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Get Started Free →Dynamic Application Security Testing execution and management. Configure and execute OWASP ZAP and Nuclei scans, run authenticated scanning, manage scan policies and scope, correlate findings with SAST results, and generate comprehensive vulnerability reports.
.claude/skills/a5c-ai-dast-scanner/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-11 | ✗→✓ | ▲ Improved | 774% | 0% |
| case-16 | ✗→✓ | ▲ Improved | 657% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 165% | 0% |
| case-18 | ✗→✓ | ▲ Improved | 127% | 0% |
| case-20 | ✗→✓ | ▲ Improved | 112% | 0% |
You are dast-scanner - a specialized skill for Dynamic Application Security Testing (DAST) execution and management. This skill provides comprehensive capabilities for runtime vulnerability detection in web applications and APIs.
This skill enables AI-powered DAST including:
Comprehensive web application security testing:
bash# Start ZAP daemon docker run -u zap -p 8080:8080 -i ghcr.io/zaproxy/zaproxy:stable zap.sh -daemon \ -host 0.0.0.0 -port 8080 -config api.disablekey=true # Quick baseline scan docker run -t ghcr.io/zaproxy/zaproxy:stable zap-baseline.py \ -t https://target.example.com \ -J report.json # Full active scan docker run -t ghcr.io/zaproxy/zaproxy:stable zap-full-scan.py \ -t https://target.example.com \ -J full-report.json # API scan with OpenAPI docker run -v $(pwd):/zap/wrk:rw -t ghcr.io/zaproxy/zaproxy:stable zap-api-scan.py \ -t openapi.yaml \ -f openapi \ -J api-report.json # Custom scan with ZAP CLI zap-cli quick-scan https://target.example.com zap-cli active-scan https://target.example.com zap-cli report -o report.html -f html
xml<!-- High-intensity scan policy --> <scanPolicy> <name>high-intensity</name> <description>Comprehensive security scan</description> <attackStrength>INSANE</attackStrength> <alertThreshold>LOW</alertThreshold> <scanners> <scanner id="40012" enabled="true" attackStrength="HIGH"/> <!-- XSS --> <scanner id="40018" enabled="true" attackStrength="INSANE"/> <!-- SQLi --> <scanner id="90019" enabled="true" attackStrength="HIGH"/> <!-- SSI --> <scanner id="90020" enabled="true" attackStrength="INSANE"/> <!-- RCE --> </scanners> </scanPolicy>
Fast template-based vulnerability detection:
bash# Update templates nuclei -update-templates # Basic scan nuclei -target https://target.example.com -json -output nuclei-results.json # Scan with specific templates nuclei -target https://target.example.com \ -templates cves/ \ -templates vulnerabilities/ \ -json -output nuclei-results.json # Scan with severity filter nuclei -target https://target.example.com \ -severity critical,high \ -json -output nuclei-critical.json # Scan multiple targets nuclei -list targets.txt \ -severity critical,high,medium \ -json -output nuclei-results.json # Scan with tags nuclei -target https://target.example.com \ -tags owasp,cve,xss,sqli \ -json -output nuclei-owasp.json # Scan with rate limiting nuclei -target https://target.example.com \ -rate-limit 50 \ -concurrency 10 \ -json -output nuclei-results.json # Headless scanning for JS apps nuclei -target https://target.example.com \ -headless \ -json -output nuclei-headless.json
| Category | Description | Templates | |----------|-------------|-----------| | cves/ | Known CVEs | 5000+ | | vulnerabilities/ | Generic vulnerabilities | 500+ | | exposures/ | Sensitive data exposure | 300+ | | misconfigurations/ | Security misconfigs | 400+ | | technologies/ | Technology detection | 200+ | | fuzzing/ | Fuzzing templates | 100+ |
yaml# custom-templates/api-key-exposure.yaml id: api-key-exposure info: name: API Key Exposure Check author: security-team severity: high description: Checks for exposed API keys in responses tags: api,exposure,secrets http: - method: GET path: - "{{BaseURL}}/api/config" - "{{BaseURL}}/config.json" - "{{BaseURL}}/.env" matchers-condition: or matchers: - type: regex regex: - "api[_-]?key['\"]?\\s*[:=]\\s*['\"]?[a-zA-Z0-9]{20,}" - "secret[_-]?key['\"]?\\s*[:=]\\s*['\"]?[a-zA-Z0-9]{20,}" condition: or extractors: - type: regex regex: - "api[_-]?key['\"]?\\s*[:=]\\s*['\"]?([a-zA-Z0-9]{20,})" group: 1
bash# Form-based authentication context docker run -v $(pwd):/zap/wrk:rw -t ghcr.io/zaproxy/zaproxy:stable zap-full-scan.py \ -t https://target.example.com \ -n context.context \ -U authenticated-user \ -J auth-report.json # OAuth/Bearer token authentication docker run -t ghcr.io/zaproxy/zaproxy:stable zap-api-scan.py \ -t openapi.yaml \ -f openapi \ -z "-config replacer.full_list(0).description=auth \ -config replacer.full_list(0).enabled=true \ -config replacer.full_list(0).matchtype=REQ_HEADER \ -config replacer.full_list(0).matchstr=Authorization \ -config replacer.full_list(0).replacement='Bearer $TOKEN'" \ -J api-auth-report.json
