Ransomware operators are scaling their attacks, and the barriers to entry continue to fall. In the first half of 2026, Flashpoint identified 6,256 ransomware attacks across industries, representing a 45% increase between 2025 and 2026, as Ransomware-as-a-Service (RaaS) operations expanded and threat actors increasingly leveraged AI, stolen credentials, and vulnerability exploits to accelerate their campaigns.

The impact is widespread. Manufacturing accounted for 18% of observed attacks, followed by business services and consulting (13%) and healthcare (9%). Meanwhile, prolific ransomware groups such as Qilin and Akira continue to demonstrate the scale at which these operations can function.

Understanding how ransomware attacks develop, and where they can be interrupted, is critical for defenders.

Introducing Ransomware in the Age of AI: A Survival Guide for Defenders

Flashpoint’s new guide, Ransomware in the Age of AI: A Survival Guide for Defenders, provides cyber threat intelligence professionals, threat hunters, and security leaders with a practical look at the modern ransomware attack lifecycle, from initial reconnaissance and access to incident response and recovery.

Drawing on Flashpoint’s primary-source intelligence and analysis of evolving threat actor tactics, the guide explores how organizations can identify opportunities to disrupt attacks before they escalate, strengthen incident response, and reduce the risk of repeat compromise.

Access the guide to learn:

• How modern ransomware attacks unfold: Follow the attack lifecycle, from reconnaissance, phishing, and initial access through lateral movement, encryption, and ransom negotiations.
• Where defenders can intervene: Understand how compromised credential monitoring, vulnerability intelligence, and visibility into underground activity can help identify threats before attackers reach critical systems.
• How AI is reshaping ransomware operations: Explore how AI-enabled capabilities, commoditized tooling, and RaaS ecosystems are changing the economics and execution of ransomware attacks.
• How to strengthen response and recovery: Learn strategies for containing active incidents, restoring operations, improving cross-team coordination, and reducing exposure to repeat attacks.

Understanding the Modern Ransomware Attack Lifecycle

Ransomware attacks rarely begin with encryption. Long before systems are locked or ransom demands appear, threat actors may be gathering intelligence on potential targets, exploiting exposed vulnerabilities, or acquiring stolen credentials through underground marketplaces.

Flashpoint observed a 27% increase in infostealer operations in H1 2026 compared to H1 2025, underscoring the growing role of compromised identities in the ransomware ecosystem. Stolen credentials and session data can provide attackers with access to organizational environments, potentially allowing them to bypass traditional defenses and establish a foothold.

These initial access methods are increasingly interconnected with broader criminal operations. RaaS groups can leverage specialized tools and services throughout the attack chain, while AI-enabled capabilities offer additional opportunities to automate and accelerate certain activities.

This creates multiple opportunities for defenders to act. Intelligence about exposed credentials, emerging exploitation activity, and threat actor behavior can help security teams identify risks earlier and prioritize defensive action before an intrusion progresses.

The guide examines these opportunities across the ransomware lifecycle, outlining how proactive intelligence and coordinated response can help organizations minimize operational disruption and strengthen resilience.

Build a More Proactive Defense Against Ransomware

As ransomware operations continue to evolve, organizations need visibility into the threats targeting their environments and the intelligence to respond at every stage of an attack.

From identifying compromised credentials and monitoring emerging threats to containing incidents and preventing repeat attacks, a lifecycle-based approach helps security teams make more informed decisions before, during, and after a ransomware incident.

Get the Ransomware in the Age of AI: A Survival Guide for Defenders to explore the modern ransomware attack lifecycle and learn how Flashpoint’s threat intelligence can help your organization anticipate, disrupt, and recover from ransomware attacks.

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In the first half of 2026, Flashpoint tracked more than 22 million threat actor posts discussing, sharing, or advertising AI toolkits for criminal deployment. The figure reflects AI’s growing presence across the cybercriminal underground, where adversaries are using new capabilities to accelerate attacks and develop malicious tooling with fewer resources.

For enterprise defenders, these developments are adding pressure to threat intelligence programs already managing high alert volumes, limited analyst capacity, and expanding responsibilities.

During Flashpoint’s recent webinar, we examined the evolving threat landscape alongside findings from Flashpoint’s Global Threat Intelligence Report: 2026 Midyear Edition and new enterprise threat intelligence research.

