aiqbench analysis
This is a vendor-published comparison on one deliberately vulnerable app, so the 10-of-15 chain figure is a useful data point but not a general benchmark. The more durable point is the methodological split: source-code reasoning finds flaws, while live exploit testing shows whether they chain into a breach. Readers evaluating AI security tools should ask which of those questions a product actually answers.
Frontier models found the vulnerabilities. Only the attacker found the chains.
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.
Attackers don't read your repository; they hit your URL, and chain together whatever they find. In an era where offensive AI runs against live applications at machine speed, your security tooling needs to go beyond finding vulnerabilities to prove exploitability, including whether they can be combined into a breach. So we ran a test. We pointed Evo Continuous Offensive Security (COS) and Claude Security running Mythos at the same application: TaintedPort. It’s a deliberately vulnerable web app that exercises real-world bug classes and a set of registered exploit chains. These are different kinds of tools; COS attacks the running application while the…
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