirement

Establishing analytical trust is essential, but it requires strict operational guardrails to function safely at scale. This is where governance moves from an item on a checklist to a core requirement.

Many of the conversations around AI in cybersecurity focus on capability. 

• Can an AI system summarize faster? 
• Can it identify relationships that would otherwise be missed? 
• Can it reduce analyst workload?

While speed and scale are essential, they only tell half the story. As organizations move AI closer to daily operational workflows, a second, more critical set of questions is emerging centering around control.

As Gartner explains, “Agent governance and trust ensures that only authorized users and agents can access and manage sensitive threat data through role-based permissions and approval workflows.”

From our experience, by implementing these structural protections — alongside comprehensive audit logging — security leaders can ensure that AI-driven actions remain fully transparent, secure, and accountable. Governance isn’t about slowing down automation; it’s about establishing the administrative guardrails that dictate exactly who—and what—is allowed to execute a sensitive operation within the enterprise. 

This oversight is becoming a foundational necessity as threat intelligence breaks out of traditional security silos. Because CTI increasingly informs vulnerability management, fraud investigations, executive protection, security operations, and enterprise risk programs, the downstream impact of an inaccurate recommendation can disrupt an entire enterprise. This underscores the importance of understanding not only what an AI system recommends but also how it arrived at that recommendation in the first place.

AI Changes the Scale (and Reaps the Context) of Intelligence Operations

One area where AI has a massive, immediate impact is scale.

Threat intelligence teams today are completely inundated with data. Malicious activity spans encrypted messaging platforms, illicit criminal marketplaces, forums, social media, vulnerability disclosures, and vast streams of infrastructure telemetry. Even the most mature, well-resourced teams struggle to manually ingest and process this sheer volume of information.

When applied appropriately, AI elegantly solves this bottleneck. Automation acts as an incredible force multiplier — accelerating time-consuming foundational tasks like research, cross-language translation, data enrichment, summarization, clustering, and correlation. Large language models can process information at scale, reducing the manual effort required to move from collection to analysis.

The critical challenge, however, is ensuring that this massive injection of speed does not come at the expense of context.

Threat intelligence is fundamentally a contextual discipline. A standalone indicator, isolated vulnerability, or single threat actor reference rarely carries meaning on its own. To act safely, analysts must understand exactly where information originated, who is discussing it, how widely it is being shared, and how it relates to broader activity across the threat landscape.

What AI cannot do independently is establish that context. While machines are exceptionally effective at identifying patterns across vast datasets, they inherently lack source validation, analytical rigor, and nuanced judgment. If an AI accelerates the data pipeline but strips away the underlying context, assessing confidence becomes impossible, making informed decision-making even harder.

This is why Flashpoint champions a “human-led, AI-scaled” model. True scalability isn’t about replacing analysts with autonomous bots; it’s about using machines to conquer the overwhelming noise of the threat landscape while keeping the resulting intelligence heavily grounded in expert-reviewed sources. As AI capabilities continue to mature, context becomes more important, not less. The organizations that derive the most value from automation will be those that pair machine-scale processing with human-in-the-loop review to ensure every output can be validated, contextualized, and confidently acted upon.

What Security Leaders Should Be Evaluating

As AI becomes a larger component of cyber threat intelligence platforms, security leaders have an opportunity to evaluate these capabilities through a broader lens than automation alone.

The Gartner report provides a useful framework for thinking about these questions, particularly around governance and trust. Rather than focusing exclusively on what an AI system can do, Flashpoint recommends that organizations rigorously evaluate how those capabilities are managed, validated, and controlled. 

Some of the most important areas to evaluate include:

Explainability

Question to ask: Can analysts trace how an AI-generated recommendation or conclusion was produced?

The ability to review supporting evidence, understand contributing factors, and see outputs back to underlying intelligence sources is becoming increasingly important as AI is used to support operational decisions.

Confidence and Validation

Question to ask: How does the platform communicate confidence in AI-generated outputs?

Threat intelligence has always relied on confidence assessments. As AI-generated insights become more common, organizations should look for configurable confidence thresholds that allow them to tailor automated actions to their corporate risk tolerance.

Governance and Oversight

Question to ask: What controls exist around the use of AI?

Capabilities such as role-based permissions, approval workflows, and audit logging are critical governance mechanisms for organizations seeking to maintain accountability and trust in AI-driven processes.

Operational Impact

Question to ask: How does AI improve intelligence workflows in practice?

The most valuable AI capabilities are often those that help analysts spend less time on repetitive tasks and more time on investigation, analysis, and decision-making. Understanding where AI fits into the intelligence lifecycle can help organizations distinguish between meaningful operational improvements and isolated feature enhancements.

Looking Ahead

The conversation around AI in threat intelligence is still evolving, but the direction of travel is becoming increasingly clear. Organizations are looking beyond standalone AI features and placing greater emphasis on governance, transparency, and accountability.

Taken together with broader industry trends, this points to a threat intelligence market that is becoming increasingly sophisticated. Organizations are evaluating not only the quality and uniqueness of intelligence itself, but also how that intelligence is operationalized, how AI is applied, and how trust is maintained throughout the process.

We believe that shift reflects the realities of modern intelligence work. Speed and scale remain important, but neither replaces the need for context, validation, and informed decision-making.

For security leaders evaluating AI capabilities within cyber threat intelligence platforms, Gartner’s research offers valuable insight into how the market is evolving and what requirements are likely to become increasingly important in the years ahead.

Gartner subscribers can read the full report to explore the governance, trust, and AI capability trends shaping the future of cyber threat intelligence.

Gartner Disclaimer

Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose. 

Gartner, Top 5 Vendors for AI Capabilities in Cyberthreat Intelligence Technologies: Governance & Trust, Jonathan Nunez, Jaime Anderson, June 15, 2026.

Gartner, Magic Quadrant for Cyber Threat Intelligence Technologies, Jonathan Nunez, Carlos De Sola Caraballo, Jaime Anderson, May 4, 2026.

Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.

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Remus Stealer: A New, Not-So-New Infostealer

In this post, we explore the emergence of Remus Stealer, analyzing its structural and behavioral similarities to the infamous Lumma malware.

The underground marketplace rarely stays quiet for long. A new information-stealing malware dubbed Remus Stealer has surfaced in the cybercrime underground, exhibiting significant similarities to the notorious Lumma malware family across its administration panel, stolen log files, and core code structure.

Despite parallels in its code and functionality, threat actors are eagerly buying into the platform. In addition to its familiar features, it provides attackers with a distinct, modern command and control (C2) and networking infrastructure designed to slip past current security perimeters.

What We Know About Remus

Flashpoint first observed Remus appearing for sale within illicit communities in March 2026. The malware listing offers similar functionality to other popular Malware-as-a-Service (MaaS) offerings, including Google OAuth cookie restoration and Telegram channel integration for logs.

Much like the Lumma malware family, the Remus subscription service operates on a three-tiered access model:

• Basic: US$250
• Pro: US$500
• Enterprise: US$1,000

At this time, Remus has no additional channels or automated bots associated with its sale or distribution. Despite undeniable similarities to Lumma, its developer claims to not be a rebrand of the Lumma project.

Since March 2026, Remus has continued its operations mostly unhindered by negative associations associated with Lumma—particularly the doxxing of its panel in August 2025.

Similarities to Lumma

Similarities can be observed in the Remus and Lumma panels in both aesthetics and functionality. Both panels use similar assets for tab icons and have embedded advertisements for other illicit services such as packers and log clouds. Harvested logs also share extremely similar directory structures in log files, including unique identifiers.

Code-Level Overlaps

Remus is a 64-bit compiled binary, and Lumma was a 32-bit binary. However, major similarities between the code bases of both malware can be observed.

Upon execution of an unpacked sample, both Remus and Lumma will send warning messages to the user that the build is unpacked. This was a unique phenomenon first established by Lumma several years ago. In both Remus and Lumma samples, the pack check and window message are performed before the main functionality of the malware.

In both Remus and Lumma, a function is used first to check if the sample is packed, and a second function is used to send the window error message.

Remus uses similar string obfuscation methods to Lumma, in which each string has been uniquely encoded and then decoded during runtime. Deobfuscation occurs by looping byte by byte through encoded blobs. Each encoded string is obfuscated by a unique pattern. This can be seen in the code samples below:

Of note, both samples have at least one NOP instruction between the encoded blob being moved onto the stack and the deobfuscation loop.

Another unique feature of Lumma is the presence of a plaintext identifier string used to link customers to specific build generations. In Lumma, this string was referred to as the LID (Lumma ID), and this ID method appears in Remus as well as a “tag.”

Like the Lumma LID string, the Remus tag could be leveraged to attribute variant builds and campaigns to single threat actors or groups.

Additionally, both Remus and Lumma exhibit similar control flow obfuscation by replacing direct jumps with indirect jumps read from offsets that have been moved onto the stack, jumps computed from a jump table, and jumps resolved by a pointer.

Differentiators of Remus

Although Remus bears remarkable similarities to Lumma, its main differences lie in its C2 beaconing.

Before performing main stealer functionality, Remus will beacon out to its C2 infrastructure. It will attempt to resolve several domain:port combinations via POST requests, and attempt a final connection to find the C2 server using EtherHiding. If it is unable to connect, the malware will terminate.

After a connection is established, the stealer sends a POST request to the C2 in order to receive an access token. Once received and decoded, this access token is used to receive encrypted config data used by Remus to target assets on the victim system. Data collected for logs is then exfiltrated as encrypted POST data.

Protect Against Infostealers Using Flashpoint

Remus stealer represents a sophisticated continuation of the MaaS infostealer model left behind by Lumma’s collapse. While the developer asserts independence, the overwhelming code overlaps, matching obfuscation techniques, and administrative panels indicate that Remus is either heavily inspired by, or derived from the Lumma codebase. These traits have allowed it to thrive, providing threat actors with a familiar, robust alternative that sidesteps the reputational baggage and law enforcement scrutiny of its predecessors.

Flashpoint continuously tracks the latest developments in illicit communities, hard-to-reach adversary spaces, and malware repositories to identify emerging threats. Request a demo to learn how Flashpoint’s primary source collections and analyst insights empowers your security teams.

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America250 Fourth of July Threat Assessment

In this post we break down the intersecting cyber risks, physical security strains, and operational challenges shaping the security landscape for the historic Semiquincentennial celebrations.

As the United States prepares to mark its 250th anniversary this Fourth of July, the convergence of historic national celebrations, sprawling public events, and simultaneous high-profile sports tournaments is creating an exceptionally complex threat landscape. The multiyear national initiative “America250,” features over 1,200 synchronized grassroots gatherings under the “America’s Block Party” umbrella, with flagship events taking place in Washington DC, Philadelphia, Boston, New York, and Los Angeles.

Key Takeaways

While public sentiment surrounding America250 remains broadly positive, Flashpoint analysts have assessed the physical, cyber, and operational threat vectors that organizations, security teams, and municipalities must navigate during this high-visibility holiday weekend.

America250 Threats & Security Challenges:

1. Distributed Physical & Infrastructure Strain: Massive tourism influxes will collide with ongoing 2026 FIFA World Cup matches in Houston and Philadelphia on July 4, putting historic operational pressure on metropolitan transit grids and soft targets.
2. Elevated Iconicity and “City of Concern” Status: Although no specific, credible plots have been confirmed, the National Mall events in Washington, DC have received their first-ever National Special Security Event (NSSE) designation. Meanwhile, the National Counterterrorism Center (NCTC) has officially designated Philadelphia a “city of concern” due to the volume of synchronized events.
3. Ideological Protest Dynamics: Activist groups are organizing a significant anti-authoritarian march in Philadelphia. While expected to be peaceful, open-source chatter indicates a portion of attendees plan to exercise their license to carry firearms.
4. Disruption & Cyber Threat Vectors: Cyber threat groups, ransomware operators, and hacktivists are expected to attempt to exploit thin holiday IT staffing. Threat vectors range from mass public-transit ticketing fraud to high-consequence digital hoaxes involving rogue cellular infrastructure.

Physical Threat Vectors

Transportation and Infrastructure

Flashpoint assesses that “lone wolf” actors motivated by various ideological grievances, including those inspired by foreign terrorist organizations (FTOs), pose the most likely threat of disruptions to transportation infrastructure during America250 events. This threat is likely to apply to all major transport hubs during the event, including Washington DC, Philadelphia, New York City, and Boston. Attendees can expect to see an increased police and military presence near transit hubs at major events.

Event Threats

While no specific credible threats targeting America250 events have been identified, the July 4th events taking place on the National Mall in Washington DC, have been given a National Special Security Event designation, which is typically reserved for events deemed potential targets for terrorism or other criminal activity. This is the first time such a designation has been given to July 4th celebrations on the National Mall.

Memos released by the National Counterterrorism Center to security agencies also identified Philadelphia as a “city of concern” regarding potential targets for terror attacks due to the number and scale of events taking place on July 4th. Law enforcement officials have indicated that while no specific threats have been identified, increased security measures will be in place throughout the city.

Planned Protest

The Fayetteville Resistance Coalition, alongside Veterans Against Fascism, and the Women’s March is organizing an anti-authoritatian protest march in Philadelphia on July 4th—being the largest mobilization of military veterans in decades.

Flashpoint has identified chatter indicating that march attendees may be armed. However, Flashpoint has not identified any calls for violence at this protest and deem that actions will likely remain peaceful. Despite this, arrests may be possible if attendees gather in unauthorized areas or engage in civil disobedience.

Cyber Threat Vectors

Ransomware and Operational Technology (OT) Disruptions

Financially motivated threat actors frequently deploy ransomware during major US holiday weekends when corporate and municipal IT security staffing is historically thin.

Flashpoint analysts assess that attackers could target automated ticketing systems, regional rail signaling, and digital municipal transit grids. Disruption to public transit during the high-density travel window surrounding major events could induce logistical gridlock. Secondary targets include municipal water treatment facilities, local power grids, and emergency response (911) dispatch systems in primary host cities.

Hactivism

With hundreds of thousands of spectators gathering at prominent national landmarks, hacktivist groups seeking political leverage or global media visibility pose an elevated threat to public messaging infrastructure.

Compromising the digital billboards, stadium screens, or viewing decks used for America250 events presents an attractive vector for defacement. Adversaries may attempt to display political propaganda, anti-war messaging, or explicit content to captive, high-density crowds.

Event App Vulnerabilities and Data Harvesting

The decentralized nature of “America’s Block Party,” featuring over 1,200 grassroots events managed via localized apps, introduces software supply chain vulnerabilities.

Cybercriminals may target the ticketing infrastructure of high-profile, restricted-access events. Phishing campaigns, credential stuffing, or application programming interface (API) vulnerabilities within event-specific mobile applications could result in mass ticketing fraud, legitimate attendees being locked out, or crowd-control issues at venue gates.

Additionally, malicious actors frequently deploy spoofed public Wi-Fi networks around high-density tourist hubs to harvest sensitive personal data, financial credentials, and biometric profiles from unsuspecting attendees.

Protect People Using Flashpoint

To ensure attendee safety, safeguard operations, and protect public-facing brands, Flashpoint recommends implementing the following proactive measures:

1. Secure Public-Facing and Display Infrastructure: Implement strict access controls, multi-factor authentication (MFA), and offline fail-safes for all internet-connected digital signage, stadium screens, and public notification systems to prevent hacktivist defacements.
2. Audit Event Applications and Mobile Endpoints: Conduct rigorous vulnerability scans on event-specific APIs and ticket validation platforms. Advise personnel and contractors against posting photographs of official credentials, badges, or operational passes on public social media channels.
3. Establish Out-of-Band Incident Response Protocols: Prepare alternative communication channels and verified public-address messaging to immediately counter potential rogue emergency broadcasts, digital hoaxes, or localized telecom disruptions that could cause public panic.
4. Monitor High-Risk Overlap Zones: Cross-reference physical security deployment schedules in cities like Philadelphia where World Cup traffic, official America250 parades, and armed protest routes intersect near major transit networks.

Ensure your security team has full visibility into the cyber and physical threat vectors shaping this historic holiday weekend. Request a demo and see how Flashpoint equips organizations with the intelligence needed to detect, analyze, and mitigate emerging risks.