Missed the live webinar? We’ve rounded up the key takeaways below, and the full session is now available to watch on demand.

AI Is Changing the Economics and Speed of Cybercrime

AI is helping threat actors develop capabilities and execute attacks faster, reducing the time and expertise required for activities that previously demanded greater resources.

Several developments illustrate the broader shift in cybercrime economics and attack velocity:

• Initial access costs have declined by approximately 69%, reflecting the continued commoditization of access to compromised environments.
• Attackers published 637 malicious package versions in just 22 minutes during a software supply chain compromise.
• Nearly one in five vulnerabilities disclosed during the first half of this year had public or functional exploit code available, narrowing the window for defenders to address exposed systems.

AI is primarily accelerating established techniques, particularly during the early stages of the attack chain, including reconnaissance, social engineering, vulnerability discovery, and exploitation.

For defenders, this creates an opportunity to identify and disrupt malicious activity during its preparation stages. However, it also raises expectations around how quickly intelligence teams can recognize emerging threats, prioritize relevant findings, and act before an attack progresses.

AI Is Changing How Cybercriminals Develop Tools and Share Knowledge

AI is also changing how threat actors acquire the skills and capabilities needed to carry out attacks, creating new challenges for intelligence collection.

Historically, underground communities enabled cybercriminals to collaborate, exchange expertise, and obtain specialized services. Increasingly, threat actors can use AI to troubleshoot code, develop malicious tooling, and learn unfamiliar techniques independently, reducing their reliance on public collaboration.

Reduced activity in underground communities does not necessarily mean cybercriminal activity is declining. While forums, encrypted messaging platforms, and other illicit communities remain important intelligence sources, collection strategies must account for changes in how and where adversaries develop and distribute their capabilities.

Threat Intelligence Teams Are Struggling to Keep Up with Growing Demands

As adversaries accelerate their operations, enterprise threat intelligence teams are contending with growing workloads and limited resources.

Independent research commissioned by Flashpoint surveying threat intelligence budget owners and influencers at large North American enterprises identified several leading operational challenges:

• 65% cited alert noise and false positives.
• 55% identified analyst bandwidth and effectiveness.
• 50% pointed to the evolving threat landscape.
• 50% cited tool integration and interoperability challenges.

Note: Respondents could select up to three challenges.

High alert volumes, disconnected systems, and manual investigations consume analyst time that could otherwise be spent addressing emerging threats.

As one healthcare threat intelligence leader explained:

“Good analysts take time to develop and train, and we can’t hire our way out of that problem.”

These challenges are prompting organizations to examine how they can improve existing workflows, reduce repetitive investigations, and make better use of analyst expertise.

Threat Intelligence Budgets Are Growing, with AI Threats Leading Investment Priorities

Despite operational pressures, organizations are continuing to invest in threat intelligence.

Flashpoint’s research found that 50% of respondents expect their threat intelligence budgets to increase over the next 12 months, including 35% anticipating increases of at least 10%. Another 40% expect budgets to remain essentially flat, while 0% anticipate a decrease.

AI-related threats emerged as the leading priority for expanded intelligence coverage, particularly:

• Deepfakes and synthetic media, including their use in impersonation, fraud, and social engineering.
• AI-accelerated vulnerability exploitation, as adversaries identify and exploit weaknesses more quickly.
• Emerging AI-enabled attack vectors, including changes in threat actor tactics, techniques, and procedures.

Organizations are also investing in additional intelligence feeds, expanded security use cases, and further development of their intelligence programs.

These priorities reinforce the importance of translating AI-related threats into specific intelligence requirements aligned with organizational risk.

Agentic AI Adoption Is Underway, but Trust and Measurable Value Remain Essential

Alongside investments in AI-related threat coverage, organizations are exploring how agentic AI can improve their own intelligence operations.

Flashpoint’s research found that:

• 25% are already using agentic AI in production.
• 20% are piloting agentic AI or conducting proofs of concept.
• 35% are planning adoption within the next 12 to 24 months.
• 20% are taking a wait-and-see approach.

Early implementations focus primarily on information retrieval, alert prioritization, contextual enrichment, intelligence platform queries, and MITRE ATT&CK mapping.

Organizations remain more cautious about granting agents autonomy over consequential actions, such as blocking IP addresses or changing security controls.

