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Get Started Free →OWASP ZAP Advanced Integration - Enterprise Web Application Security Scanner
.claude/skills/shadd0wtaka-zap-advanced/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 101% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -7% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -42% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -49% | 0% |
| case-11 | ✗→✓ | ▲ Improved | -70% | 0% |
OWASP ZAP Advanced Integration - Enterprise Web Application Security Scanner
Category: scanning — Web Vulnerability Scanning
OWASP ZAP Advanced Integration - Enterprise Web Application Security Scanner
This module provides a comprehensive OWASP ZAP integration with:
Author: Zen-AI-Pentest Team License: MIT Version: 2.0.0
python# Auto-registered in tool_registry under "scanning" result = await tool_orchestrator.execute("zap_integration_advanced", target="example.com")
bashzap-advanced --help
deep-recon --tool zap_integration_advanced --target example.comscanningzen-agents_agent_run agent_type=scanning tool=zap_integration_advancedPOST /tools/execute with {"tool_name": "zap_integration_advanced", "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→pass | 10,033 | 15,783 | +57% | 1 | 1 | 0% | 1,822 | 3,658 | +101% | 0 | 0 | — |
case-02 | fail→fail | 6,818 | 13,210 | +94% | 1 | 1 | 0% | 841 | 1,420 | +69% | 0 | 0 | — |
case-03 | fail→fail | 8,589 | 8,103 | -6% | 1 | 1 | 0% | 868 | 991 | +14% | 0 | 0 | — |
case-04 | pass→pass | 30,919 | 13,882 | -55% | 1 | 1 | 0% | 1,888 | 1,746 | -8% | 0 | 0 | — |
case-05 | pass→pass | 3,715 | 6,615 | +78% | 1 | 1 | 0% | 627 | 912 | +45% | 0 | 0 | — |
case-06 | pass→pass | 9,535 | 10,423 | +9% | 1 | 1 | 0% | 1,798 | 2,298 | +28% | 0 | 0 | — |
case-07 | fail→pass | 9,274 | 20,958 | +126% | 1 | 1 | 0% | 1,591 | 1,486 | -7% | 0 | 0 | — |
case-08 | fail→fail | 7,602 | 1,693 | -78% | 1 | 1 | 0% | 1,289 | 634 | -51% | 0 | 0 | — |
case-09 | fail→pass | 19,870 | 9,984 | -50% | 1 | 1 | 0% | 1,405 | 817 | -42% | 0 | 0 | — |
case-10 | fail→pass | 8,632 | 2,556 | -70% | 1 | 1 | 0% | 1,528 | 774 | -49% | 0 | 0 | — |
case-11 | fail→pass | 10,082 | 1,200 | -88% | 1 | 1 | 0% | 1,743 | 518 | -70% | 0 | 0 | — |
case-12 | pass→pass | 7,352 | 7,892 | +7% | 1 | 1 | 0% | 1,233 | 521 | -58% | 0 | 0 | — |
case-13 | pass→pass | 8,425 | 2,069 | -75% | 1 | 1 | 0% | 1,388 | 593 | -57% | 0 | 0 | — |
case-14 | pass→pass | 17,113 | 15,816 | -8% | 1 | 1 | 0% | 2,851 | 3,007 | +5% | 0 | 0 | — |
case-15 | pass→pass | 7,749 | 4,669 | -40% | 1 | 1 | 0% | 1,329 | 1,025 | -23% | 0 | 0 | — |
case-16 | pass→pass | 10,996 | 7,157 | -35% | 1 | 1 | 0% | 1,700 | 1,437 | -15% | 0 | 0 | — |
case-17 | pass→pass | 8,559 | 8,426 | -2% | 1 | 1 | 0% | 1,385 | 1,276 | -8% | 0 | 0 | — |
case-18 | fail→fail | 15,222 | 15,759 | +4% | 1 | 1 | 0% | 2,592 | 2,868 | +11% | 0 | 0 | — |
case-19 | pass→pass | 15,500 | 15,216 | -2% | 1 | 1 | 0% | 2,570 | 2,750 | +7% | 0 | 0 | — |
case-20 | pass→pass | 19,889 | 17,438 | -12% | 1 | 1 | 0% | 3,211 | 3,052 | -5% | 0 | 0 | — |
case-21 | pass→fail | 12,335 | 8,074 | -35% | 1 | 1 | 0% | 2,033 | 1,665 | -18% | 0 | 0 | — |
case-22 | pass→pass | 13,620 | 14,837 | +9% | 1 | 1 | 0% | 2,365 | 2,773 | +17% | 0 | 0 | — |
case-23 | pass→fail | 12,535 | 11,077 | -12% | 1 | 1 | 0% | 2,251 | 2,449 | +9% | 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 +13 percentage points is the difference between those two pass rates over the 23 comparable cases. 2 cases got worse with the skill loaded, and they are 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.