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Unmasking the Digital Trail: Essential Techniques for Vetting AI-Generated Content

In our latest on-demand webinar, we outline the practical, human-driven techniques threat intelligence teams must deploy to detect synthetic media, protect corporate RAG ecosystems, and filter through the noise of AI-polluted networks.

In the era of generative artificial intelligence (AI), threat intelligence is facing a profound signal-to-noise challenge. AI has introduced a massive paradigm shift to threat actor operations—making execution extremely easy while simultaneously dramatically complicating the task of verification for security teams.

In our latest on-demand webinar, Matt Edmonson, SANS Senior Instructor and founder of Argelius Labs, joined Flashpoint to discuss the intersection of Open Source Intelligence (OSINT) and AI. Drawing from his vast federal law enforcement experience, he shared actionable, human-driven techniques for detecting and vetting AI-generated online content.

Neutralizing the Automated RAG and Vector Database Trap

Before deploying any human-driven vetting techniques, an analyst must understand the specific structural trap threat actors are laying. Adversaries are no longer just using AI to spin up isolated phishing copy; they are using it to corrupt the automated defense pipelines that security teams rely on.

Modern threat intelligence workflows utilize automated ingestion to feed open-source data directly into local vector databases and Retrieval-Augmented Generation (RAG) models. Aware of this, sophisticated threat actors deploy a coordinated infrastructure strategy: they register multiple lookalike domains simultaneously to broadcast the exact same AI-generated disinformation narrative.

When automated security tools ingest this data, the system flags multiple distinct “sources” confirming the story as truth. This structural echo chamber completely bypasses automated verification safeguards, polluting corporate databases with validated lies. We have seen this play out via:

• Long-Game Credibility Building: Edmonson highlighted an active Foreign Malicious Influence (FMI) campaign utilizing a French lookalike news site called Verite Cache (“The Hidden Truth”). The threat actors scrape legitimate Western news, use AI to rewrite it to build structural domain authority over time, and then manipulate narrative outcomes the moment a critical geopolitical event or election occurs.
• Simultaneous Infrastructure Deployment: This pattern was mirrored in Southeast Asia, where Singapore recently banned six lookalike news sites targeting regional discourse. Upon technical inspection, five of those six distinct domains had been registered on the exact same day to broadcast a unified narrative.
• Organic-Looking Algorithmic Surges: The scale of these operations can shift political landscapes in a matter of days. Romania recently took the extreme step of canceling and restarting its presidential election due to a covert, highly coordinated Russian-backed social media campaign. The operation used synthetic assets to trigger algorithmic recommendation engines, driving an intense, seemingly organic surge for an underdog candidate.

Triangulating AI Flaws and Anomalies Across Modalities

Vetting AI content relies on compiling a cluster of intersecting indicators across text, images, audio, and video until a definitive analytical confidence level is reached. While generative tools have grown highly sophisticated, they are still bound by mathematical constraints and architectural limitations. Catching these errors and inconsistencies requires analysts to identify a cluster of intersecting indicators across text, images, audio, and video:

• Textual Analytics (Linguistic Quirks and Filler Text): Large Language Models (LLMs) leave distinct behavioral footprints. Analysts should look for commonly-used AI wordings and “portable sentences”, as well as automated translation leakage that reveals a threat actor’s native language mechanics.
• Visual Logic Flaws (Physics and Seams): AI models frequently fail to grasp the fundamental physics of the real world. Analysts should closely inspect image logic for anatomical blunders (such as inverted hand structures), impossible geometry, or objects with extreme structural flaws. Additionally, AI struggles with “texture seams”—the exact boundaries where distinct textures meet.
• Auditory and Video Glitches (Cadence and Duration): Human speech is inherently messy, characterized by breathing pauses, environmental background noise, and shifting cadences. Synthetic speech is often locked into a perfectly uniform, monotone rhythm. Furthermore, high-fidelity deepfakes are incredibly resource-intensive to sustain over long durations. While an actor can fake 10 to 15 seconds of synthetic video convincingly, a five-minute video will almost always display jarring cuts, visual artifacting, or avatars clipping out of frame.

Empowering the Human Layer | Watch the Full Webinar

Human analysts remain the most critical layer of defense against illicit uses of AI. Empowered by comprehensive threat intelligence, OSINT, and AI technologies, security teams can hunt for clusters of intersecting indicators across text, images, audio, and video to assess authenticity. To learn more and to gain more essential techniques, watch the full on-demand webinar. Using Flashpoint, organizations can filter through noise, execute critical data premortems, and neutralize sophisticated disinformation campaigns.

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The Shift to Threat-Informed Prioritization: Operationalizing CISA BOD 26-04

In this post, we examine how CISA BOD 26-04 shifts the industry away from flat CVSS scoring and details how Flashpoint bridges the critical data gaps left by public vulnerability repositories.

With the recent issuance of Binding Operational Directive (BOD) 26-04, CISA has officially shifted federal policy away from static severity scores and flat patching timelines  toward threat-informed prioritization. The move reflects a reality security teams have grappled with for years: not all critical vulnerabilities post the same risk, and not all active vulnerabilities receive the highest CVSS scores. 

Traditional vulnerability management programs have often relied on severity-based patching models that force resource-constrained teams to focus on large volumes of high-scoring vulnerabilities. Yet research consistently shows that threat actors routinely exploit a broader range of weaknesses, including lower-scoring vulnerabilities on internet-facing assets, to gain initial access and move laterally through victim environments. 

While BOD 24-04 represents a significant step forward, there are still hidden challenges organizations will face as they adopt a risk-based approach. The operational reality is that executing a truly risk-based matrix validates what Flashpoint has maintained for years: effective vulnerability prioritization requires deep, contextual threat data. Unfortunately, the needed real-world metadata for this kind of context are simply not supported by public sources of vulnerability intelligence.

Understanding BOD 26-04

BOD 26-04 evaluates the urgency of a vulnerability by cross-referencing a security flaw against four distinct operational variables:

1. Asset Exposure: Is the asset publicly accessible via the internet?
2. Known Exploited Status (KEV): Is there verifiable evidence of active exploitation in the wild?
3. Exploit Automation: Can a threat actor completely automate the weaponization and delivery of the exploit?
4. Technical Impact: Does a successful exploit result in partial disruption or total compromise of the target system?

By analyzing these variables in tandem, organizations can tier their response and execute clear, defensible SLA metrics.

Risk Priority	Real-World Matrix Conditions	Required SLA & Operational Action
P1: Immediate Risk	In KEV + Publicly Exposed + Automatable + Total Impact	3 Days (Includes Mandatory Forensic Triage)
P2: Urgent Risk	In KEV + Publicly Exposed + (Either Non-Automatable OR Partial Impact)	7 Days
P3: Elevated Risk	In KEV + Internal / Non-Publicly Exposed Asset	14 Days
P4: Standard Risk	Not in KEV + Publicly Exposed + Automatable + Total Impact	30 Days
Deferred Risk	Not in KEV + Internal Asset OR Lower Technical Impact	Next Scheduled System Upgrade / Maintenance

According to CISA, the pilot testing of this model has shown that fewer than 1% of an organization’s typical vulnerability backlog requires urgent, immediate remediation, while over 60% can be safely deferred to standard system maintenance cycles. However, implementing this framework successfully requires access to granular, real-world data points that public sources of vulnerability intelligence simply do not support. 

“Speaking with security teams in the wake of this directive, it is clear that BOD 26-04 is a major paradigm shift. While the ability to safely defer more than half of your patch backlog is an invaluable efficiency gain for modern organizations, executing that strategy effectively requires ground-truth intelligence on exploit automation and adversary intent that public registries simply cannot deliver.”

Josh Lefkowitz, CEO and Co-founder at Flashpoint

The Data Challenge

To operationalize this model successfully, organizations will require a high-fidelity intelligence pipeline that combines comprehensive threat and vulnerability intelligence into clear, context-rich insights that support prioritization and decision making. You cannot confidently defer remediation without verifiable intelligence that proves the vulnerability lacks active exploit history or automation maturity.

Unfortunately, relying on public data feeds like the CVE database or the National Vulnerability Database (NVD) to fuel this matrix creates an immediate operational bottleneck. Public repositories have historically struggled under severe analysis backlogs, leading to processing delays and missing Common Platform Enumeration (CPE) data. Furthermore, public feeds are inherently reactive; they do not monitor illicit communities where exploit code is developed, nor do they track the real-time weaponization metrics needed to meet BOD 26-04’s tight 3-day or 7-day compliance window.

How Flashpoint Solves the Prioritization Gap

Flashpoint Vulnerability Intelligence bridges the gap between public data limitations and the requirements of real-world exposure management. Independently researched and enriched, Flashpoint provides the precise contextual signals required by the CISA BOD 26-04 matrix:

• Coverage across CVE and non-CVE vulnerabilities
• Continuous tracking of exploitation activity and adversary usage
• Context on exploit maturity and remediation
• Consistent enrichment that can be integrated into operational workflows
• Over 7,000 known exploited vulnerabilities (KEV)

By integrating Flashpoint’s continuous intelligence into operational workflows, security teams can automatically validate exposure, assess automation potential, and confidently claim the operational relief that risk-based prioritization promises.

“We are convinced by Flashpoint’s superior vulnerability coverage, timeliness in the updates, and long-term monitoring of exploits. We also really appreciate Flashpoint’s proprietary CVSS rating and classifications based on expert knowledge of the standard and practical use in the industry. Having all this curated information at your fingertips is a game changer.”

Vulnerability Manager, Telecommunications

Prioritize Vulnerability Risk Using Flashpoint

CISA’s BOD 26-04 represents a critical shift away from severity-based patching and toward defensive efficiency. However, the effectiveness of this model is entirely dependent on the fidelity of your threat data.

Without best-in-class comprehensive vulnerability intelligence, security teams will be forced back into reactive patching cycles. Request a demo to learn more how Flashpoint helps security teams move beyond the constraints of static scoring and align their vulnerability management workflows with actual risk.

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Identity Is the New Attack Surface: How Infostealers Are Reshaping Enterprise Risk

Our new guide explores how infostealers are fueling modern identity-based attacks and how organizations can build a proactive defense before stolen access is weaponized.

The New Reality of Identity-Based Threats

A publicly exposed database surfaced in early 2026 containing more than 149 million stolen login credentials. The records were not tied to a single breach or organization. Instead, they had been quietly collected over time from devices infected with information-stealing malware, with each record containing usernames, passwords, session data, and the context needed to use them.

Unlike traditional breach dumps, this data was structured, searchable, and immediately actionable. Credentials were mapped to specific services, session artifacts reflected active logins, and much of the information was recent enough to enable direct access without triggering traditional security controls.

This incident reflects a broader shift in the threat landscape.

More than 11.1 million devices were infected with infostealers last year, fueling a supply of over 3.3 billion stolen credentials, session cookies, cloud tokens, and other forms of identity data now circulating across illicit markets.

For security teams, the challenge is no longer simply detecting a breach after it occurs. It is understanding when access may already exist — where compromised credentials are circulating, how they are being used, and how quickly they can be weaponized.

That’s why Flashpoint created Identity Is the New Attack Surface: A Guide to Infostealers and Proactive Defense.

Drawing on Flashpoint’s Primary Source Collection (PSC) and analyst-driven intelligence, this guide helps IT, Threat Intelligence, Fraud, and HUNT teams understand how infostealers operate, how stolen identity data fuels real-world attacks, and how organizations can move from reactive response to proactive defense.

The guide explores:

• How today’s most active infostealers power modern attack chains
• How threat actors weaponize stolen credentials, cookies, and session data
• How organizations can operationalize infostealer intelligence for proactive defense
• How to evaluate infostealer intelligence providers and detection capabilities

Why Identity Has Become the Preferred Attack Surface

For years, security teams focused on vulnerabilities, malware delivery, and network intrusion as the primary paths to compromise. Increasingly, however, threat actors are taking a different

Modern infostealers such as Lumma, StealC, Vidar, Acreed, and Rhadamanthys provide attackers with something more valuable than initial access: usable identity. These malware families collect credentials, browser artifacts, session cookies, application data, and host metadata that help threat actors understand how a victim authenticates and what systems they can access.

A single infected device can expose credentials, browser artifacts, session cookies, application data, host metadata, and access to enterprise SaaS platforms. Together, these artifacts create a detailed profile of how a user authenticates, what systems they access, and how those systems trust that identity.

This is what makes infostealer data so valuable.

“For years, organizations have invested heavily in detecting malware, blocking exploits, and hardening infrastructure. Meanwhile, attackers have increasingly shifted to a simpler strategy: logging in with valid identities.

Infostealers have fundamentally changed the economics of access. Threat actors no longer need to compromise a network directly when billions of credentials, session cookies, and authentication artifacts are already circulating in underground ecosystems. The challenge for defenders has risen from preventing compromise to identifying where access already exists and how quickly it can be weaponized.”

Ian Gray, Vice President of Intelligence at Flashpoint

Identity data is inherently reusable. A stolen credential can be tested across multiple services. A session cookie can potentially allow attackers to hijack authenticated sessions. Browser and host metadata can help threat actors recreate a victim’s environment and bypass security controls designed to detect suspicious logins.

What begins as a single infection can quickly evolve into access across multiple systems, applications, and organizations.

What Is an Identity-Based Attack?

Identity-based attacks occur when threat actors use legitimate credentials, session cookies, authentication tokens, or other identity artifacts to gain access to systems and applications. Rather than exploiting a vulnerability or deploying malware inside a target environment, attackers authenticate as trusted users using stolen identity data.

This shift is one of the primary reasons infostealers have become so valuable. Modern infostealer logs often contain far more than usernames and passwords. They may also include browser cookies, session information, host metadata, application data, and other artifacts that help attackers understand how a user authenticates and what systems they can access. When combined, this information enables account takeover, fraud, lateral movement, and other forms of identity-based abuse.

From Credential Theft to Identity Exploitation

The way threat actors operationalize stolen data is evolving just as rapidly as the data itself.

Historically, attackers often had to manually review stolen credentials and determine which accounts were worth pursuing. Today, that process is increasingly automated.

Infostealer logs can be aggregated, tested, and prioritized at scale, allowing threat actors to rapidly identify valid access across enterprise systems, SaaS platforms, VPNs, and cloud environments.

Flashpoint identifies this as a hybrid threat: the convergence of large-scale identity compromise and automated exploitation.

Once valid access is identified, attackers can move quickly. Credentials may be reused across services. Session data can be leveraged for account takeover. Access can be sold to ransomware operators, fraud actors, or other criminal groups. In many cases, exposure itself becomes part of the attack lifecycle rather than merely a precursor to it.

The result is a threat landscape where stolen identity data is not simply stored and sold. It is continuously tested, validated, reused, and operationalized.

Turning Exposure Into Actionable Intelligence

For defenders, prevention remains important. But prevention alone is no longer enough.

Organizations must also be able to identify when credentials, session cookies, and other identity artifacts have already been exposed and are circulating within underground ecosystems.

The earliest opportunity to intervene is often after data has been exfiltrated but before attackers have successfully operationalized it.

Achieving that visibility requires more than traditional breach feeds or aggregated datasets.

Flashpoint’s Primary Source Collection approach provides direct visibility into the forums, marketplaces, Telegram channels, malware repositories, and illicit communities where infostealer activity originates. Rather than relying solely on recycled breach data, Flashpoint continuously collects from the environments where stolen identity data is first shared, sold, and operationalized.

However, collection alone is not enough.

Raw infostealer logs are noisy, fragmented, and difficult to operationalize at scale. Flashpoint transforms these logs into structured intelligence through a multi-stage workflow that includes:

• Source ingestion from underground ecosystems
• Normalization and de-duplication of collected data
• Automated parsing and enrichment of credentials, cookies, host metadata, and malware attribution
• Structured output that supports alerts, investigations, and integrations across existing security workflows

This process helps defenders understand not only what was exposed, but who may be affected, how exposure occurred, what systems may be at risk, and how quickly action is required.

Building a Proactive Defense Across the Identity Layer

The rise of infostealers has fundamentally changed how organizations should think about attack surface management.

The attack surface is no longer limited to infrastructure, endpoints, or internet-facing applications. It now includes the digital identities of employees, partners, vendors, and customers.

Security teams need visibility into the identity layer itself — understanding where exposure exists, how attackers are leveraging stolen data, and what actions should be taken before access is exploited.

