A new benchmark, Snyk VulnBench 2.0, evaluates the effectiveness of AI security agents and deterministic static application security testing (SAST) tools in identifying vulnerabilities. The benchmark, comprising 108 hand-curated vulnerabilities across various programming languages, found that combining Snyk Code and Claude Code achieved the highest recall, identifying 101 out of 108 vulnerabilities. The study also highlighted that the AI model's performance is significantly influenced by its harness and review policies, with some AI configurations reporting vulnerabilities not present in the reference set. AI
IMPACT This research provides insights into the comparative effectiveness of AI security agents and traditional SAST tools, guiding future development and adoption in software security.
RANK_REASON The cluster is based on an academic paper detailing a new benchmark and its evaluation results.
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- Claude Code
- Codex Security
- GPT 5.6 Luna
- Java
- Javascript
- Opus
- Python
- Snyk Code
- Snyk MCP
- Snyk VulnBench 2.0
- Sol
- TypeScript
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