One research participant captured the concern:

“An agent that’s confidently wrong is worse than one that’s slow.”

Accuracy, data privacy, auditability, predictable costs, and human oversight remain central considerations. Organizations also expect AI investments to demonstrate measurable value through time savings, improved efficiency, and faster response.

Preparing Your Threat Intelligence Strategy for 2027

As organizations prepare for 2027, four priorities can help guide threat intelligence planning:

1. Plan for threats you cannot readily observe. Identify potential gaps in intelligence collection and examine emerging attack methods, including weaknesses in internal security processes.
2. Prepare for machine-speed attacks. Evaluate detection, prioritization, and response capabilities against increasingly compressed attack timelines.
3. Turn AI threats into actionable intelligence requirements. Map emerging techniques to relevant adversaries, established frameworks, defensive controls, and business risks.
4. Use agentic AI where it can extend analyst capacity. Prioritize repeatable workflows that deliver measurable value while maintaining appropriate data controls and human oversight.

Watch 22 Million Reasons to Rethink Your 2027 Threat Intelligence Strategy for a deeper look at the cybercriminal underground, enterprise threat intelligence investment trends, and practical considerations for agentic AI adoption.

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Data Center Physical Security: Mitigating FPV Drone Threats

In this post, we explore how shifting online sentiment and low-cost First-Person View (FPV) technology are creating an unprecedented airborne threat vector for critical data center infrastructure.

Data centers have become a driving force in the modern digital economy—powering cloud services, global enterprise operations, and the explosive growth of artificial intelligence (AI). However, due to growing negative public discourse, data centers are facing a new physical threat vector: low-cost, payload-capable drones.

According to Flashpoint research, shifting public sentiment surrounding AI development, combined with the extreme accessibility of First-Person View (FPV) drone technology, is creating an unprecedented hybrid threat to physical critical infrastructure.

Here is what you need to know about this emerging threat landscape and what it means for physical security teams protecting critical assets.

Growing Online Sentiment and Anti-AI Hostility

Organizations tasked with protecting critical data infrastructure need to understand that this growing threat is not developing in a vacuum. Across both clearnet and Deep and Dark Web (DDW) forums, online discussions regarding data center expansion have intensified, with a significant portion bordering on hostility. Key drivers of negative sentiment include:

• Environmental & Local Concerns: Debates over massive energy consumption, water usage, noise, and localized quality-of-life impacts.
• Backlash against AI: Discontent directed at tech companies driving the rapid deployment of AI infrastructure.
• Perceived Regulatory Inaction: Frustration among activists who feel local and state governments are failing to halt or regulate new construction.

While much of the current online chatter currently revolves around organized protests and aspirational threats, Flashpoint analysts note a troubling uptick in rhetoric targeting corporate tech executives and data center infrastructure.

The Evolving Data Center Threat Landscape

Data centers across the United States are seeing a rapid increase in physical and operational threats. Vandalism and property destruction have become common topics in illicit online spaces when discussing data centers and their impact on everyday life. Flashpoint research highlights two primary force multipliers driving this threat:

DIY Drones & Low Barriers to Entry

Historically, kinetic airborne strikes required specialized equipment and advanced training. Today, that barrier to entry has virtually collapsed. Rapid improvements in drone manufacturing have made payload-capable aircraft extraordinarily accessible. In today’s market, an individual can purchase an off-the-shelf system or assemble a customized drone for under $1,000 USD.

Inspiration for these tactics is also readily available; widespread footage of FPV drones operating in conflict zones like Ukraine has demonstrated to online audiences how easily and effectively low-cost aircrafts can be weaponized. Threat actors view this as a high-yield investment, especially given the capability to deploy multiple drones in quick succession.

Protests as Cover for Physical Operations

Organized protests to stop data center development remain prevalent, and large crowds can easily overwhelm contracted security personnel, diminishing the effectiveness of a response to an aerial threat. A malicious actor could use a protest at a data center as cover to cause physical damage to the facility while security resources are spread thin. For example, on July 19, 2026, activists threw balloons filled with acetic acid at a data center construction site in Amsterdam. In its aftermath, Flashpoint analysts captured individuals online discussing the use of drones to deliver similar payloads.