By combining direct visibility into underground ecosystems with structured, actionable intelligence, organizations can identify compromised accounts earlier, uncover infection trends, prioritize response efforts, and reduce the likelihood of downstream compromise.

Download Identity Is the New Attack Surface: A Guide to Infostealers and Proactive Defense to learn how your organization can build a proactive defense program across the identity layer.

Key Infostealer Statistics

According to Flashpoint research:

• More than 11.1 million devices were infected with infostealers in the last year.
• Over 3.3 billion credentials, session cookies, cloud tokens, and identity artifacts are circulating across illicit markets.
• Flashpoint analysts identified 30+ active infostealer strains being sold across underground ecosystems.
• Flashpoint’s credential database contains 48+ billion credentials, including more than 1 billion tied to infostealer activity.
• More than 4.2% of infostealer-exposed credentials include browser cookies that may support session hijacking.
• Flashpoint can collect and parse some infostealer logs within one to two days of infection.

Frequently Asked Questions (FAQ)

FAQ: Infostealers and Identity-Based Threats

What is an infostealer?

An infostealer is a type of malware designed to collect sensitive information from an infected device. Depending on the strain, this can include usernames and passwords, browser cookies, session tokens, saved payment information, cryptocurrency wallets, system metadata, and other identity-related artifacts.

How do infostealers work?

Infostealers infect a victim’s device and collect information such as credentials, browser data, session cookies, autofill information, cryptocurrency wallet data, and system metadata. The stolen information is packaged into files known as infostealer logs, which can then be sold, shared, or operationalized by threat actors.

What information can infostealers steal?

Depending on the malware family, infostealers can collect usernames and passwords, session cookies, authentication tokens, browser history, saved payment information, cryptocurrency wallet data, system information, installed applications, and other identity-related artifacts. The goal is to provide attackers with enough information to access accounts and impersonate legitimate users.

What are the most common infostealers?

The infostealer ecosystem changes rapidly, but Flashpoint analysts currently track strains such as Lumma (also known as LummaC2/Remus), StealC, Vidar, Acreed, and Rhadamanthys among the most prominent malware families driving credential theft and identity-based attacks.

Why are infostealers so dangerous?

Infostealers provide attackers with more than credentials. Modern infostealer logs often contain the context needed to use stolen data, including session information, browser artifacts, and device metadata. This allows threat actors to perform account takeovers, move laterally within environments, and gain access to business-critical systems. According to Flashpoint’s 2026 Global Threat Intelligence Report, more than 11.1 million devices were infected with infostealers last year, contributing to a pool of over 3.3 billion stolen credentials, session cookies, cloud tokens, and other identity artifacts.

What is an infostealer log?

An infostealer log is a package of data collected from an infected device. Logs may contain credentials, cookies, browser data, application information, host metadata, and other artifacts that help attackers understand how a victim authenticates and what systems they can access.

Can infostealers bypass multi-factor authentication (MFA)?

In some cases, yes. While multifactor authentication remains a critical security control, stolen session cookies and authenticated session data can sometimes allow threat actors to hijack existing sessions without needing to complete the MFA process themselves. Flashpoint found that more than 4.2% of infostealer-exposed credentials in its dataset were associated with browser cookies, highlighting the growing importance of session-based risk.

How do threat actors obtain infostealer logs?

Infostealer logs are frequently bought and sold across illicit marketplaces, forums, Telegram channels, and other underground communities. Many are distributed through Malware-as-a-Service (MaaS) offerings that make infostealer capabilities accessible to a wide range of threat actors. Flashpoint analysts identified more than 30 unique infostealer strains actively offered for sale across underground ecosystems.

How can organizations detect credential exposure from infostealers?

Organizations can monitor underground sources where stolen data is shared and sold, identify exposed credentials associated with their domains, and investigate related artifacts such as cookies, host metadata, and malware attribution. The earlier exposure is identified, the greater the opportunity to remediate before attackers operationalize access. Flashpoint collects and parses some infostealer logs within one to two days of infection, helping organizations detect exposure closer to the point of compromise.

What should organizations do if employee credentials appear in an infostealer log?

Organizations should immediately assess the scope of exposure, reset affected credentials, invalidate active sessions, review authentication activity, investigate the infected device, and determine whether additional accounts or systems may have been impacted.

How is Flashpoint’s approach to infostealer intelligence different from traditional breach monitoring?

Many organizations rely on aggregated breach feeds or credential dumps that may be weeks or months old by the time they are discovered. Flashpoint’s Primary Source Collection (PSC) approach provides direct visibility into the forums, marketplaces, Telegram channels, and underground communities where stolen identity data is first shared, sold, and operationalized.

In addition to collecting raw infostealer logs, Flashpoint parses and enriches the data with context such as malware attribution, session cookies, host metadata, browser artifacts, and affected identities. Today, Flashpoint’s credential database contains more than 48 billion credentials, including over 1 billion tied to infostealer activity, providing organizations with actionable intelligence rather than raw exposure data.

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Understanding Illicit Ecosystems: Weaponizing Mainstream Apps and Social Infrastructure

As part of our ongoing series, we focus on the shared infrastructure that fuels threat actors; the intersection of mainstream social media, open-source messaging platforms, and gaming communities.

Threat actors and their illicit communities do not exist in a vacuum. To scale their operations, coordinate financial fraud, deploy malware, and recruit new talent, threat actors must interface with the broader digital world. This means leveraging everyday, public digital spaces to facilitate illicit activity, effectively hiding in plain sight.

The Clearnet Threat Landscape: Hiding in Plain Sight

When conceptualizing the cybercriminal underground, it is easy to focus exclusively on Tor-based onion sites or restricted-access dark web forums and marketplaces. However, a massive portion of modern illicit activity thrives on the clearnet. Threat actors heavily utilize commercial social media and public messaging networks to coordinate fraud, deploy malware, and run public relations campaigns for their operations.

At first glance, conducting illicit operations on highly monitored, mainstream platforms seems counterintuitive. However, the massive, continuous volume of legitimate traffic on the clearnet provides a form of operational security. By blending into the noise, threat actors can maintain a highly accessible digital presence. This visibility is crucial for their business models: it allows them to maintain a low barrier to entry for potential recruits and targets who know exactly what markers to look for, or who are systematically funneled into these spaces.

How Threat Actors Weaponize Consumer Platforms

The misuse of mainstream communication tools has changed how threat actors interact. Rather than waiting for users to seek out the dark web, cybercriminals are actively meeting their targets or co-conspirators on platforms designed for daily socialization.

Discord

Originally built to connect gaming communities, Discord’s rapid growth and robust infrastructure have inadvertently made it a target for malicious activity. Cybercriminals treat the platform as a multi-functional tool for both technical infrastructure, social engineering, and radicalization.

On a technical level, advanced persistent threats (APTs) and other threat actors exploit Discord’s content delivery network (CDN) to host and distribute malware. Because traffic to Discord domains is generally trusted by corporate networks, threat actors can potentially use it to deliver payloads—such as infostealers and remote access trojans (RATs)—bypassing standard security perimeters.

Beyond hosting malware, extremist groups across various ideological spectrums often target the platform’s demographic, which skews heavily towards younger tech-savvy users. This group provides an impressionable pool of adolescents who may be susceptible to grooming, indoctrination, and recruitment into illicit operations.

Case Study: The Targeting and Recruitment Mechanics of “The Com”

While monitoring The Com, Flashpoint analysts have observed the systematic use of platforms like Discord, Roblox, and Minecraft to run predatory extortion pipelines. The mechanics of this ecosystem takes place through a multi-phase methodology:

1. Platform Scouting: Recruiters patrol servers on popular youth-centric gaming platforms, such as Discord, Roblox, and Minecraft. They look for minors showing signs of social isolation, depression, disordered eating, or a desire to belong.
2. Building Trust and “Love Bombing”: Initial engagements are seemingly harmless. However, trust is built quickly to establish a sense of indebtedness. Recruiters offer gifts such as in-game perks/currency, premium subscriptions, or other digital items. In some cases, a romantic facade is used to establish a connection. In either scenario, “love bombing” creates an immediate feeling of psychological obligation in the target.
3. Platform Migration: Once rapport is established, the recruiter moves the target away from the game and into an encrypted app or private Discord server, following a public-to-private strategy. By moving the interaction away from the original platform’s safety controls, the recruiter can isolate the target in a more controlled environment.

Once isolated, perpetrators coerce victims into sending sensitive imagery or CSAM. This material is immediately compiled and weaponized as leverage for blackmail via doxxing. This creates a severe psychological trap in which the victim feels compelled to partake in escalating illegal activity to keep their previous actions hidden. This drives the victim to transition from a victim into an aggressor to escape their own abuse.

Telegram

While many social media and messaging platforms can serve as an initial funnel for engagement, Telegram has been known to be used from time to time as an operational hub for the broader illicit ecosystem. Since the arrest of Pavel Durov, Telegram has begun working more closely with law enforcement, leading to several key arrests and major disruptions due to their cooperation. 

The platform occupies a unique space in threat intelligence and open source intelligence (OSINT). While the vast majority of its user base is entirely benign, its minimal moderation policy and robust channel architecture have made it vital to public and private intelligence gathering.

Telegram functions as an open marketplace and real-time coordination center for a vast spectrum of threat actors. Flashpoint has observed it being used by:

1. State-sponsored APT groups and hacktivists
2. Geopolitical actors and mercenary groups distributing battlefield intelligence and propaganda
3. Cybercriminal syndicates coordinating financial fraud schemes, check fraud, and the sale of compromised data.

Furthermore, threat actors routinely use other public-facing platforms like X (formerly Twitter) alongside Telegram to amplify their impact. They leverage the broad reach of social media to broadcast proof of their compromises, hype up ransomware leaks, and exert public pressure on corporate victims during extortion cycles. Concurrently, Telegram often acts as the backend repository where the stolen data is hosted, discussed, and monetized.

Monitor the Clearnet Using Flashpoint

The evolution of illicit ecosystems demonstrates that the lines between the dark web and the clearnet have intersected. Whether analyzing the activities of extremist and threat actor groups or tracking the predatory pipelines of The Com, defenders must look beyond traditional intelligence sources.

Because malicious actors rely heavily on consumer messaging apps and social platforms to coordinate attacks, leak data, and target people, monitoring these public-to-private pipelines is an essential component of threat intelligence. Uncovering these physical and cyber threats requires best-in-class threat intelligence and OSINT investigations capable of parsing the massive noise of the clearnet to find the signals of illicit coordination.

Request a demo to see how Flashpoint empowers security teams to monitor these decentralized threat landscapes to proactively protect their critical assets.

Check out the rest of our “Understanding Illicit Ecosystems” series:

Understanding Illicit Ecosystems: The Hybrid Threat of “The Com”

Understanding Illicit Ecosystems: XSS and the Current State of the Russian-Speaking Underground

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Connecting Vulnerability Intelligence to Real-World Exposure With Flashpoint EASM

In this post, we explore how Flashpoint’s External Attack Surface Management (EASM) capability helps organizations continuously discover internet-facing assets, identify exposure to critical vulnerabilities, and prioritize remediation efforts based on real-world risk.

The volume of vulnerability disclosures is higher than ever, yet most security teams are still struggling to act.

From vulnerability scanners to public sources and AI-accelerated discovery, organizations are often drowning in findings, but lack the context to prioritize what affects their perimeter and is actively being exploited. 

Compounding this challenge is the growing issue of unknown and forgotten assets. Up to 95% of a company’s assets change each year, creating critical external blind spots and leaving them vulnerable to attacks on unmonitored infrastructure.

As attack surfaces expand due to cloud adoption, shadow IT, acquisitions, and distributed environments, many organizations struggle to maintain control over what assets they own, what software is running on those assets, and therefore, where exposures exist. You can’t patch what you don’t know is there.

These are the challenges Flashpoint External Attack Surface Management (EASM) is designed to address. With the introduction of EASM in Flashpoint Ignite, organizations can continuously discover internet-facing assets, map them to Flashpoint Vulnerability Intelligence, and prioritize remediation efforts based on actual risk rather than vulnerability volume and severity alone.

“The most effective vulnerability management programs are built on more than vulnerability awareness alone,” said Josh Lefkowitz, Co-Founder and CEO of Flashpoint. “Organizations need to understand where exposure exists within their environment and focus remediation efforts where they will have the greatest impact. Flashpoint EASM helps connect vulnerability intelligence directly to exposed assets, giving security teams a clear path from identification to remediation.”

Understanding the Exposure Gap

For many organizations, vulnerability intelligence is no longer the limiting factor.

Security teams have access to more vulnerability data than ever before. They can track newly disclosed vulnerabilities, monitor exploit activity, review KEV catalogs, and identify emerging threats often within hours of disclosure. And Flashpoint customers get the added advantage of learning about vulnerabilities up to 2 weeks faster than NVD, as well as the growing 105K+ vulnerabilities that never make it to public sources.

But understanding whether those vulnerabilities affect assets the organization actually owns remains a challenge. And that challenge exists because asset visibility and vulnerability intelligence often live in separate workflows.

• Asset inventories become outdated. 
• Cloud infrastructure changes constantly. 
• New internet-facing services appear without centralized oversight. 
• Acquisitions introduce unfamiliar infrastructure. 
• Shadow IT creates blind spots that security teams may not discover until after exposure is identified.

As environments become more dynamic, validating exposure often requires analysts to pivot between scanners, spreadsheets, asset inventories, cloud consoles, and vulnerability intelligence sources.

As a result, organizations must face a growing disconnect between understanding which vulnerabilities are out there vs. whether the organization is actually at risk.

Connecting Asset Discovery to Vulnerability Intelligence

Flashpoint EASM begins by discovering internet-facing assets associated with an organization, giving security teams an attacker’s-eye view of their external perimeter. Using seed domains and IP addresses, it initiates ongoing discovery across the external environment, uncovering infrastructure that often evades internal tracking, including:

• Shadow IT and untracked cloud resources
• Forgotten infrastructure and legacy internet-facing assets
• Newly exposed services and subdomains

Once assets are validated, they are surfaced within Ignite and automatically correlated with Flashpoint Vulnerability Intelligence, including pre-NVD findings, KEV intelligence, and proprietary vulnerability coverage beyond public sources. Teams receive alerts when new assets are discovered and when newly identified vulnerabilities affect monitored assets. For a full walkthrough of the workflow, see the Flashpoint EASM product update.

Prioritizing What Actually Requires Action

Not every vulnerability on your attack surface demands the same response. Flashpoint EASM helps teams cut through the noise by combining asset exposure with intelligence on what attackers are actively exploiting, so remediation efforts focus on the vulnerabilities that create meaningful risk.

Rather than focusing on vulnerability severity alone, security teams can now prioritize based on actual exploit activity targeting their attack surface. Flashpoint EASM provides the clarity needed to make that shift.

Building a Continuously Monitored, De-Risked Perimeter

As attack surfaces continue to evolve, organizations need full attack surface visibility, intelligence on what attackers are exploiting, and an efficient path to remediation.

By connecting Flashpoint Vulnerability Intelligence directly to their exposed assets, organizations can move from reactive investigation to having confidence that their external perimeter is continuously monitored and de-risked.

Learn more about Flashpoint External Attack Surface Management and request a demo.

Frequently Asked Questions (FAQ)

What is External Attack Surface Management (EASM)?

External Attack Surface Management (EASM) helps organizations discover, monitor, and assess internet-facing assets that could be exposed to attackers.

This includes domains, subdomains, IP addresses, cloud infrastructure, internet-accessible services, and other externally exposed assets that may introduce security risk.

By continuously monitoring these assets, organizations can better understand their external attack surface and identify exposures that require remediation.

How is Flashpoint EASM different from traditional asset inventories?

Traditional asset inventories, CMDBs, and internal scanners often depend on manual updates and may not reflect the full scope of an organization’s internet-facing environment.

Flashpoint EASM continuously discovers external assets and maps them to Flashpoint Vulnerability Intelligence, helping organizations identify exposures that may otherwise remain difficult to track through static inventories alone.

Why is attack surface visibility important?

As organizations adopt cloud services, acquire new businesses, deploy new applications, and support distributed environments, external attack surfaces change constantly.

