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Get Started Free →Security audit skill. Use when asked to "audit security", "check for vulnerabilities", "security review", "pentest", or when evaluating code that handles auth, user input, secrets, or external data. Runs a phased scan covering OWASP Top 10 and STRIDE threat modeling.
.claude/skills/blueberrycongee-security-audit/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-05 | ✗→✓ | ▲ Improved | -24% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 10% | 0% |
| case-22 | ✓→✗ | ▼ Worse | 25% | 0% |
| case-02 | ✓→✓ | = Same ✓ | 3% | 0% |
| case-03 | ✓→✓ | = Same ✓ | -8% | 0% |
Phased security scan. Each phase is independent — skip phases that do not apply to the codebase.
CLI args, file uploads, WebSocket messages, IPC, environment variables)
For each entry point identified in Phase 1:
grep -r for common secret patterns in source (API keys, tokens, passwords,connection strings) — exclude node_modules, .git, lock files
git log --all -p -S "password\|secret\|api_key\|token" for secretsthat were committed and later removed (they are still in history)
.gitignore covers .env, credential files, and key materialin client-side bundles
npm audit / pip audit / equivalentIf CI/CD config exists (.github/workflows/, .gitlab-ci.yml, etc.):
pull_request_target grant write access to untrusted PRs?For each component identified in Phase 1, evaluate:
For each finding:
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 9,759 | 12,946 | +33% | 1 | 1 | 0% | 1,070 | 1,734 | +62% | 0 | 0 | — |
case-02 | pass→pass | 12,831 | 8,728 | -32% | 1 | 1 | 0% | 2,213 | 2,270 | +3% | 0 | 0 | — |
case-03 | pass→pass | 10,975 | 5,624 | -49% | 1 | 1 | 0% | 1,871 | 1,718 | -8% | 0 | 0 | — |
case-04 | pass→pass | 11,858 | 13,048 | +10% | 1 | 1 | 0% | 2,162 | 3,133 | +45% | 0 | 0 | — |
case-05 | fail→pass | 12,478 | 4,681 | -62% | 1 | 1 | 0% | 2,195 | 1,663 | -24% | 0 | 0 | — |
case-06 | pass→pass | 11,082 | 9,731 | -12% | 1 | 1 | 0% | 1,694 | 2,434 | +44% | 0 | 0 | — |
case-07 | pass→pass | 11,279 | 9,314 | -17% | 1 | 1 | 0% | 2,082 | 2,532 | +22% | 0 | 0 | — |
case-08 | pass→pass | 10,978 | 6,696 | -39% | 1 | 1 | 0% | 1,793 | 1,894 | +6% | 0 | 0 | — |
case-09 | pass→pass | 9,357 | 7,359 | -21% | 1 | 1 | 0% | 1,690 | 2,134 | +26% | 0 | 0 | — |
case-10 | pass→pass | 12,648 | 14,050 | +11% | 1 | 1 | 0% | 2,026 | 3,222 | +59% | 0 | 0 | — |
case-11 | pass→pass | 10,735 | 8,499 | -21% | 1 | 1 | 0% | 1,949 | 2,512 | +29% | 0 | 0 | — |
case-12 | pass→pass | 6,754 | 8,039 | +19% | 1 | 1 | 0% | 1,129 | 2,186 | +94% | 0 | 0 | — |
case-13 | pass→pass | 5,635 | 5,389 | -4% | 1 | 1 | 0% | 982 | 1,718 | +75% | 0 | 0 | — |
case-14 | pass→pass | 4,778 | 4,805 | +1% | 1 | 1 | 0% | 783 | 1,566 | +100% | 0 | 0 | — |
case-15 | pass→pass | 14,761 | 10,942 | -26% | 1 | 1 | 0% | 2,089 | 2,503 | +20% | 0 | 0 | — |
case-16 | pass→pass | 12,325 | 9,755 | -21% | 1 | 1 | 0% | 2,053 | 2,532 | +23% | 0 | 0 | — |
case-17 | fail→pass | 10,423 | 6,358 | -39% | 1 | 1 | 0% | 1,819 | 1,997 | +10% | 0 | 0 | — |
case-18 | pass→pass | 13,280 | 12,748 | -4% | 1 | 1 | 0% | 2,251 | 3,063 | +36% | 0 | 0 | — |
case-19 | pass→pass | 12,891 | 16,980 | +32% | 1 | 1 | 0% | 1,992 | 3,607 | +81% | 0 | 0 | — |
case-20 | pass→pass | 7,477 | 11,543 | +54% | 1 | 1 | 0% | 1,321 | 1,781 | +35% | 0 | 0 | — |
case-21 | fail→fail | 3,966 | 5,004 | +26% | 1 | 1 | 0% | 687 | 1,750 | +155% | 0 | 0 | — |
case-22 | pass→fail | 13,390 | 13,707 | +2% | 1 | 1 | 0% | 2,599 | 3,239 | +25% | 0 | 0 | — |
case-23 | pass→pass | 20,453 | 28,331 | +39% | 1 | 1 | 0% | 4,549 | 6,904 | +52% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +4 percentage points is the difference between those two pass rates over the 23 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.