Regulatory and Defense Measure Challenges

Current federal regulations limit the ability to effectively deter or stop an incoming drone threat because the US Federal Aviation Administration (FAA) classifies drones as aircraft. Therefore, organizations specializing in the physical security of data centers will likely need to increase their operational capabilities and advise companies on potential hardening to deter attacks.

Traditional foot patrols and monitoring perimeter access control points will be insufficient in mitigating overhead threats. The majority of data centers are currently not equipped with the specialized Counter-Unmanned Aircraft Systems (C-UAS) equipment, specialized training, or legal authorization needed to respond effectively to airborne incursions.

Protect Critical Infrastructure Using Flashpoint

Defending against aerial incursions requires moving from reactive security to proactive, intelligence-led physical protection. Physical security teams cannot afford to rely solely on ground-level surveillance when threat actors are leveraging open-source hardware and coordinating online.

Flashpoint Physical Security Intelligence (PSI) equips security teams and executive protection units with real-time visibility into emerging physical threats before they reach your perimeter:

• Early Warning Indicator Tracking: Monitor chatter across mainstream social platforms, fringe networks, and illicit DDW forums to identify probe attempts or the targeting of specific data center facilities and executives.
• Geospatial Threat Mapping: Overlay real-time intelligence onto physical assets using customizable geofencing to detect active incidents, protest activity, and drone-related discussions near sensitive sites.
• Actionable Counter-UAS Insights: Receive finished intelligence and analyst support to benchmark threat actor TTPs (Tactics, Techniques, and Procedures), enabling your organization to harden physical structures and justify operational investments.

To learn more about how Flashpoint helps safeguard critical infrastructure, executives, and high-value assets against physical and cyber threats, request a demo today.

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The Flashpoint Method: Prioritizing Vulnerabilities in an Era of AI-Accelerated Discovery

We outline Flashpoint’s practical, repeatable framework for prioritizing vulnerabilities based on real-world risk, exploitability, and business impact.

Organizations are gaining new ways to identify vulnerabilities at scale, thanks to new generations of powerful AI models. However, security teams still face the same fundamental question: which vulnerabilities actually matter?

Vulnerability management teams have increasingly struggled to keep pace with growing disclosure volumes. From January 1, 2026 to June 30, 2026, Flashpoint tracked 21,667 vulnerabilities, an 8% period-over-period increase, with one-in-five containing publicly available exploit code at time of disclosure. At the same time, the gap between disclosure and exploitation continues to shrink, with some vulnerabilities weaponized in as little as 24 hours.

Flashpoint’s Method for Threat-Informed Vulnerability Prioritization

Recent developments such as Anthropic’s Mythos model have highlighted the growing potential for AI-assisted vulnerability discovery. As advances in code analysis enable researchers and organizations to identify software flaws at unprecedented speed and scale, the volume of discovered vulnerabilities is set to potentially increase significantly across software ecosystems.

That’s why we created this guide, The Flashpoint Method for Threat-Informed Vulnerability Prioritization, a practical, intelligence-driven framework designed to help vulnerability and exposure management teams cut through the AI-driven noise and focus on the vulnerabilities that matter most. By incorporating real-world exploitation activity, threat actor behavior, asset exposure, business context, and remediation considerations, organizations can make faster, more informed decisions and reduce risk more effectively.

Download to gain:

1. A clear, threat-informed prioritization framework: How to assess which vulnerabilities demand immediate attention, and why — moving beyond static severity scores alone.
2. Core and expanded prioritization checklists: Criteria spanning asset criticality, active exploitation, CVSS severity and ransomware risk, social risk and community chatter, business context, compensating controls, zero-day status, KEV inclusion, EPSS scoring, ease of remediation, and vulnerability age.
3. How to operationalize prioritization at AI scale: Insight into how Flashpoint’s vulnerability intelligence platform and analyst expertise help teams keep pace as AI-assisted discovery accelerates disclosure volume.

Prioritize Vulnerabilities More Effectively and Faster Using Flashpoint

While increased visibility into vulnerabilities is ultimately a positive for defenders, it amplifies a challenge security teams already face—separating which vulnerabilities represent meaningful risk to your environment and require immediate action.

Download The Flashpoint Method for Threat-Informed Vulnerability Prioritization to learn how Flashpoint’s vulnerability intelligence helps organizations triage, prioritize, and remediate risk more effectively.