Without continuous visibility, security teams may struggle to identify unknown assets, shadow IT, forgotten infrastructure, or newly exposed services that increase organizational risk.

How does Flashpoint EASM help prioritize remediation?

Knowing a vulnerability is severe is only half the picture. Flashpoint EASM correlates discovered assets with our proprietary vulnerability intelligence, including KEV data and pre-NVD findings, so teams can prioritize based on the severity of vulnerabilities present on their actual attack surface.

What vulnerability intelligence is included?

Flashpoint EASM integrates directly with Flashpoint Vulnerability Intelligence, including:

• Proprietary vulnerability coverage beyond public sources
• Pre-NVD vulnerability findings
• Known Exploited Vulnerability (KEV) intelligence
• Vulnerability enrichment and contextual risk information

This allows organizations to understand both exposure and vulnerability relevance within a single workflow.

Does Flashpoint EASM support continuous monitoring?

Yes. Once assets are discovered and validated, Flashpoint EASM continuously monitors the external attack surface for newly identified assets, vulnerable software, exposed services, and relevant vulnerability findings.

Teams can receive alerts when new exposure risks are identified.

How does Flashpoint EASM reduce alert fatigue?

Traditional vulnerability programs generate large volumes of findings without clarity on whether those assets are actually owned or exposed. Flashpoint EASM’s triage inbox lets teams accept true assets and reject noise, ensuring alerts are scoped only to infrastructure the organization actually owns.

Who should use Flashpoint EASM?

Flashpoint EASM is designed for security teams responsible for:

• Vulnerability management
• Attack surface management
• Exposure management
• Threat intelligence
• Security operations
• Risk management

It is particularly valuable for organizations seeking to connect vulnerability intelligence to real-world asset exposure and remediation priorities.

How does Flashpoint EASM work with Flashpoint Vulnerability Intelligence?

Flashpoint EASM extends the value of Flashpoint Vulnerability Intelligence by helping organizations understand where vulnerable assets exist within their external environment.

Rather than viewing vulnerability intelligence and attack surface visibility separately, organizations can use both capabilities together to identify exposure, prioritize remediation, and reduce risk more effectively.

Request a demo today.

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Understanding Illicit Ecosystems: XSS and the Current State of the Russian-Speaking Underground

In this post, we explore XSS’ shift from a unified forum to a scattered community spread across several competing factions.

What is XSS?

For more than two decades, XSS was the gathering ground for the Russian-speaking cybercriminal underground. Evolving from its former name, DaMaGeLaB, XSS evolved from a mid-tier message board into a top-tier hacking forum.

XSS is home to vendors of various crime types, including loaders, phishing, scamming, carding, malware development, distributed denial-of-service (DDoS) bots, and related services. It also facilitates the trade of illicit goods and services, while simultaneously serving as a networking and recruitment hub for threat actors.

XSS forum content falls within the following main sections:

• “Underground”: Includes most noncommercial content, such as sharing information on malware, vulnerabilities, and exploits, phishing, fraud, open source intelligence, artificial intelligence, and machine learning.
• “Programming, Development”: Includes posts and articles about programming languages and administration.
• “Library”: Includes news articles, databases, and discussions around software and tools. Users also post about vulnerabilities and exploits.
• “Business Decisions”: Users discuss different investments, the sale of digital goods, trading, start-ups of fraudulent businesses, and news about cryptocurrencies.
• “Lounge Zone, Resting”: Content involves lifestyle discussions, hobbies, and cybercriminal community rumors and scandals.
• “Trading Platform”: Users sell and look to buy network access, malware, counterfeit documents, and advertise their services. This is where users hire and look for work or partners.
• “People’s Court”: Used for complaints and arbitration and contains lists of phishing forums and scammers.
• “Ours”: Contains information about the XSS project, discussions on issues, suggestions, and initiatives for forum improvement.
• “Private: Underground”: Closed section for only forum members.

XSS Disruption: July 2025 Takedown

On July 23, 2025, law enforcement organizations reportedly seized XSS as part of a multinational operation with Ukrainian authorities, French police, and Europol. Alongside the domain seizure, French authorities reported the arrest of XSS’s longtime administrator in Ukraine.

This arrest triggered an immediate chain reaction that has had lasting effects on the Russian-speaking underground—with the XSS ecosystem splintering into several competing factions.

The Current State of the Russian-Speaking Underground

While the original XSS architecture was severely disrupted, the surrounding Russian-speaking cybercriminal ecosystem remains intensely active. However, instead of a centralized hub, the XSS ecosystem is spread out through competing environments that emerged directly from the fallout of the takedown.

DamageLib

Launched by the legacy moderators of XSS, DamageLib represents a structural pivot away from standard illicit forums. Concluding that the old XSS site was compromised by law enforcement, the moderators launched a new model that completely abandons commerce—shutting down all buying, selling, and auctions entirely—-to eliminate user tracking and surveillance. Instead, it focuses strictly on technical materials and tutorials.

Rehub

Recognizing that displaced cybercriminals still required a commercial venue to trade, a former XSS moderator launched Rehub quickly after the emergence of DamageLib. Rehub immediately integrated a commercial platform, successfully recruiting prominent threat actors into its moderation team to establish underground credibility.

The forum is still in its development stage, with its content being populated, and an active member base being built.

XSS[.pro]

In early August 2025, an unknown entity launched an alleged resurrection of the forum on a new domain [.pro], utilizing old backups that preserved legacy user data, threads, and forum deposits. However, this new version has been met with significant distrust from Exploit and DamageLib, believing the [.pro] domain to be a honeypot controlled by law enforcement.

XSSF Forum

Started by a pro-Russian Telegram hacking group, this community actively targets EU and Ukrainian digital infrastructure. According to user discussions on DamageLib, this forum is not related to XSS. In addition, Flashpoint analysts note that targeting Ukrainian infrastructure directly contradicts its original community rules. The authenticity of this forum and its ownership has not been verified.

Monitor a Fractured Underground Using Flashpoint

While law enforcement achieved a significant victory over XSS, they did not eliminate the Russian-speaking cybercriminal underground. Instead, they broke the foundational trust mechanics that had kept it centralized for twenty years.

This has left the Russian-speaking underground in a deeply fractured state that is still intensely active and highly adaptive. For defenders and analysts, this threat has not diminished—it has diversified. Tracking this ecosystem no longer means watching a single centralized community, but rather actively mapping out the live migrations, shifting rules, and behavioral patterns across these splintered groups.

Request a demo to learn how Flashpoint helps security teams aggregate intelligence from these scattered factions into a single source of truth, empowering your organization to proactively monitor and intercept emerging threats.

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How to Align and Measure Threat Intelligence Operations: Flashpoint Priority Intelligence Requirements

In this post, we explore how Flashpoint’s new Intelligence Requirements capability helps organizations define, manage, and operationalize PIRs directly within Ignite by connecting intelligence priorities, monitoring activity, investigations, and measurable operational outcomes into a more unified workflow.

For many intelligence teams, the hardest part of the intelligence lifecycle is no longer collection. It is operationalization.

Analysts are flooded with incoming activity every day, from credential exposures and actor chatter to vulnerability reporting and operational alerts. But without a structured way to connect those signals to business priorities and operational risk, many organizations still struggle to translate intelligence activity into actionable decisions and measurable outcomes.

That is exactly the problem Intelligence Requirements (IRs) are designed to solve.

With the introduction of Intelligence Requirements in Flashpoint Ignite, organizations can define, manage, and operationalize both General Intelligence Requirements (GIRs) and Priority Intelligence Requirements (PIRs) directly within their day-to-day intelligence workflows. By bringing intelligence priorities, monitoring activity, investigations, and reporting into a more unified operational model, teams can create clearer alignment between intelligence operations and organizational risk.

With Intelligence Requirements, organizations can:

• Centralize and structure General Intelligence Requirements and Priority Intelligence Requirements (PIRs) directly within Ignite to create clearer alignment across intelligence operations.
• Connect alerts and monitoring activity to business priorities and organizational risk to improve focus and prioritization.
• Tie intelligence findings directly to Investigations workflows to support faster triage, collaboration, and response.
• Accelerate adoption with pre-built PIR templates or create custom intelligence requirements tailored to organizational priorities.
• Gain measurable visibility into intelligence activity, investigative trends, and how CTI supports operational and business outcomes.

“The most effective threat intelligence programs are the ones aligned directly to the priorities that matter most to an organization — from reducing operational risk to enhancing executive and mission-level decision-making,” said Josh Lefkowitz, Co-Founder and CEO of Flashpoint. “With Intelligence Requirements, Flashpoint is helping organizations with the critical effort to define and operationalize those priorities across intelligence workflows — creating a clearer connection between threat intelligence programs and outcomes.”

Turning Intelligence Priorities Into Operational Workflows

At its core, a Priority Intelligence Requirement represents a question an organization needs answered.

Examples might include:

• Are credentials tied to our organization appearing in underground communities?
• Is a ransomware group targeting organizations in our industry?
• Are discussions about our executives increasing across threat actor forums?
• Is new malware infrastructure emerging that overlaps with our environment?

Historically, PIRs have existed outside operational workflows entirely — tracked through spreadsheets, slide decks, ticketing systems, or institutional knowledge spread across analyst teams. Meanwhile, alerting, investigations, and reporting frequently operated across disconnected processes, making it difficult to maintain clear alignment between intelligence activity and organizational priorities.

The challenge is, as intelligence programs scale, that fragmentation creates operational friction. Analysts spend more time organizing workflows, managing signals, and explaining priorities instead of focusing on the intelligence questions that matter most.

Inside Ignite, Intelligence Requirements provide a more structured operational framework that connects:

• Intelligence priorities
• Monitoring activity
• Investigations
• Triage workflows
• Collaboration
• Operational outcomes

Building Signals Around Intelligence Questions

Once an Intelligence Requirement is defined, teams can begin building the signals designed to answer that requirement.

This transforms the role alerting plays within intelligence operations.

Rather than creating isolated alerts with little context, analysts can associate alerts directly to specific Intelligence Requirements. Those alerts become observable signals tied to the intelligence questions the organization is trying to answer.

For example:

• A credential exposure alert may support an identity-focused PIR
• Ransomware reporting alerts may support an executive risk PIR
• Actor chatter or malware discussions may support a geopolitical monitoring PIR

This creates significantly more clarity for analysts:

• Why does this alert exist?
• What intelligence priority does it support?
• Which signals are actually producing meaningful operational value?

As intelligence programs mature, that visibility becomes increasingly important beyond the analyst team itself. Security leaders are under growing pressure to explain how intelligence activity supports operational priorities, business risk reduction, and executive decision-making.

By organizing alerts around intelligence requirements instead of individual datasets alone, organizations gain a more operational view of intelligence activity and its relevance to broader business objectives.

Creating a Stronger Feedback Loop Between Monitoring and Prioritization

One of the biggest challenges intelligence teams face today is alert fatigue.

Large volumes of alerts can overwhelm analysts and obscure the signals most relevant to operational risk. Over time, this makes it harder to prioritize analyst attention, refine monitoring strategies, and understand which intelligence activity is actually producing operational value.

Intelligence Requirements help bring more structure and context to monitoring workflows by connecting incoming activity directly to defined intelligence priorities.

Instead of reviewing alerts in isolation, analysts can evaluate activity within the context of the PIRs it supports. This gives teams clearer visibility into:

• Which signals consistently produce meaningful intelligence
• Where noisy monitoring workflows are slowing analysts down
• Which intelligence priorities are driving the most operational activity
• How analyst effort aligns to organizational risk

Over time, this creates a stronger operational feedback loop. Monitoring workflows can be refined based on investigative outcomes, low-value signals become easier to identify, and teams gain a clearer understanding of which intelligence activity deserves the most attention.

The result is a more intentional and measurable approach to intelligence monitoring that helps analysts spend less time managing noise and more time focusing on operationally relevant signals.

Connecting Intelligence Activity to Collaborative Investigations

Prioritizing signals is only part of the workflow.

When activity warrants deeper analysis, analysts can move directly from alert triage into Investigations within Ignite. This is where Intelligence Requirements begin connecting monitoring activity to collaborative operational response.

Investigations provide a centralized environment where teams can organize findings, preserve investigative context, track evolving activity, coordinate across stakeholders, and develop operational reporting around emerging threats.

Importantly, investigations remain connected back to the original Intelligence Requirement, helping preserve the broader operational context behind the work and maintain alignment between investigative activity and organizational priorities.

This creates a more continuous operational process:

1. Define the intelligence question
2. Build monitoring workflows around relevant signals
3. Prioritize incoming intelligence
4. Escalate meaningful findings into investigations
5. Collaborate, analyze, and report on operational activity
6. Refine monitoring workflows based on outcomes

Within Ignite, analysts can also leverage AI Workspace capabilities to accelerate analysis, summarize investigative findings, and support downstream reporting workflows.

By connecting monitoring, investigations, collaboration, and analysis within the same operational framework, organizations gain a clearer understanding of how intelligence activity supports operational decision-making and business risk management.

Supporting More Mature Intelligence Operations

As threat environments become more complex, operational maturity increasingly depends on an organization’s ability to connect priorities, monitoring activity, investigations, and outcomes within the same framework.

That challenge extends beyond the analyst team itself. Intelligence leaders are increasingly expected to demonstrate how intelligence activity supports operational priorities, informs risk decisions, and contributes to broader business objectives.

Intelligence Requirements help organizations create a more structured and measurable operational model by connecting intelligence priorities directly to monitoring workflows and investigations inside Ignite.

Over time, this gives organizations clearer visibility into:

• which priorities are generating operational activity
• where analysts are spending investigative effort
• how intelligence supports organizational risk management
• how CTI workflows contribute to operational and business outcomes

By reducing fragmentation across workflows and maintaining stronger alignment between intelligence activity and organizational priorities, teams can spend less time managing process and more time focusing on the intelligence questions most relevant to the business.

Learn more about Flashpoint Intelligence Requirements and request a demo.

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The Mini Shai-Hulud Worm and the New Era of CI/CD Exploitation

In this post we break down the technical mechanics of TeamPCP’s recent campaign, the impact on the developer ecosystem, and the urgent steps needed to secure software supply chains.

The developer ecosystem recently faced one of its most significant architectural threats to date, with the threat actor group TeamPCP unleashing Mini Shai-Hulud—a self propagating worm and multi-ecosystem threat. Potentially affecting millions of developers and thousands of companies, Mini Shai-Hulud has fundamentally compromised the trust layer of modern CI/CD pipelines.

The operational tempo of Mini Shai-Hulud has accelerated with every campaign. What began as opportunistic credential theft has now evolved into a high-speed, automated operation that can compromise hundreds of packages in under thirty minutes. From the exfiltration of approximately 3,800 internal GitHub repositories to the poisoning of critical libraries like TanStack and AntV, TeamPCP’s campaign has been incredibly effective in exploiting developer tooling and identity infrastructure.

What is Mini Shai-Hulud?

Mini Shai-Hulud is deployed as a 498 KB obfuscated script executed using the Bun JavaScript runtime. The deliberate choice of Bun, rather than Node.js, is a tactical evasion technique as most endpoint detection and response (EDR) platforms and security information and event management (SIEM) solutions have behavioral rules tuned to Node.js execution patterns.

How Mini Shai-Hulud Works

The worm propagates by stealing npm and GitHub authentication (OIDC) tokens from developer environments, then using those credentials to publish malicious versions of packages the compromised user maintains. To accomplish this, the worm scrapes runner process memory to extract short-lived identity tokens, which it then exchanges for per-package npm trusted-publisher tokens without requiring any long-lived npm secrets.

Credential Exfiltration and Command-and-Control

Mini Shai-Hulud targets credentials across 130 file paths, including npm tokens, GitHub personal access tokens, AWS, GCP, and Azure configuration files, Kubernetes kubeconfig files, Docker credentials, HashiCorp Vault tokens, 1Password and Bitwarden CLI vaults, SSH private keys, and Bitcoin wallet files. 

Exfiltration occurs across multiple channels: the Session Protocol network, the GitHub Git Data API using dynamically created Dune-themed repositories on victim accounts, HTTPS to the threat actor-controlled domain, and an api for GitHub Actions workflow exfiltration.

