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Mythos-Ready Application Security Checklist

AI-powered vulnerability discovery is changing how attackers find and exploit software weaknesses. Use this 21-point checklist to evaluate whether your application security program is prepared for an AI-accelerated threat environment, from pre-engagement planning to remediation after your penetration test.

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Key Takeaways

  • Evaluate your readiness across 21 security controls spanning before, during, and after a penetration test.
  • Identify gaps in AI security, source code protection, dependency management, and attack path testing.
  • Learn which controls help reduce risk from AI-assisted vulnerability discovery.
  • Benchmark your security maturity with a simple scoring system.
  • Understand the next steps to strengthen your application security program after testing

Checklist · 21-point readiness audit

Mythos-Ready Application Security Checklist

Claude Mythos showed that AI can read source code and find exploitable weaknesses faster than any human team. Use this checklist to confirm your application security program is ready for an AI-accelerated threat environment, before your next penetration test.

•Most teams start with a penetration test, then add secure code review as their program matures.
•21 controls across 3 phases: before, during, and after your engagement.
•Check off items, tally your total, and match it to the scoring key below.
0/21 controls confirmed ☆☆☆☆☆

Check off items below to see your Mythos-readiness score.

1

Before the Engagement

7 controls
01Asset inventory complete

All cloud, SaaS, infra & AI agent surfaces documented. SBOMs generated for all builds.

02Dependency audit done

Third-party libraries reviewed. Known high-severity CVEs in open-source dependencies flagged.

03Scope includes AI surfaces

MCP servers, LLM integrations, agentic workflows added to scope, not just traditional endpoints.

04Patch velocity baselined

Current mean time to patch critical vulnerabilities documented. Target: under 24 hrs for critical, internet-facing issues.

05IR playbooks reviewed

Incident response plans updated for multi-vector, AI-assisted attack scenarios, not just single-CVE events.

06Access hygiene verified

Phishing-resistant MFA enforced, least-privilege access confirmed, secrets rotation current, extended to repos and git history: branch protection, mandatory PR review, and no leaked credentials in history.

07AI coding assistant policy set

Clear policy for what proprietary source code can be shared with AI coding tools. Vendor data-retention terms reviewed.

2

During the Engagement

6 controls
08Exploit chain simulation

Tester maps multi-step attack paths across identity, app, infra, not isolated vulnerabilities.

09AI-assisted discovery used

Engagement uses AI tooling to surface vuln classes automated scanners and humans miss.

10Detection speed tested

Mean time to detect (MTTD) and contain (MTTC) actively measured during simulated attack sequences.

11Glasswing patches checked

Project Glasswing vendor patches reviewed. Confirm your stack has absorbed the latest disclosure wave.

12Egress filtering probed

Outbound traffic controls tested. Data exfiltration paths mapped and validated.

13Sandbox escape tested

If AI agents or LLM pipelines are in scope, tested for unsanctioned actions and privilege escalation.

3

After the Engagement

8 controls
14Vulnerabilities ranked by attack path

Vulnerabilities prioritised by exploitability and chain potential, not just CVSS score in isolation.

15Remediation SLAs set

Critical, internet-facing: patch within 24 hrs. High: 7 days. No quarterly maintenance-window exceptions.

16MTTD / MTTC benchmarked

Detection and containment times documented. Used to update board-level risk metrics going forward.

17Open-source deps patched

All flagged third-party library vulnerabilities triaged and patched. SBOMs updated to reflect current state.

18Secure code review completed

The natural next step after your first pentest: a dedicated secure code review, not just automated scanning, for hardcoded secrets, injection flaws, and business-logic gaps.

19Source code vulnerabilities retested

Secure code review vulnerabilities remediated and revalidated. Confirms fixes hold before the next engagement cycle.

20IR playbooks updated

Playbooks revised based on attack paths found. Multi-simultaneous zero-day scenarios explicitly covered.

21Next engagement scheduled

Continuous cadence confirmed. Point-in-time testing is insufficient in an AI-accelerated threat environment.

Scoring key

18–21 ★★★★★ You're well prepared for a Mythos-ready penetration test.
13–17 ★★★★☆ Strong foundation with a few areas to improve.
7–12 ★★★☆☆ Several important security capabilities should be strengthened before testing.
0–6 ★★☆☆☆ Start with foundational application security improvements before scheduling a comprehensive engagement.

Not sure where you stand? Book a consultation. We'll help you scope the right mix of penetration testing and secure code review for where your program is today.

Book a Consultation →

Sources: Anthropic, Project Glasswing (Apr 2026) · Mandiant M-Trends 2026 · CSA/SANS/OWASP, "The AI Vulnerability Storm: Building a Mythos-Ready Security Program" (Apr 2026) · UK AI Security Institute, Mythos Preview cyber evaluation (Apr 2026)

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