Frequently Asked Questions (FAQ)

What is threat-informed vulnerability prioritization?

Threat-informed vulnerability prioritization is the process of evaluating vulnerabilities based on real-world risk rather than severity scores alone. It incorporates factors such as active exploitation, exploit availability, threat actor activity, asset exposure, business context, and remediation considerations to determine which vulnerabilities require immediate attention.

Why is vulnerability prioritization important?

Organizations face thousands of newly disclosed vulnerabilities each year, while security teams have limited time and resources to remediate them. Effective vulnerability prioritization helps organizations focus on the vulnerabilities most likely to be exploited and most likely to impact their environment.

How is AI changing vulnerability management?

AI-assisted code analysis is enabling researchers and organizations to identify software flaws faster and at greater scale. While increased visibility into vulnerabilities benefits defenders, it also increases the volume of vulnerabilities that security teams must evaluate, making effective prioritization even more important.

Why isn’t CVSS enough for vulnerability prioritization?

CVSS provides a standardized measure of technical severity, but it does not account for whether a vulnerability is actively being exploited, relevant to your environment, or likely to impact your business. Effective prioritization combines severity with threat intelligence and organizational context to assess real-world risk.

How does Flashpoint help organizations prioritize vulnerabilities?

Flashpoint combines analyst-driven vulnerability intelligence with real-world exploitation data, threat actor insights, asset exposure, and business context to help organizations identify the vulnerabilities that pose the greatest operational risk. This intelligence supports faster, more informed remediation decisions and operationalizes threat-informed vulnerability management at AI scale.

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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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AI agents are moving deeper into offensive cyber operations. In a campaign highlighted in September reporting, a Chinese-speaking operator reportedly deployed multiple open-source AI agent frameworks to find and exploit vulnerabilities across several targets, automating work that would ordinarily require hands-on effort from an attacker.

The reported activity illustrates how AI tools are being applied to increasingly complex stages of an attack, including tasks that traditionally require substantial technical expertise and hands-on effort.

Meanwhile, the volume of AI-related activity across illicit communities continues to climb.

In September 2026, Flashpoint analysts identified 8,837,186 posts discussing artificial intelligence in the context of illicit activity, up from 7,461,908 in August. That represents an approximately 18% increase in a single month.

Across forums, marketplaces, and chat services, threat actors continue to advertise AI services, exchange techniques, and explore ways to incorporate AI into fraud, identity verification bypass, social engineering, and offensive cyber operations.

To track these developments, Flashpoint’s monthly AI Threat Report analyzes primary source communities across forums, marketplaces, and chat services. This month’s intelligence highlights a sharp increase in AI-enabled identity verification bypass activity, continued demand for malicious AI capabilities, and emerging examples of AI agent tooling being used in offensive operations.

Where AI Activity Is Concentrated

Telegram remained the dominant source of observed AI service advertisements in September, with 6,309,872 posts, up from 4,899,407 in August. That represents an approximately 29% month-over-month increase.

Activity across other platforms was substantially lower. Flashpoint identified 20,361 posts on GitHub Gist, followed by Pastebin (6,288), Signal (6,123), and Reddit (5,882). Smaller volumes were observed across 4chan, BlackHatWorld, Discord, Mastodon, and other sources.

As with previous months, these figures do not represent unique advertisements or services. Threat actors frequently repeat or distribute the same messages across multiple channels and platforms to maximize exposure.

Telegram’s continued dominance underscores its importance as a distribution channel for illicit AI services. Other platforms provide additional avenues for sharing technical material, advertising capabilities, and discussing methods.

The distribution of activity also reinforces why post volume requires context. Repeated advertisements can inflate overall counts, making it important to examine the underlying services and techniques being promoted alongside changes in activity.

AI-Enabled Fraud and Identity Verification Bypass

Discussions of AI-enabled identity verification bypass continued to accelerate in September.

Flashpoint analysts observed 1,171,914 posts advertising or discussing Know Your Customer (KYC) bypass methods using AI technology, including deepfake technology. That compares with 751,644 posts in August, representing an approximately 56% month-over-month increase.

The increase is particularly noteworthy given the growth already observed in August, when KYC-related activity nearly doubled from July. Across the past two months, the number of observed posts has nearly tripled, rising from 394,567 in July to more than 1.17 million in September.

