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It's a fair question. Anthropic's Project Glasswing announcement, paired with the vulnerability research benchmarks coming out of OpenAI's GPT 5.5, has made AI-driven vulnerability discovery a board-level topic in a matter of weeks.
To answer that question, first we need to discuss the operational problem defenders actually face and why threat intelligence can be the best way to counter it at machine speed. Then we'll get into what Recorded Future is already deploying to solve it: our agentic processing.
Even before AI and the news of Mythos’ capabilities and speed, defenders were struggling. Signal volume was outpacing analyst capacity. Coverage gaps widened daily as long-tail vendors and niche platforms went unmonitored. Raw findings arrived without root cause, threat-actor relevance, or vetted remediation paths. Producing one analyst-grade enrichment took hours of senior researcher time. The math didn't work at enterprise scale.
The data point that should anchor any conversation about the AI vulnerability surge: The NVD disclosed approximately 50,000 CVEs in 2025. Recorded Future Intelligence observed only 446 actively exploited in the wild — less than 1%.
Finding vulnerabilities is one thing, but knowing which ones matter, to which environments, against which adversaries, and with which compensating controls already in place is a whole different matter. Forrester put it directly: “The limiting factor in security is no longer the ability and knowledge to find problems — it's the ability to absorb, prioritize, and act on them before adversaries do.” The bottleneck has always been on the absorb-prioritize-act side. The find side was never the problem.
Frontier AI models accelerate the finding side. Threat intelligence is what helps close the prioritization gap on the fixing side.
Threat intelligence is operational, not philosophical. It comes down to four signals that distinguish the small fraction of CVEs adversaries actually weaponize from the overwhelming majority that they don't. These four signals are non-negotiable to be able to get to the prioritizing at speed and scale:
Together, these four signals are how you prioritize what actually matters for any given defender.
If attackers are moving at Mythos speed, your defenses need to keep up using agentic processing and Autonomous Threat Operations. This is my answer to the question we started with about what Recorded Future is doing about the new world we live in.
Agentic processing is the production system that turns exposure signals into deployable intelligence. The pipeline reads descriptions, vendor advisories, and patch diffs the moment they appear. It produces production-ready detection signatures — documented detection logic, evidence specification, passive fingerprinting strategy. It writes analyst-grade enrichment for every finding — root cause, exploit mechanics, threat-actor associations, prioritized defensive controls with deploy-time and false-positive estimates, validated remediation tasks with acceptance criteria and rollback plans.
It’s end-to-end target: identification to deployment in customer environments in only 31 minutes. Internal averages run lower. No security team operating manual triage workflows is matching that throughput.
That content can reach every relevant control point in your environment through Autonomous Threat Operations (ATO).
ATO turns agentic-processing outputs and correlated intelligence into operational action across over 100 integrations spanning SIEM, SOAR, EDR/XDR, NGFW, vulnerability management, threat intelligence platforms, identity and access management, email and cloud security, GRC, and threat-informed defense. It continuously deploys priority intelligence, runs autonomous threat hunts, pushes detection rules, and takes preventive action without analyst hours spent on manual correlation. The 8-to-12 hours of weekly correlation work most analyst teams perform manually is almost entirely eliminated. The hunting cadence becomes 24/7.
Soon, ATO will do this across your attack surface and third parties, as vendor exposure has been the most common path to breach for the past three years.
The five-stage pipeline that produces all of this — threat signals, intelligent enrichment, validation and verification, structured output, and customer workflow — runs continuously. Production-ready content is in customer environments within minutes of the originating disclosure across every category of threat the platform detects.
Four things distinguish agentic processing from anything a security team can build manually:
These benefits represent the difference between preventing threats pre-attack and absorbing the damage after.
Let’s look at an example of what agentic processing does at machine speed.
Take CVE-2025-55182 — React2Shell, a pre-authentication remote code execution vulnerability in React Server Components. Within minutes of disclosure, agentic processing produced:
In this new Mythos age, this type of agentic processing and speed is going to be required as the new baseline.
Vulnerability disclosure is the most visible trigger for the intelligence-at-speed pattern, but it isn't the only one. The same operational logic applies wherever a new threat signal surfaces and a defender needs to act on it before the adversary monetizes it.
When a brand impersonation site is stood up, the defensive sequence is the same: detection, intelligence enrichment (registrant, registrar, hosting infrastructure, historical campaign association), prioritized defensive controls (takedown coordination, blocking at email and web layers, alerting affected employees), and verification that the takedown landed. Recorded Future's Digital Risk Protection runs this loop continuously across the open, deep, and dark web.
When a stolen credential surfaces in an infostealer log market, Identity Intelligence runs the same pattern: detection of credentials tied to your environment, enrichment with infection context (malware family, device, other credentials in the same log, MFA cookie capture status), prioritized response (force password reset, revoke active sessions, alert the user), and verification.
The pattern is the posture. Apply intelligence at machine speed wherever the adversary is acting, across every category of threat surface. Vulnerabilities are one trigger. The work generalizes. Recorded Future is operationalizing intelligence at machine speed across our four solutions, Cyber Operations, Digital Risk Protection, Third-Party Risk, and Payment Fraud Intelligence.
The operational response to AI-driven vulnerability discovery is what separates organizations that contain exposures from those that wake up to incident response calls.
We are seeing customers set up automation to move faster in response to this new reality. A large enterprise in the financial services sector used Recorded Future to transform their vulnerability management workflow. Following a major patching effort across the organization, the team built out automation between their vulnerability scanning and IT service management tools. The result: a streamlined, repeatable process and an estimated weekly time savings of over 20 hours for the team.
We recommend taking these five actions so you can respond as well:
AI-driven vulnerability discovery is here. The big question is whether your systems can operate at attacker speed, with a depth of intelligence that survives executive scrutiny. If the answer isn’t a confident yes, then Mythos and the category behind it have already shifted the math against you.
See it in production. Request a demo to see Recorded Future Intelligence and Autonomous Threat Operations turn a vulnerability disclosure into deployable detection and action across your stack within minutes.
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