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ai security
30 days with Claude Mythos Preview: How Tenable adapted our security program, and why yours is next
Tenable conducted a 30-day evaluation of Anthropic's Claude Mythos Preview frontier AI model against its own codebase, building an agentic security harness to identify and prove exploitability of code flaws. The work demonstrated that frontier AI shifts code security from ranking potential defects to verifying which vulnerabilities are genuinely exploitable with reproducible proofs, though success depends on building robust orchestration systems around the model rather than the model alone. Tenable found the approach resource-intensive, requiring both significant compute costs and senior engineer time to properly implement and validate findings.
Why it matters: Security teams evaluating frontier AI for code testing should understand that while these models can generate working exploits faster than traditional static analysis, the real value lies in the harness and expert judgment required to translate findings into actionable remediation, making this approach suitable primarily for organizations with mature security practices and available senior engineering resources.
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ai security
30 days with Claude Mythos Preview: How Tenable adapted our security program, and why yours is next
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ai security
30 days with Claude Mythos Preview: How Tenable adapted our security program, and why yours is next
Tenable reported running Anthropic’s Claude Mythos Preview, a frontier artificial intelligence (AI) model, against its own source code for thirty days to generate reproducible exploits for identified flaws. The experiment showed that pairing the model with a purpose‑built harness turns suspected defects into confirmed, exploitable issues that analysts can act on. Tenable noted that while the AI speeds up discovery, the lasting value lies in the orchestration system and the senior engineer who defines threat models and validates results.
Why it matters: Security teams that rely on code analysis gain a clearer path to prioritize remediation when they can pair frontier AI models with a validated exploit harness, but must invest in senior expertise to interpret results.
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