These discussions are concentrated in Telegram channels advertising methods designed to circumvent identity verification controls through generative AI, including deepfake technology.

For financial institutions and other organizations that rely on digital identity verification, this activity warrants close attention. AI-enabled impersonation can create additional challenges for onboarding, account recovery, and other processes that depend on verifying a user’s identity.

The sustained increase in underground discussion also provides security and fraud teams with an important signal about where threat actor interest is concentrated, even when repeated advertisements contribute to the overall volume.

Malicious LLM Usage and Prompt-Based Workflows

Malicious and unrestricted large language models (LLMs) remained part of the AI-related activity observed across Flashpoint Collections in September.

Threat actors continue to develop their own models or seek ways to bypass safeguards imposed by mainstream AI services. These capabilities can support phishing, social engineering, harmful code generation, and the creation of malicious or offensive content.

The availability of malicious and unrestricted LLMs gives threat actors additional options for incorporating AI into existing workflows. Models designed or modified to circumvent safety restrictions can be used to generate content and technical material that mainstream services would ordinarily reject.

These tools also introduce challenges for security teams assessing how AI-enabled threats are evolving. Understanding which models are being discussed, how they are marketed, and the capabilities being sought by threat actors can provide insight into emerging areas of interest across illicit communities.

Notable AI-Related Activity Observed in September

Flashpoint identified several notable developments involving AI infrastructure and the growing use of AI in offensive cyber operations.

September reporting highlighted a Chinese-speaking operator reportedly using three open-source AI agent frameworks, including Strix and Cairn, to automate vulnerability discovery and exploitation across multiple targets, according to The Register, citing Gambit.

These developments highlight two areas of concern: the targeting of proprietary AI infrastructure and the potential for agent-based tools to accelerate offensive operations. For security teams, both reinforce the importance of protecting AI development environments and addressing exploitable weaknesses before attackers can capitalize on them.

What Security Teams Should Take Away

September’s intelligence points to continued growth in AI-related criminal activity, with particularly sharp increases in discussions surrounding identity verification bypass.

Flashpoint observed more than 8.8 million posts discussing AI and criminal activity, while KYC bypass discussions exceeded 1.17 million posts for the first time in the three-month period examined.

At the same time, reported activity involving AI agent frameworks illustrates how automation is extending into more complex offensive workflows. Threat actors are exploring ways to apply AI to vulnerability discovery and exploitation, alongside its established uses in fraud, impersonation, and social engineering.

For security teams, these developments reinforce the importance of maintaining visibility into the communities where new capabilities are discussed, advertised, and tested. Tracking changes in activity and understanding how tools are being applied can help organizations identify emerging risks and better prioritize their defenses.

To see how Flashpoint can help your team identify and respond to emerging threats, 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 use and discuss artificial intelligence across illicit communities. Built on Flashpoint’s primary source collection, the report provides visibility into underground forums, chat services, marketplaces, and other environments where AI-related criminal activity is discussed and advertised.

How are threat actors currently using AI in cybercrime?

Threat actors are using or exploring AI capabilities across a range of criminal activities, including identity verification bypass, phishing, social engineering, malicious code generation, and vulnerability discovery.

September reporting also highlighted the use of AI agent frameworks to automate elements of offensive cyber operations, including vulnerability discovery and exploitation.

How rapidly is illicit AI activity growing in cybercrime communities?

Flashpoint analysts identified 8,837,186 posts discussing AI and criminal activities in September 2026, compared with 7,461,908 in August. This represents an approximately 18% month-over-month increase.

Activity related to AI-enabled KYC bypass also grew substantially, reaching 1,171,914 posts in September, an increase of approximately 56% from August.

These figures measure observed posts, rather than unique threat actors, services, or confirmed attacks.

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

Telegram continues to account for the largest concentration of observed AI service advertisements. Flashpoint identified more than 6.3 million posts advertising AI services on Telegram in September.

Other sources included GitHub Gist, Pastebin, Signal, Reddit, 4chan, BlackHatWorld, Discord, and Mastodon.

What are malicious LLMs?

Malicious LLMs are AI models developed, modified, or marketed for purposes that mainstream AI services typically restrict. Threat actors may use these models to generate phishing content, assist with social engineering, create harmful code, or support other criminal activities.