The worm uses a dead-drop command-and-control (C2) architecture via GitHub’s public commit search API. An installed daemon (kitty-monitor, deployed as a systemd service on Linux or a LaunchAgent on macOS) polls GitHub for commits containing the string “firedalazer,” parses RSA-PSS-signed command payloads from matching commits, and executes them. This technique leverages GitHub as a trusted relay, making C2 traffic difficult to block without disrupting legitimate GitHub usage.

The worm then uses a persistence mechanism as a dead-man’s switch: a GitHub personal access token named “IfYouRevokeThisTokenItWillWipeTheComputerOfTheOwner” is created on compromised developer machines. If an operator revokes this token without first disabling the persistence mechanism, the worm destroys all home directory data on the compromised device.

AI Agent Hijacking

Beyond standard persistence mechanisms, Mini Shai-Hulud targets AI coding agents. The SafeDep analysis documents that the worm modifies Claude Code’s settings .json to insert a SessionStart hook, enabling the worm to be reinstated with full LLM API privileges even if the infected npm packages are later removed, or the npm cache is cleared. A similar technique targets Visual Studio Code’s tasks.json file using the “runOn”: “folderOpen” trigger, and Codex configuration files are also targeted.

These AI agent hijacking techniques represent a novel attack surface: by persisting within trusted AI tool configurations, the malware can exfiltrate all code and secrets processed by those tools during future development sessions.

Four Waves of Supply Chain Attacks

Flashpoint has observed at least four documented waves of TeamPCP npm and PyPI supply chain attacks in 2026, leveraging Mini Shai-Hulud to compromise developer tooling ecosystems and steal credentials, cloud keys, and source code across tens of thousands of organizations. 

The following timeline tracks the escalation of TeamPCP and the Mini Shai-Hulud waves throughout 2026:

Wave 1: Initial SAP Packages (April 2026)

The first documented wave of Mini Shai-Hulud attacks targeted a small number of SAP-ecosystem npm packages in April 2026. While TeamPCP had already proven their CI/CD attack capabilities in March 2026 by compromising Aqua Security’s Trivy scanner and Checkmarx KICS via GitHub Actions, this initial wave served primarily as a proof-of-concept for the self-propagation mechanism and a reconnaissance phase for TeamPCP’s access broker network. Further, these attacks demonstrated the group’s ability to compromise widely used security tooling—a development that significantly undermines defenders’ ability to trust automated CI/CD pipeline scanning results.

Wave 2: TanStack, Mistral AI, and Guardrails AI (May 2026)

Leveraging a GitHub Actions cache-poisoning technique, TeamPCP published malicious versions of 42 TanStack packages across 84 releases, impacting a project with over 518 million cumulative downloads. 

The attack also compromised Mistral AI and Guardrails AI, extending the attack surface to the AI developer tools ecosystem. Forged commit authorship was used to blend the attacker’s commits into AI-assisted development environments where Claude Code is commonly deployed.

TeamPCP simultaneously listed Mistral AI source code for sale on BreachForums, claiming possession of approximately 5 GB of data across 450 internal Mistral repositories.

Wave 3: AntV Ecosystem (May 2026)

Targeting AntV enterprise data visualization ecosystem, TeamPCP compromised the atool npm account, which held publishing rights across a broad catalog of AntV packages. In 22 minutes, 637 malicious versions were published across 323 packages—a scale and speed that overwhelmed standard security monitoring pipelines.

Each infected package contained the Mini Shai-Hulud worm, which, upon execution, created up to 2,500 compromised repositories on victim accounts within hours.

Wave 4: Co-Ownership of BreachForums and GitHub Breach

In the most recent wave, TeamPCP announced its assumption of co-ownership of BreachForums, the largest English-language cybercriminal forum currently active. This development significantly elevates TeamPCP’s standing and operational reach. As co-owners, the group stated it would manage platform operations, handle dispute resolution, staff and vet moderation personnel, and host monetary contests for the community. The announcement positions TeamPCP as both an active threat actor and a platform-level infrastructure operator, with the ability to shape forum policies, curate the availability of criminal tooling, and influence the broader access broker and ransomware ecosystem.

Additionally, by poisoning a GitHub employee’s development environment, TeamPCP exfiltrated approximately 3,800 internal GitHub repositories. Within the stolen data were highly sensitive codebases such as:

• copilot-api and copilot-token-service
• actions-runtime
• billing-platform
• enterprise-crypto
• authentication
• codeql-core
• detection-engineering
• csirt
• azure-config

Recommended Immediate Actions

Critically, the theft of internal source code from one of the world’s most widely used code hosting platforms creates incredible downstream risk for organizations that depend on GitHub Copilot and GitHub Actions for their own software development pipelines. Organizations running AI coding agents such as Claude Code and VS Code with extensions in their CI/CD pipelines face heightened exposure. Security teams should treat AI agent configuration files as sensitive assets subject to integrity monitoring and change-control policies.

If your organization uses npm, PyPi, or AI-assisted development tools, Flashpoint recommends the following immediate steps:

1. Audit and remove: Immediately audit CI/CD environments and remove all infected versions of AntV, TanStack, Mistral AI, and Bitwarden CLI packages.
2. Rotate credentials: Rotate all cloud credentials (AWS, GCP, Azure) and npm tokens.
3. Disable persistence first: Before revoking suspicious GitHub tokens, ensure the kitty-monitor daemon is disabled to avoid triggering the “dead-man’s switch” wiper.
4. Lock down IDEs: Restrict the installation of VS Code extensions to an approved allow-list and monitor for unauthorized changes to settings.json or tasks.json.
5. Block C2 infrastructure: Block all traffic to identified TeamPCP C2 domains.

Track TeamPCP and Defend against Mini Shai-Hulud Using Flashpoint

Flashpoint assesses with high confidence that TeamPCP will continue to scale its supply-chain attacks against npm, PyPI, and developer tooling ecosystems. The group’s shift from direct execution to orchestrating a broader ecosystem via BreachForums signals a maturation into a platform-layer criminal operation. While TeamPCP has hinted that the group may be approaching “retirement” due to law enforcement pressure, this should be treated with caution. Whether a misdirection or a genuine exit plan, the open-sourcing of Shai-Hulud means the tradecraft is available to the wider cybercriminal community.

Organizations should reference the OpenSSF npm Best Practices guidance for a practical baseline in hardening their package consumption posture. Flashpoint customers can gain access to known Indicators of Compromise (IOCs) and MITRE ATT&CK Mapping for Mini Shai-Hulud by logging into Flashpoint Ignite. To learn more about how Flashpoint tracks threat actor groups like TeamPCP and protects the software supply chain, request a demo.

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Understanding Illicit Ecosystems: The Hybrid Threat of “The Com”

In this post, we dive into the decentralized architecture of “The Com,” exposing its hybrid ecosystem of hacking, extortion, and real-life violence—and how it fuels a ruthless pipeline of cyber-fraud cycles and adolescent exploitation.

What is “The Com”?

The Community, more widely known as “The Com” is a sophisticated hybrid threat ecosystem in which cybercrime serves as the venture capital for domestic terrorism. Existing since the early 2010s, it operates in the “edgesphere”, a grey area where mainstream social media overlaps with underground criminal networks, blending nihilistic violent extremism (NVE) with high-level financial fraud. In The Com, cybercrime against Fortune 500 companies is the primary revenue stream used by members to fund a domestic terror network that aims to radicalize youth and encourage real-world violence.

However, The Com poses more than just financial risk, it is a self-serving victim-to-perpetrator pipeline. It uses stolen capital to recruit adolescents, who they view as a disposable workforce, turning them from a victim to a perpetrator. Despite being a decentralized web of individuals rather than a traditional threat actor organization, The Com has managed to grow by hiding in the gaps between corporate security, parental oversight, and law enforcement.

How The Com is Structured

The Com is often mischaracterized as a single, formal organization. In reality, its ecosystem is unstructured and lacks a shared culture or leadership. However, the various factions within the ecosystem are extremely organized, supporting three broad categories of criminal activity: cybercrime, exploitation of minors, and real-world physical violence.

Federal investigations have shown that The Com includes a mix of adults and minors, men and women. While the exact number of members is difficult to determine, Flashpoint estimates that the broader ecosystem of The Com is in the thousands. While being a global threat, its most active core members are concentrated in Western English-speaking countries: the United Kingdom, the United States, and Canada.

Understanding the Key Pillars of The Com

While The Com is a decentralized ecosystem, its internal structure is defined by a high degree of operational alignment. Individual crews and networks within each pillar exhibit a shared psychology and standardized tradecraft that ensures their criminal activities remain effective and repeatable.

However, Flashpoint notes that members of these pillars do not operate alone. Their interaction with members of other pillars (extortion and real-world violence) amplifies the intended threat.

HACKER Com: The Economic Engine of The Com

Hacker Com acts as the ecosystem’s economic engine and primary technical arm. Its primary function is to hack major corporations and commit financial fraud to fund the broader community’s activities and lifestyle.
Seeing themselves as the elite technical tier of The Com, Hacker Com members are motivated primarily by financial gain and the thrill of outsmarting corporate security infrastructures. Notable crews within this pillar include Scattered Spider, LAPSUS$, ShinyHunters, and DragonForce.

TTPs Used by HACKER Com

The following tactics, tools, and procedures (TTPs) have been observed by HACKER COM groups:

Social Engineering (Vishing)

Hacker Com members capitalize on TTPs that target human vulnerabilities instead of relying solely on software and other exploits. Vishing is a signature move of the Scattered Spider crew, whose native English-speaking members call corporate IT helpdesks impersonating employees of that company. 

Analysts note these threat actors are likely Gen Z who socially engineer older support staff by mimicking the impatient attitudes and vernacular of young tech executives, essentially hacking the generation gap. They leverage this form of social engineering to convince support staff to reset passwords or even re-enroll new multifactor authentication (MFA) devices, which grants them access to the victims’ networks.

Supply Chain Targeting

Crews in this pillar have also successfully breached major targets by attacking their trusted vendors. For instance, Lapsus$ compromised Okta by targeting its third-party contractor, Sykes, while Scattered Spider has repeatedly targeted Okta’s identity services to pivot into their clients’ networks.

Living-off-the-land (LOTL)

Once inside a network, threat actors avoid detection by using legitimate, preexisting software and other remote admin tools such as AnyDesk, Ngrok, and Teleport to maintain persistence and move laterally. They often gamify this access, mocking victims for allowing them to simply “log in” using standard admin tools rather than having to hack their way in via complex exploits. They treat the ease of access as a testament to the victim’s incompetence.

SIM Swapping

A SIM swap attack is a foundational TTP used by financially motivated actors that involves social engineering mobile carriers to hijack a target’s phone number, usually resulting in the takeover of high-value cryptocurrency accounts.

EXTORT Com: The Ideological Engine of The Com

The Extort Com pillar functions as a machine designed for psychological control, coercion, and sexual exploitation of minors. Its goals intersect squarely with NVE ideologies, resulting in a marketplace and production center for CSAM and extreme violence, where members often trade these materials as a form of social currency.

Targets are migrated from public channels, which include social media and video games such as Roblox and Minecraft, to private ones maintained by The Com. Once moved, the dynamic shifts from recruitment to active exploitation, which is done to ensure the victim’s compliance.

IRL Com: The Enforcement Engine of The COM

The “In Real Life” (IRL) pillar serves as the physical enforcement arm of the ecosystem, effectively bridging the gap between virtual threats and reality. Sometimes referred to by law enforcement as “IRL Terror,” members often turn online animosity and disputes into real-world harm against people and their property.

Protect Against Converging Threats Using Flashpoint

The evolution of The Com represents a fundamental shift in the global threat landscape. It is not enough to view cybercrime as a purely financial risk or domestic extremism as a purely ideological one, the two have merged into a self-sustaining engine where stolen corporate capital fuels the radicalization and exploitation of the next generation.

As The Com continues to professionalize its tradecraft and expand its reach, the boundary between our digital and physical worlds will only continue to thin. To protect against this decentralized threat, organizations will require a mutli-layered defense strategy that is powered by intelligence that is sourced at the heart of these groups. Request a demo to learn more.

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AI Threat Report: How Artificial Intelligence Is Used Across Illicit Communities

A monthly analysis of how artificial intelligence is used in illicit communities, based on Flashpoint proprietary intelligence and direct visibility into real threat actor environments.

It seems to be a Tuesday morning like any other. A finance employee joins a video call with their CFO and several colleagues. The request appears to be routine. The faces match. The voices sound authentic. Minutes later, $25 million is transferred—only to be discovered later that every participant on the call, except one, was AI-generated.

Techniques behind incidents like this—synthetic video, voice cloning, scripted interactions—are now being discussed openly in the same environments where threat actors exchange tools and methods. In July 2026 alone, Flashpoint analysts identified more than 5.5 million posts discussing artificial intelligence in the context of illicit activity.

This volume reflects a larger shift: Artificial Intelligence (AI) is now deeply embedded across cybercrime ecosystems, heavily influencing fraud, impersonation, social engineering, and access operations. It alters how malicious content is generated, how identities are replicated, and how automated workflows are executed and refined over time.

To track this evolution, our monthly AI Threat Report analyzes primary source communities across forums, marketplaces, and chat services. By isolating the tactics, tools, and operational patterns shaping malicious AI use, our latest data reveals an aggressive focus on prompt-sharing, jailbreak methods, and alternative models that lack standard moderation controls.

AI Activity Volume and What It Represents

Flashpoint analysts identified 5,575,564 posts discussing AI and criminal activities in July 2026. In June, Flashpoint observed 4,718,651 posts, marking a 18% month-over-month increase.

The underlying activity was concentrated around a familiar set of use cases:

• Identity verification bypass
• Fraud enablement and scripting
• Impersonation through synthetic media
• Prompt-sharing and jailbreak workflows

Where AI Activity Is Concentrated

While AI-related chatter remained concentrated on a small handful of platforms, with Telegram accounted for the absolute majority of observed activity. Reddit, GitHub Gist, Pastebin, 4chan, Discord, and Mastodon followed, seeing significantly lower volumes. The vast majority of illicit AI distribution was driven by threat actor communities selling custom-built, open-source LLMs.

The massive Telegram volume highlights its role as a heavily saturated distribution layer. Threat actors frequently spam messages across channels for maximum exposure, making it a primary marketplace for prompts, jailbreak methods, fraud tooling, and service advertisements.

Throughout the month, the same offers and workflows appeared repeatedly across different channels, often tweaked based on user feedback or platform updates. Meanwhile, alternative platforms served more targeted roles:

• GitHub Gist and paste sites hosted scripts and technical supporting material.
• Underground forums supported reputation building and long-form technical discussions.
• Discord and Reddit communities centered around specific models, prompt collections, or jailbreak workflows.

Because these environments remain interconnected, techniques introduced in one community frequently reappear elsewhere the moment they prove to produce reliable outputs or successfully evade moderation controls continue to gain traction and which techniques are becoming more broadly operationalized.

AI-Enabled Fraud and Identity Verification Bypass

Flashpoint analysts observed a considerable drop in identity evasion activity in July, recording 394,567 posts advertising or discussing Know Your Customer (KYC) bypass methods—which include deepfake-enabled verification workflows.

This activity was highly concentrated across Telegram channels dedicated to identity fraud, with posts consistently advertising:

• Synthetic video generation designed to mimic live verification behavior.
• Voice cloning and scripted interaction prompts.
• Bundled “KYC bypass kits” tailored to specific onboarding systems.

Some offerings included step-by-step guidance on adapting responses for specific financial platforms. Others promoted end-to-end combinations of synthetic video, matching fraudulent documentation, and AI-generated scripts to fully automate impersonation attempts.

This activity connects directly to the broader access ecosystem. Stolen credentials, session tokens, and phishing infrastructure are increasingly combined with AI-enabled impersonation within the same operational workflows. For security teams, this means verification systems, onboarding processes, and account recovery layers are being actively tested and systematically targeted in the same environments where these methods are exchanged and improved.

Malicious LLM Usage and Prompt-Based Workflows

Discussions tied to malicious or unrestricted LLM usage focused heavily on jailbreak methods, prompt-sharing, and access to alternative models perceived as less restricted than mainstream platforms. Threat actors continue to rely on unrestricted models to generate phishing links, build harmful code, or craft offensive media.

