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In a recent blog, we explored what Anthropic’s Project Glasswing means for security programs and why the exposures it doesn’t find may matter more than the ones it does.
The thing is, Claude Mythos finds zero-day vulnerabilities across code and infrastructure at a speed no human team can match. That translates into a massive increase in findings headed your way. If your security program is built to find vulnerabilities and patch them, this flood will mean more work, for sure. But lower risk? Not so sure.
Turning Mythos’ volume into actual risk reduction takes a different operating model – one that validates what’s actually exploitable, looks beyond individual vulnerabilities, and prioritizes based on what matters to the business. In this blog, we’ll explain why traditional vulnerability-focused programs fall short in the Mythos era and how exposure management fills the gap.
What Project Glasswing and Mythos Do
Project Glasswing is Anthropic’s initiative to secure the world’s most critical software before AI-driven vulnerability discovery becomes available to a wider audience. The Mythos model finds vulnerabilities and figures out how to combine them into working exploits – including complex combinations that single-source scanners and manual reviews frequently miss.
The good news is that Anthropic has built safety and governance controls into the program. This means that the findings that reach the public will have already passed through an initial validation layer. But that still leaves a tsunami of new CVEs headed straight for your remediation queue. Even NIST announced that they will not enrich every CVE that goes into the National Vulnerability Database (NVD) following a surge of 263% increase of CVE submissions between 2020 and 2025.
Why Vulnerability-Focused Programs Fall Short
That wave of CVEs is coming whether your program is ready or not. And most programs aren’t – because they’re built around a single workflow: scan for CVEs, sort by CVSS, patch from the top. That workflow already struggles under today’s volume; Microsoft’s April Patch Tuesday dropped 163 new vulnerabilities – the second largest release in recent history.
Mythos will multiply it.
And the deeper problem is what that workflow leaves out. Because attackers don’t exploit isolated CVEs. They chain exposures together – a misconfiguration here, a cached credential there, an over-privileged service account connecting the two – until they find a path to a critical asset. And the exposures they rely on most – AD weaknesses, network reachability gaps, identity misuse – don’t even have CVSS scores. They don’t show up in vulnerability scans – because many of today’s breaches use identity or directory exposures as the pivot that gets attackers from one system to the next.
A security program that receives a flood of new Mythos-generated CVEs and runs them through the same pipeline will patch more and learn nothing new. It still won’t measure whether a fix actually reduced an exploitable path to a crown-jewel system – or just closed a finding that was never going anywhere.
How Exposure Management Helps Defenders in the Mythos Era
Exposure management platforms treat Mythos’ outputs as raw material that needs context before anyone acts on it. That context comes, for example, from continuous attack-path simulation – which shows you which findings are actually viable in your environment, which can be chained together to reach critical assets and which ones lead nowhere. In this way, you can discover choke points – intersections where a single fix eliminates multiple attack paths at once. And this helps your team get the most out of every hour it spends on remediation. What’s more, because validation keeps running in the background, you always know whether a fix actually broke an attacker path or just closed a ticket.
The approach also extends well beyond CVEs. Exposure management platforms offer unified visibility across on-prem and cloud, so an attack path that starts in one environment and ends in the other isn’t overlooked because two different tools are watching two different environments (like compromises that go from on-prem to cloud, or from external to internal). These platforms map over-privileged accounts and identity-based routes that enable lateral movement, and run assume-breach exercises to test whether your segmentation actually holds. And because the new findings originate from an AI model, advanced exposure management can offer clear governance around who can access which assets (including your AI infrastructure), what actions are taken, and who approves each step. None of these are fringe ideas – the Cloud Security Alliance’s recent Mythos ready paper lays out the same priorities: continuous validation, chained attack-path awareness, and business-context prioritization.
Acting on Mythos Findings Without Risking Production
All of the above is the strategic case. How should it work in practice when you’ve got a flood of Mythos-generated findings and you need to know which ones are real – without testing them against your live environment?
That’s where a digital twin – a capability built into advanced exposure management platforms like XM Cyber CEM – comes in. Using this technique, you can create a replica of your environment – identity relationships, network paths between systems, firewall rules, segmentation policies, and configurations – in isolation. Then you can emulate attacker steps to confirm whether each finding is actually viable. For each one, you get documented evidence of exploitability, reachability in light of security controls (like firewalls and MFA), and a clear picture of the potential compromise to your critical assets.
You also use the platform to test remediations before pushing them to production. You can confirm that a fix actually breaks the end-to-end chain and measure its effect on your overall exposure – all without risking accidental disruption to live systems.
Where to Focus First
If you’re building an exposure management program around Mythos-era findings, start with identity hygiene. Enforce least privilege, verify that MFA is actually in place, and remediate exposed service accounts. These are the pivot points attackers rely on most.
Active Directory is next. Secure trust relationships, reduce privileged account exposure, and monitor risky delegation configurations. AD weaknesses show up in the majority of real-world attack paths and they’re often the easiest to exploit.
From there, map your reachability and segmentation. Close unnecessary ingress paths and confirm that segmentation actually blocks lateral movement between zones. Fix insecure defaults that enable privilege escalation or data egress. Extend that visibility to your supply chain – vendor connections and third-party integrations create exposures that most programs never account for.
Once those foundations are solid, exposure management can help you harden your choke points – the single nodes attackers must pass through to reach critical assets. This way, every attack path that runs through these gets blocked at once.
Finally, feed validated findings into your workflows so remediation becomes part of daily operations. And track what actually matters: measurable reductions in exploitable paths to your crown jewels.
The Bottom Line
Mythos will accelerate vulnerability discovery far beyond what any team can process manually. But that acceleration can still create value if your program can separate the findings that matter from the ones that don’t – and prove it continuously.
Exposure management gives you that capability. It connects Mythos-generated findings to your actual environment, validates exploitability in a digital twin, and focuses remediation on the paths that reach your critical assets. The result is a program that measures risk reduction, not just patch counts.
More findings will mean more work. Yet with exposure management, they’ll also mean less risk.
Want to see how your program handles Mythos-era volume? Book a demo or talk to our team today.
