bug-hunt-bench: 105 real bugs in two production repos, frontier coding models find and fix them in their own CLI, graded blind

by phuryn · Codex Skill · ★ 171

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Security audit verdict: SAFE · quality 51/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-codingbenchmarkbug-fixingclaude-codecodex-clicoding-agentsgpt-6leaderboardllm-benchmarkllm-evaluation

Quick Facts

Stars171
Forks7
LanguageJavaScript
CategoryCodex Skill
Quality Score51/100
Open Issues6
Last Updated2026-10-27
Created2026-08-25
Platformsclaude-code, cli, codex, gemini, node
Est. Tokens~18k

About bug-hunt-bench

Bug Hunt Bench — which AI coding model fixes the most real bugs? 105 real bugs, hidden in two production codebases. Frontier coding models — GPT-6, Claude, Grok, Gemini, DeepSeek, Kimi, GLM and more — get one round per repo in their own agentic CLI (Codex CLI, Claude Code, Grok CLI, Antigravity CLI) to find and fix what they can. Every diff is graded blind against a withheld answer key.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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