The underground market centers on usability and output reliability, with frequent references to:

• Jailbreak prompts designed to bypass safety guardrails.
• Phishing and fraud-oriented prompt collections.
• Step-by-step instructions for generating specific malicious outputs.
• Requests for prompts tailored to social engineering campaigns.

Many of these prompts are shared in active, living collections that include updates and troubleshooting channels. When a prompt stops working or a platform introduces new restrictions, users exchange feedback and roll out updated versions within hours.

This behavior reinforces how prompt engineering has developed into its own service layer across illicit communities. The emphasis remains on accessibility, portability, and ease of use rather than custom, ground-up model development.

What Security Teams Should Take Away

The underground activity tracked this month shows how artificial intelligence is being operationalized in environments where techniques are developed, tested, and shared long before they surface in the wild.

Because these methods are structured for easy deployment, they require very little modification to move from a forum discussion into an active attack vector. For security teams, the priority must be maintaining direct visibility into how these methods are evolving. Understanding which techniques are actively in circulation is the only way to build earlier detection and more focused defenses at the control layer.

If you want to see how this activity maps to your environment, request a demo.

Frequently Asked Questions (FAQ)

What is the Flashpoint AI Threat Report?

The Flashpoint AI Threat Report is a monthly intelligence analysis tracking how threat actors operationalize artificial intelligence across illicit communities. Built on Flashpoint’s primary source collection, this report provides proprietary visibility into underground forums and dark web marketplaces. The report isolates emerging cybercrime trends, jailbreak workflows, synthetic media fraud, and malicious language model usage.

How are threat actors currently using AI in cybercrime?

Threat actors primarily use AI to automate and refine existing attack vectors. Key operational use cases include:

• Identity Verification Bypass: Creating deepfake video and voice clones to circumvent Know Your Customer (KYC) checks. 
• Social Engineering: Generating natural, multi-language phishing scripts and executive impersonations.
• Prompt Engineering & Jailbreaks: Exchanging prompts to bypass guardrails on mainstream LLMs.

How rapidly is illicit AI activity growing in cybercrime communities?

Illicit AI activity is growing exponentially. Flashpoint analysts identified 5,575,564 posts discussing AI and criminal activities in July 2026—an 18% month-over-month increase from the 4,718,651 posts recorded in June 2026. This rise highlights how AI tools have become deeply embedded in the daily operations of underground threat ecosystems.

Which messaging platforms and forums host the most illicit AI chatter?

1. Telegram: Hosts the vast majority of illicit AI activity, functioning as a heavily saturated marketplace for trading prompts, jailbreak scripts, and KYC bypass kits. 
2. GitHub Gist & Pastebin: Host supporting scripts and technical code snippets. 
3. Discord & Reddit: Host community discussions around prompt collections and specific LLM models.

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How Mergers and Acquisitions Expand Your Attack Surface Overnight

This post details how M&A activity can turn an acquisition target into an entry point into your environment and how to identify and reduce that exposure before it’s leveraged by threat actors.

M&A activity introduces immediate external exposure.

As soon as a deal is announced, the target’s infrastructure, access points, and identity footprint become relevant to a larger organization. Threat actors track acquisition activity and begin probing newly relevant environments quickly, often before integration planning is complete.

In one recent case, an external assessment of an acquisition target identified a publicly accessible VPN management interface tied to known exploited vulnerabilities. The configuration allowed session hijacking without credentials and had not been identified during internal reviews or due diligence. It was remediated within 24 hours of discovery.

The issue was reachable from the internet and aligned with active exploitation.

What Changes During an Acquisition

From a security perspective, the environment does not change at announcement. The context around it does.

The same systems, credentials, and configurations now sit within:

• A higher-value organization
• A broader identity and access ecosystem
• A timeline where ownership and responsibility are shifting

That shift is enough to change how the environment is targeted.

Threat actors monitor acquisition activity because it helps them prioritize. A smaller organization with uneven controls becomes more valuable once it is tied to a larger parent. Access pathways that previously led to a limited environment may now provide a stepping stone into something much larger.

How Adversaries Approach M&A Activity

Observed behavior around acquisitions is consistent across sectors.

Actors look for environments that:

• Expose remote access infrastructure (VPN, RDP, administrative interfaces)
• Contain credentials already circulating from infostealer infections
• Run edge devices tied to known exploited vulnerabilities
• Maintain assets that are reachable but not actively monitored

They do not need full network visibility. They work from what can be discovered externally and validated quickly.

In several cases, ransomware operators and access brokers have been observed scanning for specific device types or software versions shortly after acquisition announcements, aligning targeting with known exposure patterns.

Why Traditional Due Diligence Doesn’t Surface This

Due diligence produces a structured view of security posture. External exposure requires a different lens.

Most diligence processes rely on:

• Self-reported controls
• Point-in-time vulnerability data
• Documentation of architecture and policy

They rarely include:

• Direct validation of internet-facing systems
• Mapping of externally reachable assets
• Alignment with current exploitation activity

This creates a gap between what is documented and what is accessible.

The exposure that matters most during this phase tends to sit outside formal reporting: edge infrastructure, unmanaged assets, and access points that have not been recently validated.

The Role of Identity in M&A Risk

Identity expands alongside infrastructure. Employee credentials tied to the target organization may already be compromised through infostealer infections. Those credentials often include:

• Corporate email and password combinations
• Session cookies tied to SaaS platforms
• Autofill data and device metadata

Once an acquisition is announced, those credentials become more valuable. They are tested against:

• VPN gateways
• Cloud platforms
• Internal applications exposed through remote access

Where Exposure Persists

Across M&A activity, a few categories show up consistently when environments are assessed externally.

Remote access remains one of the most reliable entry points. VPN gateways and administrative interfaces are frequently exposed and often lag behind patch cycles tied to active exploitation.

Edge devices introduce additional risk. Firewalls, load balancers, and network appliances are commonly targeted when they run software associated with known exploited vulnerabilities.

Untracked infrastructure also plays a role. Smaller organizations often maintain systems outside formal asset inventories. These systems remain reachable and are rarely monitored closely.

These conditions are present before integration begins and remain in place until they are actively addressed.

Timing and Execution

The period immediately following an announcement carries the highest concentration of unknowns.

• Security ownership is in transition.
• Monitoring coverage may not extend across the target environment.
• External exposure remains unchanged.

At the same time, the environment is receiving more attention.

In the earlier example, remediation occurred within a day of discovery. Without that visibility, the same exposure would have remained available during a period of increased interest.

What This Looks Like in Practice

The teams that manage M&A risk effectively start from the outside and move inward.

The first step is establishing visibility into the target’s external footprint as soon as a deal becomes public. This includes identifying internet-facing infrastructure, exposed services, and access points that can be validated directly.

From there, the focus shifts to prioritization. Exposure is evaluated based on exploitability and alignment with current attacker behavior. Systems tied to known exploited vulnerabilities, remotely accessible services, and credential-based access paths rise to the top quickly.

Validation follows. Exposed systems are confirmed, configurations are reviewed, and access pathways are tested to determine what is actually reachable.

Once confirmed, response is immediate. High-risk exposure is remediated or restricted without waiting for integration milestones or broader security alignment.

This sequence is consistent across environments:

• Establish visibility into internet-facing assets early
• Validate exposed services and access points directly
• Prioritize based on exploitability and active targeting
• Act on confirmed exposure as soon as it is identified

Teams are at an advantage when they start this work while the environment is still limited in scope and before external attention translates into access.

See It in Your Environment

M&A activity introduces risk on a compressed timeline. External exposure does not wait for integration plans, and neither do attackers. If you’re supporting acquisitions, the first step is understanding what is already visible and reachable from the outside.

Flashpoint helps security and threat intelligence teams map internet-facing assets, identify exposed access points, and prioritize risk based on real-world exploitation and adversary activity.

Request a demo to see how Flashpoint supports acquisition-driven risk assessments, so you can identify and reduce exposure before it becomes an incident.

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The Evolution of the Geotag: How AI is Bridging the Gap in Location-Based OSINT

In this post, we explore how the decline of geotagged data is reshaping location-based OSINT, the intelligence gaps it creates for analysts, and how AI-driven keyword generation and geofencing are restoring visibility into real-world events.

For years, location-based open-source intelligence (OSINT) has relied heavily on a steady stream of user-generated geographic data. Geotagged social media posts with embedded latitude and longitude coordinates have long been a goldmine for tracking regional trends, monitoring real-time events, and understanding on-the-ground public sentiment. Intelligence professionals and data scientists have historically used this passively-generated location-based data to aggregate real-time insights for everything from tracking public sentiment to monitoring natural disasters.

However, the era of effortless geographic tracking is coming to an end. Geotagged social media data is becoming increasingly scarce, making it significantly harder for security teams to gather a complete picture of location-based intelligence.

The Decline of Location Sharing

The primary driver behind the diminishing use of geotags is a massive shift in digital privacy standards. For instance, major platform-level policy interventions, such as Apple’s November 2021 iOS privacy update, changed the default consent model for device tracking. Instead of requiring users to actively opt out of location tracking, iPhone users must now explicitly opt in.

As a result of these strengthened privacy controls, a massive behavioral shift occurred: within a year of the iOS update, 62% of affected users chose to opt out of location tracking entirely. This platform-mediated behavioral barrier has drastically reduced the availability and visibility of granular location traces, creating complex new blind spots for researchers and intelligence analysts.

The Intelligence Gap

With precise coordinates disappearing from social feeds, security practitioners and OSINT investigators are left facing a major data void. Relying purely on traditional keyword or hashtag searches to find location-specific events is highly inefficient. In fact, as little as 7% of social media posts actually contain hashtags. If an analyst is scanning 10,000 posts a day looking for a specific hashtag, they could be missing up to 9,300 posts that hold critical intelligence.

To compensate for missing geotags, security practitioners have traditionally had to spend valuable time performing manual, tedious searches for specific local details like street names, landmarks, and local businesses to figure out where an event is taking place.

Bridging the Gap with AI

To overcome the increasing scarcity of explicit location data, the intelligence industry is leveraging artificial intelligence and spatial technologies.

AI-powered keyword optimization tools like Echosec’s new AI-powered “Optimize” feature are designed specifically to bridge this data gap. Instead of relying on users to share their precise coordinates, AI automatically generates hyper-relevant, location-based keywords for an investigator’s search. If an analyst is looking into a specific neighborhood, the AI will suggest relevant landmarks, tourist attractions, schools, government buildings, and businesses to monitor. This instantly converts manual, time-consuming research into an automated process, significantly increasing the volume and relevance of the data collected.

Geo-Based OSINT 2.0

Geo-based search combined with AI keyword generation is taking OSINT to the next level. Geofencing allows teams to draw virtual perimeters around physical sites, such as corporate offices, foreign meeting sites, or public gatherings, to monitor digital activity strictly within those areas. This means you don’t need to know what keywords or hashtags you are looking for; you only need to know where to look. This is incredibly valuable for real-time executive protection and monitoring civil unrest, as it surfaces visual intelligence and early warnings directly from the scene, cutting out irrelevant noise.

The Future of OSINT for Situational Awareness

The decline of the geotag is a victory for consumer privacy, but it isn’t the end of location-based intelligence. By leveraging AI-driven keywords and hyper-local geofencing, security teams can move beyond broad geographic searches. These smart tools alleviate research bottlenecks, allowing analysts to redirect their expertise away from exhaustive data hunting and toward the critical analysis needed to respond to threats before they escalate. The geotag may be fading, but our situational awareness remains sharper than ever.

Don’t let the intelligence gap compromise your situational awareness. Ready to move from tedious manual searches to immediate, actionable insights? Book your Echosec demo today and empower your team with the next generation of location-based insight.

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Navigating the Threat Landscape of the 2026 FIFA World Cup

In this blog, we break down emerging threat activity, protest movements, cyber risks, and operational challenges shaping the security environment for the 2026 FIFA World Cup.

Updated June 2026

Key Takeaways

As the 2026 FIFA World Cup progresses, Flashpoint analysts continue to monitor a dynamic threat environment spanning physical security, civil unrest, cyber threats, and geopolitical developments. While analysts have not identified any credible indications of an imminent attack targeting tournament venues or participants, several notable developments have emerged since our previous assessment.

2026 FIFA World Cup Security Challenges:

• Protest activity has expanded across host nations. In Mexico City, anti-World Cup demonstrators reportedly blocked access roads near Estadio Azteca and clashed with security forces during opening-event activities. Additional campaigns remain active across Canada, Mexico, and the United States, including anti-FIFA coalitions, labor actions, housing advocacy movements, and the growing “No ICE in the Cup” campaign.
• Iran-related tensions continue to shape the tournament environment. Recent matches involving Iran have generated demonstrations, pitch-invasion incidents, political messaging from supporters, and ongoing disputes surrounding travel restrictions, visa issues, and operational limitations affecting the Iranian team.
• Security concerns remain elevated around high-profile matches and surrounding fan activity. Analysts continue to monitor the potential for crowd-management incidents, stadium-perimeter disruptions, and clashes between rival supporter groups, particularly in and around fan zones, transit hubs, and other soft-target locations.
• Local operational disruptions are increasingly intersecting with tournament activity. Recent examples include hotel labor strikes in Philadelphia and other city-specific demonstrations that may affect transportation, hospitality operations, and visitor movement around host venues.
• Cybercriminal activity targeting fans remains persistent. Security researchers and law enforcement agencies continue to warn of thousands of fraudulent domains impersonating FIFA-related services, including fake ticketing portals, merchandise sites, streaming services, and employment opportunities designed to steal credentials and personal information.
• Analysts are also monitoring claims from politically motivated and state-aligned cyber actors seeking to associate themselves with World Cup-related threats. While some publicly promoted claims remain unverified, the tournament continues to present an attractive target for threat actors seeking visibility, disruption, or financial gain.
• Online sentiment remains largely positive and focused on the tournament atmosphere, but controversy continues around ticket prices, commercialization, geopolitical tensions, and fan-related incidents that have generated significant discussion across social media platforms.

Current Threat Assessment

The 2026 FIFA World Cup will be unlike any tournament before it.

Set to run starting next month from June 11th to July 19th across the United States, Canada, and Mexico, this will be the first World Cup co-hosted by three nations and expanded to 48 teams across 16 host cities. More than five million fans are expected to attend matches in person, with billions more engaging globally.

That scale introduces a different class of risk. The World Cup is a distributed, high-visibility global operation spanning stadiums, transit systems, hotels, fan festivals, and digital infrastructure.

At the time of writing, Flashpoint analysts have not identified any specific, credible threats targeting the tournament. However, recent extremist propaganda and geopolitical tensions continue to reinforce the need for heightened vigilance across host nations.

A Converging Threat Environment

The risks surrounding the 2026 World Cup intersect across multiple domains.

Physical security, cyber activity, geopolitical tensions, and social movements all operate against the same infrastructure and audiences. Activity in one area can quickly affect another.

Flashpoint assesses that the most persistent risks across all host nations include:

• Crimes of opportunity targeting visitors unfamiliar with local environments
• Lone-actor attacks, including those driven by extremist ideologies
• Overcrowding, fan conflicts, and unmanaged gatherings
  

These risks are amplified by the tournament’s scale and geographic distribution.

Civil Unrest and Protest Activity

World Cup tournaments routinely become platforms for protest.

For 2026, multiple movements are already organizing around the event:

• “Boycott USA 2026” campaigns and groups like CODEPINK are calling for relocation of matches
• The “50501 Movement” has signaled intent to leverage the tournament’s visibility for national demonstrations
• Coalitions of civil society organizations have raised concerns around immigration enforcement, surveillance, and civil rights
  

Recent organizing activity has expanded beyond traditional anti-FIFA campaigns. Civil rights organizations, labor groups, anti-ICE coalitions, and community organizations in multiple host cities have announced or promoted demonstrations tied to immigration enforcement, displacement concerns, labor issues, and the broader social impacts of the tournament.

In the United States, Flashpoint analysts assess with high confidence that protests will occur across all host cities, with messaging tied to immigration policy, labor issues, and geopolitical tensions.

In Canada and Mexico, protests tied to environmental concerns, infrastructure impact, and global conflicts are also expected.

