Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →OWASP ZAP Integration - Web Application Security Scanner for Zen-AI-Pentest
.claude/skills/shadd0wtaka-zap/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | -44% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -1% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 3% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -12% | 0% |
| case-17 | ✗→✓ | ▲ Improved | -64% | 0% |
OWASP ZAP Integration - Web Application Security Scanner for Zen-AI-Pentest
Category: scanning — Web Vulnerability Scanning
OWASP ZAP Integration - Web Application Security Scanner for Zen-AI-Pentest
This module provides a comprehensive OWASP ZAP wrapper with:
Au
python# Auto-registered in tool_registry under "scanning" result = await tool_orchestrator.execute("zap_integration", target="example.com")
bashzap --help
deep-recon --tool zap_integration --target example.comscanningzen-agents_agent_run agent_type=scanning tool=zap_integrationPOST /tools/execute with {"tool_name": "zap_integration", "target": "example.com"}| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 6,359 | 16,557 | +160% | 1 | 1 | 0% | 461 | 1,202 | +161% | 0 | 0 | — |
case-02 | fail→fail | 9,265 | 10,097 | +9% | 1 | 1 | 0% | 1,020 | 1,090 | +7% | 0 | 0 | — |
case-03 | fail→fail | 12,097 | 14,282 | +18% | 1 | 1 | 0% | 1,338 | 1,620 | +21% | 0 | 0 | — |
case-04 | pass→pass | 14,588 | 29,618 | +103% | 1 | 1 | 0% | 2,584 | 2,041 | -21% | 0 | 0 | — |
case-05 | pass→pass | 6,929 | 14,753 | +113% | 1 | 1 | 0% | 1,123 | 1,717 | +53% | 0 | 0 | — |
case-06 | pass→pass | 9,389 | 11,141 | +19% | 1 | 1 | 0% | 1,906 | 2,583 | +36% | 0 | 0 | — |
case-07 | fail→fail | 6,207 | 10,540 | +70% | 1 | 1 | 0% | 467 | 1,599 | +242% | 0 | 0 | — |
case-08 | fail→fail | 8,948 | 26,655 | +198% | 1 | 1 | 0% | 669 | 1,409 | +111% | 0 | 0 | — |
case-09 | fail→pass | 6,186 | 1,730 | -72% | 1 | 1 | 0% | 1,015 | 565 | -44% | 0 | 0 | — |
case-10 | fail→pass | 11,606 | 11,504 | -1% | 1 | 1 | 0% | 1,428 | 1,419 | -1% | 0 | 0 | — |
case-11 | fail→pass | 10,483 | 9,104 | -13% | 1 | 1 | 0% | 1,100 | 1,132 | +3% | 0 | 0 | — |
case-12 | fail→pass | 16,323 | 11,043 | -32% | 1 | 1 | 0% | 2,675 | 2,348 | -12% | 0 | 0 | — |
case-13 | pass→pass | 6,428 | 6,080 | -5% | 1 | 1 | 0% | 1,059 | 1,324 | +25% | 0 | 0 | — |
case-14 | pass→pass | 14,341 | 17,078 | +19% | 1 | 1 | 0% | 2,403 | 1,981 | -18% | 0 | 0 | — |
case-15 | pass→pass | 15,122 | 11,926 | -21% | 1 | 1 | 0% | 2,610 | 2,700 | +3% | 0 | 0 | — |
case-16 | pass→pass | 9,981 | 5,163 | -48% | 1 | 1 | 0% | 1,796 | 754 | -58% | 0 | 0 | — |
case-17 | fail→pass | 10,414 | 4,582 | -56% | 1 | 1 | 0% | 2,027 | 730 | -64% | 0 | 0 | — |
case-18 | pass→pass | 14,700 | 13,327 | -9% | 1 | 1 | 0% | 2,892 | 2,867 | -1% | 0 | 0 | — |
case-19 | pass→pass | 3,827 | 4,115 | +8% | 1 | 1 | 0% | 554 | 1,001 | +81% | 0 | 0 | — |
case-20 | pass→pass | 11,176 | 10,524 | -6% | 1 | 1 | 0% | 2,071 | 2,412 | +16% | 0 | 0 | — |
case-21 | pass→pass | 7,712 | 3,599 | -53% | 1 | 1 | 0% | 1,262 | 947 | -25% | 0 | 0 | — |
case-22 | fail→pass | 5,200 | 2,697 | -48% | 1 | 1 | 0% | 938 | 796 | -15% | 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. 22 cases were attempted. The headline lift of +27 percentage points is the difference between those two pass rates over the 22 comparable cases.
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.