Flashpoint continues to track discussion of these models across illicit communities to understand how their capabilities and use cases are evolving.

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Flashpoint’s Top 5 Predictions for the 2026 Threat Landscape

Flashpoint’s forward-looking threat insights for security and executive teams, provides the strategic foresight needed to prepare for the convergence of AI, identity, and physical security threats in 2026.

As the global threat landscape accelerates its transformation, 2026 marks an inflection point requiring defensive strategies to fundamentally shift. The volatility observed in 2025 has paved the way for an era soon to be defined by AI-weaponized autonomy, information-stealing malware, systemic instability of public vulnerability systems, and the complete convergence of digital and physical risk.

Flashpoint offers a unique window into these complexities, providing organizations with the foresight needed to navigate what lies ahead. Drawing from Flashpoint’s leading intelligence and primary source collections, we highlight five key trends shaping the 2026 threat landscape. These insights aim to help organizations not only understand what’s next but also build the resilience needed to withstand and adapt to emerging challenges.

Prediction 1: Agentic AI Threats Will Weaponize Autonomy, Forcing a New Defensive Standard

2026 will see continued evolution of AI threats, with future attacks centering on autonomy and integration. Across the deep and dark web, Flashpoint is observing threat actors move past experimentation and into operational use of illegal AI. 

As attackers train custom fraud-tuned LLMs (Large Language Models) and multilingual phishing tools directly on illicit data, these AI models will become more capable. The criminal intent shaping their misuse will also become more sophisticated. Additionally, 2026 will see a greater marketplace for paid jailbreaking communities and synthetic media kits for KYC (Know Your Customer) bypass.

These advancements are enabling criminals to move beyond simple tools and engage in scaled, autonomous fraud operations, leading to two major shifts:

1. Agentic AI is becoming the true flashpoint: Threat actors will be using agentic systems to automate reconnaissance, generate synthetic identities, and iterate on fraud playbooks in near real-time. In this SaaS ecosystem, AI will help attackers leverage subscription tiers and customer feedback loops at scale.
2. The attack surface will shift to focus on AI Integrations: Organizations are increasingly plugging LLMs into live data streams, internal tools, identity systems, and autonomous agents. This practice often lacks the same security vetting, access controls, and monitoring applied to other enterprise systems. As such, attackers will heavily target these integrations, such as APIs, plugins, and system connections, rather than the models themselves.

“The ubiquity of automation has dramatically increased attack tempo, leaving many security teams behind the curve. While automation can replace repetitive tasks across the enterprise, organizations must not make the critical mistake of substituting human judgement for AI at the intelligence level.

This is paramount because a critical threat in 2026 is Agentic AI autonomy weaponized against soft targets—API integrations and identity systems. The only winning defense will be human-led and AI-scaled, prioritizing purposeful use to keep organizations ahead of this exponential risk.”

Josh Lefkowitz, CEO at Flashpoint

These evolving AI threats will force a fundamental shift in defensive strategies. Defenders will have to shift to deploying systems around AI rather than trust them on their own.

Prediction 2: Identity Compromise via Infostealers Will Become the Foundation of Every Attack

Infostealers will become the entry point, the data broker, the reconnaissance layer, and the fuel for everything that comes after a cyberattack. This shift is already in motion and is accelerating rapidly: in just the first half of 2025, infostealers were responsible for 1.8 billion stolen credentials, an 800% spike from the start of the year. However, 2026 will redefine the malware’s role, making its most valuable output being access, rather than disruption.

Infostealers will become the upstream event that powers the rest of the attack chain. Identity and session data will be increasingly targeted, since it gives attackers immediate access into victim environments. Ransomware, fraud, data theft, and extortion will simply be downstream ways to monetize.

This upstream approach defines the new reality of the attack chain, which is already operational. Nearly every major stealer strain Flashpoint observes now exfiltrates the following:

• Autofill PII (personable identifiable information)
• Saved addresses
• Phone numbers
• Internal URLs
• Browsing history
• Cloud app tokens

An organization’s attack surface is no longer just composed of their own networks. It is the entire digital identity of their employees and partners. This new reality requires security teams to take a new approach. Instead of attempting to block attacks, they must proactively detect compromised credentials before they are weaponized. This will be the difference between reacting to a data breach and preventing one.