While many campaigns began as awareness and advocacy efforts, several have evolved into organized demonstrations, community events, and direct actions tied to tournament activities. Analysts continue to monitor anti-FIFA coalitions in Canada, anti-World Cup organizing efforts in Mexico, and the growing “No ICE in the Cup” campaign across US host cities. The scale of the event means even localized demonstrations can escalate quickly, especially around stadiums, transit hubs, fan zones, and other high-traffic gathering areas.

Physical Security and Crowd Risk

No specific terrorist plots have been identified. But that does not reduce the risk.

Large gatherings remain attractive targets for:

• Lone actors seeking high visibility
• Opportunistic criminals
• Disruptive fan groups
  

Online chatter continues to reference potential attacks, including decentralized calls for violence from extremist-linked media outlets. At the same time, analysts are monitoring a broader threat environment shaped by geopolitical tensions, extremist propaganda, and lone-actor attack risks that frequently accompany large and globally visible events.

Beyond intentional threats, crowd dynamics pose a persistent risk. Past sporting events have shown how quickly panic, overcrowding, or pyrotechnics can trigger dangerous conditions, including crowd crush incidents.

Fan culture adds another layer. Organized groups such as Ultras and hooligan firms increasingly operate with coordination, using encrypted messaging, reconnaissance (“spotting”), and off-site meetups to avoid security controls.

Security concerns extend beyond traditional supporter culture. Some organized fan groups have evolved increasingly sophisticated tactics, including coordinated reconnaissance, plain-clothes scouting, encrypted communications, and deliberate efforts to move confrontations away from stadium security zones and into “soft zones” like bars, transit hubs, and other gathering locations.

Recent demonstrations in Mexico City highlighted the potential for stadium-perimeter disruptions and confrontations with security personnel during major tournament events. While these incidents were protest-related rather than terrorism-related, they underscore how quickly localized tensions can create operational and crowd-management challenges.

Geopolitical Tensions and High-Risk Matches

Geopolitics will shape the security environment throughout the tournament.

The ongoing tensions involving the United States, Israel, and Iran are expected to influence both protest activity and threat perceptions. Iran’s participation—particularly matches held in U.S. cities—has already sparked debate, travel concerns, and increased security planning.

Discussions surrounding Iranian participation continue to generate significant attention online and offline. Analysts are monitoring protest activity related to symbol restrictions, travel policies, and broader geopolitical tensions involving Iran, Israel, and the United States. These issues are expected to influence both public demonstrations and security planning throughout the tournament.

The issue extends beyond match security. Visa policies, travel restrictions, diaspora activism, and ongoing debate surrounding Iranian participation have already generated significant discussion among supporters, advocacy groups, and government stakeholders.

Certain matches carry elevated risk due to:

• Historical rivalries
• National identity tensions
• Known fan group activity
  

These matches require heightened monitoring not just inside stadiums, but across surrounding areas where supporters gather.

The Expanding Cyber Threat Surface

The World Cup is also a large-scale digital event.

Even without identified active campaigns, Flashpoint analysts expect the tournament to function as a stress test for global infrastructure.

Key cyber risks include:

• Ticketing fraud: Fake domains impersonating official FIFA platforms
• Phishing and social engineering: Targeting fans, vendors, and staff
• Ransomware and DDoS attacks: Disrupting transit systems, stadium operations, and hospitality networks
• Infrastructure targeting: Exploiting vulnerabilities in public-facing systems
  

Researchers have already identified thousands of fraudulent domains impersonating FIFA-related services, alongside phishing campaigns designed to harvest credentials, hijack accounts, and resell legitimate tickets purchased by victims.

Threat actors are also expected to monetize the event through:

• AI-enhanced fraud campaigns leveraging convincing fake websites, social media content, and communications
• Fraudulent housing and rental listings
• Rideshare and transportation scams
• Sports betting manipulation and extortion
  

Analysts are also monitoring claims by state-aligned hacktivist groups seeking to associate themselves with World Cup-related threats. While some publicly promoted claims remain uncorroborated, the broader trend highlights ongoing interest from politically motivated cyber actors in leveraging the tournament’s visibility to amplify messaging, generate attention, or target supporting infrastructure.

Even minor disruptions to digital infrastructure can have cascading effects on physical operations that cause delayed transportation, overwhelming venues, or other safety concerns.

The reality of large-scale global events in 2026, writes Flashpoint’s intelligence operations expert Ian Gray, is that “the attack surface is no longer just the venue, it’s the infrastructure surrounding the whole event.” Read his full in-depth analysis on TechRadar here.

Operational Security Gaps

Some of the most overlooked risks are also the simplest.

Attendees, staff, and media frequently post images of credentials like press passes, security badges, and access tokens on public social media. These images can be used to replicate credentials and bypass controls.

Similarly, fans often attempt to:

• Access team hotels
• Enter restricted areas
• Interact directly with players

These behaviors create additional pressure on venue and hospitality security teams, particularly in high-profile locations.

Beyond the Stadium: Distributed Risk

The World Cup extends far beyond match venues. Security teams must account for:

• Team base camps and training facilities
• Fan festivals and unofficial gatherings
• Hotels, tourist destinations, and transit systems
• Cross-border travel between host nations
• Increased human trafficking and exploitation risks associated with large-scale international travel and temporary workforces
• Housing, labor, and community tensions in host cities experiencing increased visitor traffic

Unauthorized fan festivals and spontaneous gatherings remain a persistent concern, often drawing large crowds without coordinated security planning.

At the same time, environmental factors like extreme heat, severe storms, wildfire risk, and transportation disruptions may affect operations and place additional strain on local infrastructure.

Getting Ready for the Tournament

The absence of identified threats should not be misinterpreted as low risk.

Events of this scale require continuous monitoring across physical, cyber, and social domains. Threat indicators often emerge early in:

• Online forums and messaging platforms
• Local protest planning
• Fraudulent domain registrations
• Changes in adversary behavior
• Emerging protest campaigns and social mobilization efforts

Effective preparation depends on:

• Broad, multilingual monitoring across open and closed sources
• Correlation between physical and cyber indicators
• Visibility into both high-profile targets and “soft zones”
• Close coordination between public and private sector partners

Flashpoint recommends monitoring key terms such as “World Cup,” “FIFA,” “Fan Festival,” and related hashtags across intelligence platforms to maintain situational awareness.

Maintaining visibility into both online sentiment and real-world activity remains critical, particularly as narratives surrounding immigration enforcement, geopolitical tensions, event costs, and tournament operations continue to evolve.

Preparing for the Whistle

Building a robust threat monitoring architecture is a continuous process. Host cities and law enforcement often use smaller-scale international competitions as test runs to prepare for the scale and complexity of events like the FIFA World Cup.

By leveraging Flashpoint’s advanced search capabilities—including broad keyword coverage, wildcard operators, and visibility into deep and dark web communities—organizations can maintain awareness of emerging risks tied to large-scale events. From stadium infrastructure to digital ticketing platforms, actionable intelligence supports more informed, timely decisions.

To see how Flashpoint enables this level of visibility and monitoring in practice, request a demo.

Request a demo today.

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Inside the 2026 Cyber Threat Landscape: Data-Driven Security Priorities

In Flashpoint’s recent webinar, we examine the defining shifts shaping the 2026 threat landscape, from AI-driven attack automation to the growing role of identity in initial access. We analyze how infostealers, vulnerabilities, and ransomware activity are evolving, and where security teams should focus now.

In 2026, the threat landscape operates as a single, connected system. Identity, malware, and infrastructure are now part of the same attack chain, executed at a speed that compresses the time between access and impact.

What once required multiple stages and specialized tooling is now streamlined and automated.

Flashpoint recently hosted an on-demand webinar, “Inside the 2026 Cyber Threat Landscape: Data-Driven Security Priorities,” where our intelligence team broke down the trends driving this shift. Drawing from primary source intelligence across forums, marketplaces, and closed communities, the session examined how modern attack chains are forming and evolving, as well as where defenders still have opportunities to intervene.

Here are the key takeaways you need to know to prioritize threats and protect your organization.

AI Is Being Operationalized Across the Attack Lifecycle

Artificial intelligence is now embedded across multiple stages of attacker workflows.

Flashpoint tracked more than 1.5 billion mentions of AI in illicit communities in 2025, with activity accelerating sharply toward the end of the year. These discussions center on how AI can be applied to real operations, including phishing, malware development, and fraud.

As Ian Gray, Vice President of Intelligence at Flashpoint, noted during the session, “Adversaries are extremely adept, and they’re constantly looking at how they can use the newest state-of-the-art tools—whether that’s commercial models or their own implementations—and how they can jailbreak them or adapt them to their workflows.”

One of the most notable developments is the use of agentic AI systems to automate tasks that were previously manual. These systems are being used to:

• Test stolen credentials across VPNs, SaaS platforms, and cloud environments
• Rotate infrastructure during active operations
• Generate and refine attack inputs based on previous outcomes

Alongside this, threat actors are actively exploring ways to bypass safeguards in commercial AI tools, including:

• Jailbreaking model restrictions
• Embedding hidden instructions through prompt injection
• Manipulating AI-powered features within enterprise applications

This activity reflects a sustained effort to integrate AI directly into attack execution rather than treating it as a standalone capability.

Identity Is Driving Initial Access

The fundamental mechanics of cybercrime have shifted from breaking in to logging in, as attackers leverage stolen session cookies to behave like legitimate users.

As Gray explained, “Threat actors are finding a variety of ways to get into enterprise networks, and typically it’s through the human element. While humans can be trained or educated, it’s not something that can be patched in the traditional sense.”

This dynamic is already visible at scale.

Flashpoint observed 11.1 million infected devices and 3.3 billion stolen credentials in 2025. These credentials are extracted through infostealers and circulated across marketplaces, enabling direct access into enterprise environments.

In many cases, attackers are using:

• Session cookies and tokens to bypass authentication flows
• Browser fingerprints and system metadata to replicate legitimate user behavior
• Valid credentials to access SaaS platforms, VPNs, and internal systems

Once access is established, activity often blends into normal user behavior, making detection more difficult. Compromised identities are also reused across multiple services, expanding the scope of potential exposure.

This pattern continues to appear in intrusion activity tied to SaaS platforms and third-party integrations, where access to one system can provide visibility into multiple environments.

Infostealers Are Enabling Scalable Access

Infostealers remain a primary driver of credential exposure.

Logs containing credentials, cookies, and system data are continuously harvested and made available through criminal marketplaces and subscription-based services. These logs are used directly or integrated into automated workflows that test and validate access at scale.

Gray pointed to how this plays out in practice: “Infostealers have really commoditized access. They harvest credentials, identify which ones are useful, and then test them at scale across VPNs, SaaS platforms, and cloud environments.”

The ecosystem continues to shift as law enforcement activity disrupts established players and new variants gain traction. Families such as Vidar, Lumma, and others maintain a strong presence due to accessibility and ongoing development.

In parallel, credential harvesting is feeding downstream activity, including:

• Account takeover
• Fraud operations
• Data exfiltration and extortion

This linkage between initial access and follow-on activity is consistent across multiple reporting streams.

Vulnerability Exploitation Is Moving Faster

Vulnerability volume continues to increase alongside exploitation speed.

Flashpoint recorded more than 44,000 disclosed vulnerabilities in 2025, with over 14,000 tied to publicly available exploits. In several cases, exploitation activity followed disclosure within a day.

As Gray put it, “With vulnerabilities, it can feel like you’re trying to boil the ocean. There’s such a high volume of disclosures, but in reality, there’s a smaller set—those that are remotely exploitable, have proof-of-concept code, and are being actively used—that you need to focus on.”

Attacker focus is concentrated in areas that provide broad access or downstream impact, including:

• Software supply chains and CI/CD environments
• Open-source dependencies
• Widely used enterprise platforms

Given the volume of disclosures, prioritization remains critical. Vulnerabilities that are remotely exploitable and paired with public exploit code present immediate risk, particularly when active discussion or exploitation is observed.

Ransomware Activity Continues to Shift

Ransomware activity increased by 53%, with continued changes in how operations are carried out.

Gray framed the shift this way: “Why even bother to develop ransomware? That takes time, resources, and overhead—when you can gain access through a compromised account or third-party platform and immediately move to extortion.”

In addition to traditional ransomware deployment, there is sustained activity centered on:

• Data exfiltration followed by extortion
• Use of compromised credentials for direct access
• Targeting of third-party providers and SaaS platforms

Intrusions tied to help desks, identity workflows, and federated applications continue to appear in reporting, often involving social engineering or unauthorized access provisioning.

There is also ongoing activity related to insider recruitment, with threat actors seeking individuals who can provide direct access or privileged information.

Industries with higher operational dependencies, including manufacturing, technology, and healthcare, continue to be targeted due to the potential impact of disruption.

Translating Intelligence Into Action

The trends shaping 2026 are grounded in how attackers are currently operating across multiple domains.

As Gray emphasized, “You have to take into account vulnerabilities, exposures, infostealers, and identity compromise all at the same time. These aren’t separate problems anymore—they’re all part of the same attack chain.”

Security teams should focus on:

• Identifying exposures with a high likelihood of exploitation
• Monitoring for compromised credentials tied to organizational domains
• Reviewing identity access and third-party integrations
• Prioritizing vulnerabilities with active exploit availability
• Tracking attacker activity across forums, marketplaces, and communication channels

These actions align with observed attacker behavior and provide a clearer path to prioritization.

Watch the Full Webinar and Explore the Data

The trends shaping 2026 are grounded in how attackers are already operating.

Flashpoint’s full webinar provides a deeper look at the data, along with practical guidance on how to translate intelligence into action.

Watch the on-demand session to see the full breakdown of these trends, or download the 2026 Global Threat Intelligence Report to explore the underlying data and analysis in more detail.

Request a demo today.

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Flashpoint MCP Server: Operationalizing Cyber Threat Data for Agentic AI Security Workflows

In this post, we outline how cyber threat intelligence is evolving to support agentic AI-driven security operations, why MCP is emerging as a foundational standard, and how Flashpoint is operationalizing data for this new model.

Security teams are under more pressure than ever to move faster, see more, and act with confidence.

At the same time, the way cybersecurity investigations happen is evolving. The “human-in-the-loop” model is expanding: analysts increasingly direct AI agents that gather context, correlate signals across sources, and handle repetitive triage.

While AI is rapidly becoming a staple of modern security operations, a significant gap remains: most intelligence sources were originally designed for human consumption, not AI agents. Historically, threat intelligence platforms were built for analysts to log in and piece together disparate insights. While that model remains the gold standard for deep research, it can become a bottleneck in a high-velocity, agent-led workflow where AI assistants and automation pipelines are the primary investigators.

At Flashpoint, our Ignite threat intelligence platform was built to support deep investigative workflows, enabling analysts to search and connect intelligence across primary-source datasets and build a complete picture of emerging threats. That foundation remains critical.

But as workflows evolve, customers are increasingly looking to extend that same intelligence beyond the platform—into AI assistants, automation pipelines, and other environments where work is actively happening.

That raises an important question: How do you make high-value intelligence as usable for an AI agent as it is for a human analyst?

Today, we are outlining our approach to building the Flashpoint Model Context Protocol (MCP) Server, a strategic initiative that makes Flashpoint’s best-in-class intelligence accessible not only via our award-winning platform but also natively “AI-callable” within the agentic workflows of today and tomorrow.

What Is an MCP Server and Why Does It Matter in Cyber Threat Intelligence?

Model Context Protocol (MCP) is the standard for connecting AI systems to external data sources and tools. 

In practical terms, an MCP server provides a structured way for AI systems, like agents, assistants, copilots, and automation frameworks, to access and interact with data in real time.

For cyber threat intelligence, this represents a fundamental shift in how teams operate:

• Faster investigations: AI agents can query and correlate data across disparate datasets in seconds.
• Comprehensive coverage: By searching across all primary sources in parallel, teams eliminate the risk of missing critical intelligence. 
• More seamless workflows: Analysts can stay within their agentic workflow without constant context switching.
• Reduced integration overhead: Less need for custom engineering to connect intelligence into new environments.

Flashpoint MCP Server: A Foundation for AI-Native Threat Intelligence

Flashpoint has always differentiated itself on the quality and depth of our data, sourced directly from where threats emerge. Our goal is to ensure this intelligence is available wherever your analysts are working.

Currently, teams experimenting with AI assistants face significant friction: copying and pasting, relying on third-party bridges, or maintaining custom integrations.

