On April 7, 2026, Anthropic unveiled Claude Mythos Preview, its most powerful frontier model to date and one that excels at cybersecurity tasks, specifically, vulnerability discovery in code. Mythos is capable of finding vulnerabilities and exploiting internal testing. And now, the board of directors and the executive management teams of every major organization already are posing the inevitable question to C-Suite leaders about Claude Mythos: “What are you doing about Claude Mythos? How are you preparing for a world where adversaries are using AI to find vulnerabilities in minutes?”
The answer is simple. They need to fight AI-assisted attacks with defensive security that autonomously and preemptively finds and fixes exposures at machine speed. This is the only way to report to the board on the number of security workflows the organisation has automated with AI and how it’s driven up the effectiveness of your security program. The urgency of the situation is perhaps why forward-thinking leaders are implementing continuous threat exposure management to counter the effects of AI-assisted attacks even before they occur.
Why does Exposure Management Matter when Claude Mythos Exists?
Frontier AI like Mythos and Claude Code Security address only the first stage of this lifecycle—identifying vulnerabilities. Exposure management addresses the rest. It allows organizations to discover every asset across your environment be it IT, cloud identity, AI and OT, understand whether they’re vulnerable and prioritize remediation based on business and technical context.
With tens of thousands of vulnerabilities, organizations struggle to understand which ones to plug first. Mythos and Claude Code Security don’t show organizations how a combination of vulnerabilities forms an attack chain leading to a critical system or intellectual property. Exposure management helps organizations see individual vulnerabilities in context and how they combine to create high-risk attack paths. Frontier models like Mythos and exposure management operate in entirely different domains and solve fundamentally different problems.
Being Security Ready in the Age of AI-Assisted Attacks
With 87% of organizations identifying AI-related vulnerabilities as the fastest-growing cyber risk, the urgency of building a security program to tackle AI-assisted attacks can’t be underestimated. This is where exposure management helps you strengthen your security posture.
Anthropic suggests that organizations patch everything on the Cyber Security Infrastructure Agency’s Known Exploited Vulnerabilities list. What it discounts is CVEs that haven’t landed on the list but could be very critical to business continuity. Tenable Research has tracked 201 CVEs that weren’t included in the KEV but could impact organizations due to the hardware or software they affect. The Citrix Session Recording Vulnerability that Tenable Research began watching nearly a full year (286 days) before it hit the KEV is one such example.
With the vulnerability discovery capabilities of Mythos falling into the hands of adversaries, the number of vulnerabilities could possibly grow by 10X or more. This means prioritizing which vulnerabilities to plug first becomes the most critical tool in a defender’s arsenal. Exposure management does just that. Using vulnerability priority rating, it narrows the majority of CVEs flagged as critical or high by CVSS to the 1.6% that create actual risk for the organization. It does this by analyzing the vulnerability’s reachability, identity context of what permissions a compromised asset has inherited, and whether it leads to a domain admin, business criticality of the vulnerability and attack path analysis.
For operational vulnerability management at enterprise scale, where tens of thousands of assets are assessed continuously and findings flow directly into compliance reporting and remediation workflows, probabilistic outputs generated by frontier models are not acceptable because they can produce different results by using the same prompt twice. Exposure management solves these constraints too because it combines data from scanners, endpoint agents, passive network monitors, web application scanners, OT-specific sensors, identity directory connectors, and cloud API integrations to discover every asset across live enterprise environments and deterministically assess whether deployed systems are vulnerable. It can even identify shadow AI footprints.
This data is then used to map attack paths and provide visibility into how threat actors combine vulnerabilities, misconfigurations, and excessive permissions to breach critical assets. This is essential to proactively close exposures and preventively disrupt the attacker’s journey.
Instead of being overwhelmed by AI assisted attacks, organizations must focus on intelligent prioritization, closing the gaps, and gaining full visibility into dangerous attack paths with the right exposure management solutions. Look for platforms that have cross-domain telemetry integrated with an agentic AI engine that automates asset discovery, tagging, triage, prioritization, and remediation workflows. With it, C-Suite leaders can confidently tell boards they are fighting fire with fire and it is an organization’s best bet to tackle AI-assisted attacks.