“The infostealer economy has fully industrialized the attack chain, making initial compromise a low-cost commodity. Multiple security incidents in 2025 tie back to credentials found in infostealer logs. This reality has underscored the critical importance of digital trust—specifically, verifying who can access what resources. For 2026, identity is the perimeter to watch, and security teams must proactively hunt for compromised credentials before they’re weaponized.”

Ian Gray, Vice President of Intelligence at Flashpoint

Prediction 3: CVE Volatility Will Force Redundancy in Vulnerability Intelligence

The temporary funding crisis at CVE in April 2025 and the subsequent CISA stopgap extension through March 2026 exposed the systemic fragility of a centralized vulnerability intelligence model. With the future of the CVE/NVD system hanging in the balance, 2026 will be defined by the urgent need for redundancy and diversification in vulnerability intelligence.

In today’s vulnerability intelligence ecosystem, nearly every organization’s vulnerability management framework relies on CVE and NVD—including its “alternatives” such as the EUVD (European Union Vulnerability Database). The CVE system has grown into a critical global cybersecurity utility, relied upon by nearly all vulnerability scanners, SIEM platforms, patch management tools, threat intelligence feeds, and compliance reports. A complete shutdown of CVE would result in a widespread loss of institutional infrastructure.

The next generation of security needs to be built on practices that are resilient, diversified, and intelligence-driven. It should be focused on providing insights that can be used to take action such as threat actor behavior, likelihood of exploitation in the wild, relevance to ransomware campaigns, and business context. Security teams will need to leverage a comprehensive source of vulnerability intelligence such as Flashpoint’s VulnDB that provides full coverage for CVE, while also cataloging more than 100,000 vulnerabilities missed by CVE and NVD.

Prediction 4: Executive Protection Will Remain a Critical Challenge as Cyber-Physical Threats Converge

The continued blurring of lines between cyber, physical, and geopolitical threats will elevate the risk to organizational leadership, turning executive protection into a holistic intelligence function in 2026. The rise of information warfare combined with physical world convergence means the threat to key personnel is no longer purely digital.

In the aftermath of the tragic December 2024 assassination of United Healthcare’s CEO, Flashpoint has seen the continued circulation and glorification of “wanted-style posters” of executives in extremist communities. Additionally, Flashpoint has seen nation-state actors participate, using espionage and influence to target high-value individuals.
Organizations must adopt an integrated approach that connects insights from threat actor chatter and a wealth of other OSINT sources. This fusion of intelligence is essential for applying frameworks to ensure the safety of leadership and key personnel.

Prediction 5: Extortion Shifts to Identity-Based Supply Chain Risk

2025 was marked by several large-scale extortion campaigns, demonstrating how the threat landscape is rapidly evolving. Ransomware operations have shifted into a straight extortion play. Flashpoint has observed a surge in new entrants to the ransomware market, accompanied by a decline in the quality and decorum of ransomware groups.

Furthermore, vishing campaigns attributed to “Scattered Spider” have highlighted weaknesses in identity, trust, and verification. Campaigns from “Scattered LAPSUS$ Hunters” have also exposed vulnerabilities in third-party integrations. These attacks culminated in extortion, showcasing that modern attacks will target trusted users and trusted applications for initial access, and will forgo ransomware in place of data access.

As this shift continues into 2026, threat actors will increasingly focus their efforts on exploiting human behavior and identity systems. Instead of attempting to spend resources on breaking network perimeters, attackers will instead socially engineer employees to gain access to corporate systems at scale. This change in TTPs will undoubtedly greatly increase supply chain risk, especially for third parties.

Charting a Path Through an Evolving Threat Landscape with Flashpoint Intelligence

These five predictions highlight the transformative trends shaping the future of cybersecurity and threat intelligence. Staying ahead of these challenges demands more than just reactive measures—it requires actionable intelligence, strategic foresight, and cross-sector collaboration. By embracing these principles and investing in proactive security strategies, organizations can not only mitigate risks but also seize opportunities to enhance their resilience.

As the threat landscape continues to rapidly evolve, staying informed and prepared are critical components of risk mitigation. With the right tools, insights, and partnerships, security teams can navigate the complexities ahead and safeguard what matters most.

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