We are building the Flashpoint MCP Server as a foundational access layer, the architectural connector that will power both external integrations and future AI experiences within the Flashpoint platform.

With this new layer, teams can:

• Query intelligence in one workflow: Access intelligence reports, ransomware, vulnerabilities, communities, and Deep Dark Web, and technical indicators in a single research task rather than hopping tool-to-tool.
• Ground AI agents in truth: Provide a direct, authenticated bridge to real-time, verified Flashpoint intelligence, ensuring AI responses are based on evidence rather than static training data or hallucinations.
• Scale expert analysis: Use guided prompts and workflow templates to teach the AI exactly how to use our tools to conduct expert-level investigations across our datasets.

The threat intelligence industry is adopting MCP as the standard for how AI systems connect to data.

We’re building the Flashpoint MCP Server to ensure our intelligence is a foundational component of that ecosystem and usable wherever AI-driven workflows occur.

What to Expect from Flashpoint MCP Server

The initial release of the Flashpoint MCP Server in Spring 2026 is intentionally read-only and query-focused. This creates the production-grade foundation required to bring intelligence into the workflows customers are already building. It aligns with customer guidance about using agentic AI to solve the most pressing challenges they face today.

What Comes Next

Later this year, we will move from information retrieval to Action-Oriented Intelligence. This expansion will allow users not only to access data but also to act on it directly within their AI-driven workflows. As this ecosystem evolves, we plan to deliver:

• Natural Language Orchestration: We are empowering analysts to interact with our data more intuitively. Through the MCP server, complex actions such as updating an investigation or identifying new threat sources are handled via natural-language orchestration. This ensures that the speed of an investigation is limited only by an analyst’s questions, not their mastery of a specific query syntax.
• Flashpoint-Native Agents and Skills: We are developing specialized Flashpoint Agents and “skills” built on top of this server. These will be purpose-built to address specific workflows, such as ransomware monitoring or vulnerability triage, allowing teams to deploy out-of-the-box expertise without building their own agentic logic
• Fusion of External and Internal Data: A critical advantage of the MCP framework is the ability to combine Flashpoint’s external threat intelligence with a customer’s internal environment data (SIEM, Cloud, IAM, Endpoint, etc.). This allows an agent to correlate global threat signals with your specific footprint to provide instant, individualized risk context. 
• Embedded AI within Flashpoint Ignite: This same MCP infrastructure will serve as the shared engine for new, embedded AI experiences within Flashpoint Ignite. This ensures that the same natural-language power and automated data correlation fueling external agents are also natively available within our platform UI, creating a seamless investigative experience regardless of where an analyst chooses to work.

Built and Validated in Real Workflows

We believe in the power of this new architecture because we are already using it. The MCP Server is currently embedded in our own Flashpoint Intelligence Team’s workflow, helping our analysts research and respond to complex client RFIs. 

By applying this capability to our own high-stakes research first, we ensure that what we bring to market is grounded in real investigative needs, not just technical potential. 

Operationalizing the Best Data

The future of security operations won’t be defined solely by who has access to the most data or even the most AI agents; it will be defined by who can operationalize the best data directly within the workflows where decisions are made.

The Flashpoint MCP Server is our strategic commitment to that future—making the world’s best intelligence natively accessible, usable, and aligned with the way modern security teams work.

The Flashpoint MCP Server is currently in active development, with customer availability planned for late Spring 2026. 

Subscribe to the Flashpoint blog for more updates on Flashpoint MCP Server and the latest insights from the front lines of threat intelligence.  

Frequently Asked Questions

What is the Flashpoint MCP Server? 

The Flashpoint MCP Server enables Flashpoint’s threat intelligence to be directly callable by AI agents. It implements the Model Context Protocol (MCP), an open standard for connecting AI systems to external data, so any MCP-compatible agent, including Claude, Gemini, and Cursor, can query our datasets without bespoke API integration work.

Who is the MCP Server designed for?

The MCP Server is designed for technical, forward-leaning security teams and AI-native organizations. This includes SOC analysts, CTI practitioners, and security engineers who are already building or experimenting with AI agent workflows using tools like Gemini, Claude Code, or custom LLM-based assistants.

Which Flashpoint datasets are accessible via MCP?

The initial rollout (Spring 2026) provides access to Flashpoint’s core intelligence collections, including:

• Intelligence Reports
• Communities (Online forums, messaging platforms, closed digital communities)
• Technical Indicators (IOCs)
• Vulnerability Intelligence (CVEs)
• Ransomware
• Compromised Credentials and Infected Hosts
• Strategic Entity Data

How does this differ from Flashpoint’s standard APIs?

While our standard APIs are designed for direct programmatic consumption, the MCP Server is optimized specifically for AI agents. It exposes intelligence as composable tools and guided prompts that AI agents can understand and use to perform complex, multi-step research tasks. 

How does this differ from the Flashpoint Ignite platform?

The Flashpoint MCP Server is not a replacement for Flashpoint’s award-winning Ignite platform; rather, it is a complementary access layer designed for a different type of user and workflow. While Ignite is a destination for deep research, the MCP server provides the infrastructure that enables that same intelligence to live in AI-native environments.

To learn more about Flashpoint’s MCP Server, schedule a demo today.

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2026 Gartner® Magic Quadrant for Cyber Threat Intelligence: Key Takeaways for Security Leaders

We are proud to share that Flashpoint has been named a Challenger in the inaugural 2026 Gartner® Magic Quadrant for Cyber Threat Intelligence Technologies. 

“We see this recognition as a testament to Flashpoint’s ability to execute at the highest levels for the world’s most discerning threat intelligence customers, with our unique combination of primary source collection and human analysis at the core,” — Josh Lefkowitz, CEO at Flashpoint.

The Gartner Magic Quadrant provides organizations with a wide-angle view of vendors in the cyber threat intelligence market. By applying a graphical treatment and a uniform set of evaluation criteria, the Magic Quadrant helps organizations assess how well technology providers are executing their stated visions and performing against Gartner’s market view. Vendors are evaluated based on their Ability to Execute and Completeness of Vision:

• Ability to Execute reflects the Gartner assessment of the vendor’s product and/or service, overall viability, sales execution and pricing, market responsiveness and record, marketing execution, customer experience, as well as operations.
• Completeness of Vision comprises the Gartner view of the vendor’s overall market understanding, marketing strategy, sales strategy, offering (product) strategy, business model, vertical/industry strategy, innovation, and geographic strategy.

“We believe, and our customers consistently validate, that the future of threat intelligence lies at the critical intersection of intelligence depth and application,” says Lefkowitz. “That’s why Flashpoint pairs unmatched access to primary-source environments with the ability to operationalize that intelligence across security workflows, enabling organizations to make faster, more informed decisions.”

A complimentary copy of the Gartner® Magic Quadrant for Cyber Threat Intelligence Technologies is available to download here.

Market Dynamics and Growth of the Threat Intelligence Market

The threat intelligence market has expanded in both scope and strategic importance as organizations contend with a broader and more complex threat environment. What was once a supporting function within security operations is now expected to inform decisions across vulnerability management, fraud prevention, and enterprise risk. This shift has raised the bar for how intelligence is collected, analyzed, and applied.

Gartner describes this evolution as a move toward unified cyber risk intelligence (UCRI) — an approach that brings together diverse internal and external data sources with advanced analytical capabilities to improve decision-making. As noted in The Evolution of Threat Intelligence Is Unified Cyber Risk Intelligence, “the future of threat intelligence is unified cyber risk intelligence (UCRI)… defined by the convergence of multisignal collection and advanced analytical capabilities.” In our opinion, this model reflects the reality that no single source provides sufficient visibility, and that intelligence must be corroborated across environments to be actionable. 

At the same time, the scale of available data continues to increase, introducing new challenges around prioritization and context. Gartner notes that organizations “receive vast amounts of threat data, and filtering out false positives, redundant information and irrelevant alerts to extract actionable intelligence remains a significant challenge. This “noise” can overwhelm security teams and lead to important threats being missed.” This is where AI plays a growing role. Techniques such as machine learning and natural language processing are increasingly used to correlate signals, identify patterns, and surface relevant risks faster. As intelligence becomes more integrated across the enterprise, the ability to combine multisource collection with AI-driven analysis is shaping how organizations evaluate platforms and build modern threat intelligence programs.

How Security Teams Are Evaluating Threat Intelligence

From Flashpoint’s experience working with the most discerning security and intelligence teams, the value of a threat intelligence platform is measured in how it performs in practice — how quickly it surfaces relevant activity, how much context it provides, and how easily it supports decision-making across workflows.

We see three areas consistently shape how intelligence is evaluated, supported by a combination of human expertise and AI-driven analysis:

• Access to high-signal environments: Intelligence is most useful when it reflects activity at its source. Access to closed forums, encrypted messaging platforms, and illicit marketplaces provides the context needed to understand how threats develop and move.
• Context that supports prioritization: Vulnerability and threat data require context to be actionable. Understanding how activity is discussed and operationalized in real environments allows teams to focus on what requires attention.
• Integration into operational workflows: Intelligence must fit into the systems and processes teams already rely on. Integration across SIEM, SOAR, and internal workflows allows intelligence to be applied consistently at scale.

These areas are closely tied to how Flashpoint has built its platform and how it supports organizations operating in complex threat environments.

Where Intelligence Comes From Matters

A large part of how intelligence performs in practice comes back to the source of the data itself.

We believe, and our customers continue to validate, that Flashpoint’s approach is centered on primary-source collection. That means accessing environments where threat activity is actively discussed, coordinated, and developed, including closed forums, encrypted messaging platforms, and illicit marketplaces. These environments require sustained access and ongoing validation, but they provide a level of visibility that is difficult to achieve through surface-level collection alone.

From our experience, working from these sources changes how intelligence is used. Activity can be observed earlier and understood with more context, with discussions, relationships, and intent preserved.

In practice, this allows teams to:

• Identify emerging activity before it becomes widely visible
• Maintain context across conversations, actors, and environments
• Reduce time spent investigating low-value or unverified signals

Intelligence Has to Fit Into How Teams Actually Operate

Collection alone doesn’t determine whether intelligence is useful. We believe it also has to be delivered in a way that aligns with how teams work.

In our experience, most security teams already have established workflows tied to SIEMs, SOAR platforms, and internal processes. Intelligence that integrates into those workflows can be applied consistently across investigation and response.

In practice, we see this support:

• Delivery of intelligence directly into existing systems
• Consistent application across automated and analyst-driven workflows
• Reduced friction between intelligence, investigation, and response

Over time, this consistency allows teams to build repeatable processes around intelligence rather than treating it as a separate function.

Context Drives Prioritization

The same dynamics apply to vulnerability intelligence.

From our experience, understanding which vulnerabilities exist is only one part of the problem. Determining which ones require attention in a given environment depends on context — how those vulnerabilities are being discussed, shared, or used in active threat activity.

We have seen first-hand that when vulnerability data is connected to real-world activity, teams can:

• Prioritize remediation based on active threat relevance
• Align vulnerability management with observed adversary behavior
• Reduce reliance on static scoring as the sole decision driver

Applying This in Practice

For organizations evaluating providers, challenge intelligence sources, challenge collection agility, challenge exploit prioritization and above all ask yourself is this a partner with a long-term track record of navigating the world’s most complex threat environments?

To see how Flashpoint, the world’s largest private provider of threat intelligence can help you make better decisions, faster and with confidence, schedule a demo.

Gartner Disclaimer

Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose. 

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Flashpoint.

Gartner, Magic Quadrant for Cyber Threat Intelligence Technologies, Jonathan Nunez, Carlos De Sola Caraballo, Jaime Anderson, May 4, 2026.

Gartner, The Evolution of Threat Intelligence Is Unified Cyber Risk Intelligence, By Jonathan Nunez, 15 September 2025.

Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.

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How to Build and Operationalize Priority Intelligence Requirements

In this post, we break down how to define, structure, and operationalize Priority Intelligence Requirements (PIRs) to improve focus, reduce noise, and drive more effective intelligence outcomes, with a companion starter kit to help apply these concepts in practice.

Security teams are inundated with data. Alerts, feeds, reports, and signals continue to grow in volume, but without clear direction, much of that information fails to translate into meaningful action.

Flashpoint recently hosted a webinar, “How to Build and Operationalize Priority Intelligence Requirements,” where our intelligence team walked through how organizations can bring structure to their intelligence programs. The session focused on how to define Priority Intelligence Requirements (PIRs), align them to business needs, and operationalize them across workflows. If you missed it, you can catch the on-demand recording here.

In this blog, we’ll recap the key takeaways from the webinar that you need to know to build, structure, and operationalize Priority Intelligence Requirements within your organization.

Priority Intelligence Requirements Create Focus

Priority Intelligence Requirements (PIRs) define what matters most to an organization’s intelligence function.

They serve as a framework for identifying the threats, risks, and questions that intelligence teams are responsible for answering. Without that structure, teams often default to reactive workflows—chasing alerts and producing reporting without clear alignment to business priorities.

PIRs establish that alignment by grounding intelligence work in specific, decision-driven questions.

These questions are typically tied to areas such as:

• Threat actor activity targeting the organization or its sector
• Exposure of sensitive data, credentials, or infrastructure
• Risks tied to third-party vendors or supply chain dependencies
• Emerging trends that may impact operations or security posture

When defined correctly, PIRs act as a filter that helps teams determine what to collect, analyze, and escalate.

Effective PIRs Start With the Business

One of the most common challenges highlighted in the webinar is that PIRs are often defined in isolation.

When intelligence requirements are not tied to business priorities, they tend to drift toward generic threat monitoring. This leads to reporting that is technically accurate, but operationally disconnected.

Effective PIR development starts with first understanding:

• What decisions need to be made
• Who is responsible for making them
• What information is required to support those decisions

This requires direct engagement with stakeholders across security, risk, and business teams. In practice, that often includes leadership, legal, fraud, and operational teams.

The goal is to translate business concerns into intelligence questions that can be consistently answered over time.

Structuring PIRs for Actionability

Clear structure is essential to making PIRs usable.

Well-defined PIRs are specific enough to guide collection and analysis, but flexible enough to evolve as threats change. They are typically framed as direct questions that intelligence teams can answer with available data.

Examples of structured PIRs include:

• Are threat actors actively targeting our organization or industry?
• Has our data appeared in criminal marketplaces or forums?
• Are our third-party vendors experiencing security incidents that could impact us?

This approach ensures that intelligence outputs remain focused on answering defined questions rather than producing general reporting.

It also enables consistency across teams, making it easier to track trends and measure changes over time.

Operationalizing PIRs Across Workflows

Defining PIRs is only the starting point. Their value comes from how they are integrated into day-to-day operations.

In the webinar, Flashpoint emphasized the importance of embedding PIRs across the intelligence lifecycle, including:

• Collection: Prioritizing sources and datasets that align with defined requirements
• Analysis: Structuring outputs around PIR-driven questions
• Dissemination: Delivering intelligence to the stakeholders tied to each requirement
• Feedback: Continuously refining PIRs based on evolving needs

This integration ensures that intelligence efforts remain consistent and aligned, even as threat conditions change.

It also reduces duplication of effort and helps teams avoid producing intelligence that does not support decision-making.

Measuring the Impact of Intelligence

PIRs provide a foundation for evaluating whether intelligence efforts are effective.

Without defined requirements, it is difficult to determine whether outputs are relevant or useful. PIRs create a benchmark against which teams can assess:

• Whether key questions are being answered
• Whether intelligence is reaching the right stakeholders
• Whether outputs are informing real decisions

This shifts intelligence from a reporting function to a decision-support capability.

Over time, this approach helps organizations refine both their requirements and their workflows, improving efficiency and impact.

Dive Deeper | Watch the Full Webinar

Building and operationalizing Priority Intelligence Requirements is a foundational step toward a more focused and effective intelligence program.

Flashpoint’s on-demand webinar walks through this process in detail, including practical examples and guidance for implementation.

For teams looking to move from theory to implementation, the Priority Intelligence Requirements (PIR) Starter Kit provides a practical extension of this approach. The resource includes a structured framework for defining requirements, a catalog of adaptable PIR examples across key intelligence drivers, and a template to support documentation and governance.

Watch the full session and download the starter kit to begin building requirements that directly support decision-making and risk reduction.

Begin your free trial today.