5 Things Every CISO Should Do Before the Next Mythos
by Brad Hibbert, COO & CSO//9 min read/
The attack capability gap just closed. Here is how to respond.
For decades, sophisticated cyberattacks had a price tag. Discovering zero-day vulnerabilities, building working exploits, chaining complex attack paths across operating systems and cloud infrastructure required deep expertise, significant resources, and time. That kept the most dangerous attacks inside a relatively small club. Nation-states. Well-funded criminal organizations. Advanced persistent threat groups with the patience and capability to operate at that level.
That price tag just collapsed.
On April 7, 2026, Anthropic released Claude Mythos Preview to a restricted group of technology partners. Mythos autonomously discovers zero-day vulnerabilities at scale, builds working exploits without human guidance, and chains attacks from browser to kernel to cloud. In testing it found thousands of critical vulnerabilities across every major operating system and browser. Anthropic considered it too dangerous to release publicly. Within six to eighteen months, models with equivalent capability will be broadly available, with or without the same ethical constraints.
The implications are direct. Attacks that required nation-state resources last year will be accessible to a much wider group of threat actors this year. Organizations that were never a priority target for sophisticated attackers are now within reach of commodity operators using AI-powered tools. As Rich Mogull, Chief Analyst at the Cloud Security Alliance, put it, this technology represents a clear change in our fundamental risk assumptions around vulnerabilities and patching. The exposure surface every security team is responsible for just got harder to defend.
Over the past two weeks, conversations with CISOs and security leaders across our customer base have surfaced a consistent theme: boards and executive teams are already asking what their security organizations are doing about Mythos and the AI-powered threats that follow it. That question is no longer coming. For many, it has already arrived.
Here are five things to act on now.
1. Audit Your Security Program Against the New Threat Model
Most security programs were built for human-speed adversaries working with known attack patterns. Scheduled scans. Periodic assessments. Patch cycles measured in weeks. Those cadences made sense when the threat operated on human timelines. They do not hold up against automated discovery running continuously at scale.
Audit every active security investment against a single honest question: knowing what AI has done to the offense, would we fund this from scratch today? This is not about tearing down what you have built. It is about being honest about where the program has gaps that were acceptable before and are not acceptable now. Start with vulnerability management, detection coverage, and patch cadence. All three are running below the speed of the current threat.
2. Get Precise on What Actually Matters
Mythos has already surfaced thousands of critical vulnerabilities and over 99 percent remain unpatched. No team fixes everything. The organizations that navigate this well are the ones with a clear, defensible answer to a specific question: which exposures represent real, exploitable risk to this business right now.
“Cyber risk is a business decision. It is a choice. And most organizations do not treat it like one.”
– Paul Proctor, Distinguished VP Analyst, Gartner
That answer requires more than a CVSS score. It requires connecting the vulnerability to the asset, the asset to the business service, and the service to actual revenue, compliance, or operational impact. A cyber risk graph provides that connection. It maps your full exposure surface against business context: what is customer-facing, what is regulated, what carries the highest blast radius if compromised. Your team works from that picture, fixing what matters most rather than responding to whatever the scanner flagged loudest. In an environment where AI is accelerating both discovery and exploitation, vulnerability prioritization precision is what keeps you ahead.
3. Build Continuous Vulnerability Operations
Quarterly penetration tests and periodic assessments were designed for a threat that moved on human timelines. AI-powered attackers do not take quarters off. They run continuously, against every surface in your environment, looking for the path of least resistance.
Build a permanent vulnerability operations function. Not a project that runs twice a year. A standing capability that continuously ingests new findings, correlates them against business risk, and drives remediation at pace. This is the operational core of continuous threat exposure management (CTEM): the ability to absorb new waves of findings without losing momentum. The Cloud Security Alliance briefing published in the wake of Mythos was direct: the storm of vulnerability disclosures from Project Glasswing is the first of many waves. Your program needs to be built to absorb them, not react to them one at a time.
4. Use AI to Close the Gap, Not Just Measure It
Finding vulnerabilities faster only creates value if you can act on them faster. The security teams pulling ahead right now are the ones using AI not just to surface risk but to remediate it. AI-assisted code scanning, prioritization, and fix generation are no longer experimental. They are becoming the baseline of a program that can keep pace with AI-powered offense.
Start with your highest-criticality application code and cloud exposure. Build the working relationship between security and engineering now, before the pressure of a major vulnerability wave forces it. The time between a flaw being discovered by an attacker and that flaw being weaponized is shrinking. Your ability to find it first and close it fast is the only reliable response.
5. Get Ahead of the Board Conversation
The week Mythos was announced, the US Federal Reserve and Treasury Secretary held an emergency meeting with the CEOs of the country’s largest banks. The UK’s AI Security Institute issued a formal advisory. Legal experts have noted that as AI vulnerability scanning becomes accessible, the standard of reasonable defensive effort is shifting. Boards will ask whether your organization is using AI defensively, and whether not doing so creates liability beyond the technical.
Do not wait for the question to arrive. Prepare a brief that explains what Mythos represents, how your current program maps to the new threat reality, where you are investing to close the gap, and what you need to go further. Give your board a clear narrative and a CISO who has already thought this through. That framing matters as much as the technical response.
Build the Foundation Before the Next Wave Lands
Mythos is not the end state. It is the signal. Within months, equivalent capability will be in wider circulation. The organizations that respond well will be the ones that already know where they stand: full visibility across their exposure surface, business context applied to every finding, and the operational rhythm to act quickly when new threats land.
A cyber risk graph is how you build that foundation. It connects exposure to business impact, gives your team clear cyber risk prioritization when the pressure is high, and means that when the next Mythos arrives, and it will, your program is already oriented to respond.
The window to build that foundation is open right now. Use it.
Brinqa connects your full exposure surface to business context through a cyber risk graph, giving security teams the prioritization precision they need when the threat moves at AI speed.
Your program should be built for the threat that exists today, not the one from three years ago. If you want to talk through where your exposure management program stands, talk to a Brinqa expert.
