Blogs

Blog

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.

See Flashpoint in Action

Blogs

Blog

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.

See Flashpoint in Action

Blogs

Blog

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.

See Flashpoint in Action

Blogs

Blog

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.

Request a demo today.

Blogs

Blog

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.

Request a demo.