Frontier models found the vulnerabilities. Only the attacker found the chains.
Snyk's comparison of frontier AI models for vulnerability discovery shows they reliably spot individual flaws but consistently miss exploitable multi-step attack chains—evidence that AI-assisted scanning cannot yet substitute adversarial reasoning in AppSec programmes.
Summary written by editorial AI · Source link below
Static analysis found the flaws, but only live attack testing proved how they could be chained into breaches. A comparison of Evo COS, Claude Security, and Claude Code Security.
Editorial Analysis
Enterprises adopting AI-driven vulnerability scanning should understand that current models are not capable of replacing human-led attack-chain analysis, and over-reliance creates a false sense of security.
Mandate complementary red-team or manual attack-chain reviews for any application where AI scanning is the primary vulnerability-discovery method.
AI vulnerability scanners find individual flaws effectively but miss the multi-step attack chains that lead to actual breaches, requiring continued investment in expert-led testing.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at Snyk Blog in a new tab.
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