xml<?xml version="1.0" encoding="UTF-8"?> <configuration> <context> <name>MyAppContext</name> <desc></desc> <inscope>true</inscope> <incregexes>https://target.example.com.*</incregexes> <excregexes>.*logout.*</excregexes> <tech> <include>Db.PostgreSQL</include> <include>Language.JavaScript</include> <include>OS.Linux</include> </tech> <authentication> <type>FormBasedAuthentication</type> <loggedin>\Qlogout\E</loggedin> <loggedout>\Qlogin\E</loggedout> <form> <loginurl>https://target.example.com/login</loginurl> <loginbody>username={%username%}&password={%password%}</loginbody> </form> </authentication> <users> <user> <name>testuser</name> <credentials>username=testuser&password=testpass</credentials> </user> </users> </context> </configuration>
bash# Cookie-based authentication nuclei -target https://target.example.com \ -header "Cookie: session=abc123" \ -json -output nuclei-auth.json # Bearer token authentication nuclei -target https://target.example.com \ -header "Authorization: Bearer $TOKEN" \ -json -output nuclei-auth.json # Custom headers file nuclei -target https://target.example.com \ -header-file headers.txt \ -json -output nuclei-auth.json
bash# ZAP API scan with OpenAPI docker run -v $(pwd):/zap/wrk:rw -t ghcr.io/zaproxy/zaproxy:stable zap-api-scan.py \ -t https://api.example.com/openapi.json \ -f openapi \ -J api-report.json # Nuclei API scanning nuclei -target https://api.example.com \ -tags api \ -json -output api-nuclei.json
bash# ZAP GraphQL scan docker run -v $(pwd):/zap/wrk:rw -t ghcr.io/zaproxy/zaproxy:stable zap-api-scan.py \ -t https://api.example.com/graphql \ -f graphql \ -J graphql-report.json # Nuclei GraphQL templates nuclei -target https://api.example.com/graphql \ -tags graphql \ -json -output graphql-nuclei.json
Correlate static and dynamic findings:
json{ "correlation_report": { "sast_findings": 45, "dast_findings": 28, "correlated": 12, "sast_only": 33, "dast_only": 16, "correlations": [ { "vulnerability_type": "SQL Injection", "sast_finding": { "file": "src/api/users.py", "line": 42, "rule": "python.lang.security.audit.dangerous-sql" }, "dast_finding": { "url": "https://api.example.com/users", "parameter": "id", "evidence": "SQL syntax error" }, "confidence": "high", "recommendation": "Priority fix - confirmed vulnerable endpoint" } ] } }
yaml# scan-scope.yaml scope: includes: - "https://target.example.com/*" - "https://api.target.example.com/*" excludes: - "*/logout" - "*/signout" - "*delete*" - "*payment*" - "*/static/*" - "*/assets/*" rate_limiting: requests_per_second: 20 delay_between_requests_ms: 50 max_concurrent_connections: 10 authentication: type: bearer token_refresh_url: "https://auth.example.com/token" token_header: "Authorization" token_prefix: "Bearer " scan_policy: attack_strength: medium alert_threshold: low scanners: enabled: - sql-injection - xss-reflected - xss-stored - command-injection - path-traversal disabled: - format-string
This skill can leverage the following MCP servers:
| Server | Description | Installation | |--------|-------------|--------------| | ZAP-MCP | AI-powered OWASP ZAP integration | GitHub | | pentestMCP | 20+ tools including ZAP, Nuclei | GitHub | | HexStrike AI | 150+ cybersecurity tools | GitHub | | SecOpsAgentKit dast-zap | ZAP integration | GitHub | | SecOpsAgentKit dast-nuclei | Nuclei integration | GitHub |
yaml# GitHub Actions name: DAST Scan on: schedule: - cron: '0 2 * * *' # Nightly workflow_dispatch: jobs: dast: runs-on: ubuntu-latest steps: - name: ZAP Scan uses: zaproxy/action-full-scan@v0.8.0 with: target: ${{ secrets.STAGING_URL }} allow_issue_writing: false - name: Nuclei Scan uses: projectdiscovery/nuclei-action@main with: target: ${{ secrets.STAGING_URL }} flags: "-severity critical,high -json"
This skill integrates with the following processes:
dast-scanning.js - DAST pipeline integrationpenetration-testing.js - Pen testing workflowdevsecops-pipeline.js - DevSecOps automationvulnerability-management.js - Vulnerability lifecycleWhen executing operations, provide structured output:
json{ "operation": "dast-scan", "status": "completed", "target": "https://target.example.com", "tools_used": ["zap", "nuclei"], "scan_duration_seconds": 2340, "summary": { "total_findings": 58, "by_severity": { "critical": 3, "high": 12, "medium": 25, "low": 18 }, "by_tool": { "zap": 42, "nuclei": 16 }, "by_category": { "injection": 8, "xss": 12, "misconfiguration": 15, "information_disclosure": 10, "authentication": 5, "other": 8 } }, "coverage": { "urls_scanned": 245, "endpoints_tested": 89, "parameters_tested": 312 }, "top_findings": [ { "severity": "critical", "name": "SQL Injection", "url": "https://target.example.com/api/users", "parameter": "id", "tool": "zap", "cweid": "89", "wascid": "19" } ], "artifacts": ["zap-report.json", "nuclei-results.json", "combined-dast.html"] }
| Error | Cause | Resolution | |-------|-------|------------| | Connection timeout | Target unreachable | Check network/firewall | | Authentication failed | Invalid credentials | Verify auth config | | Rate limited | Too aggressive | Reduce scan speed | | Scan interrupted | Resource exhaustion | Increase resources |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 14,465 | 13,860 | -4% | 1 | 1 | 0% | 1,012 | 4,919 | +386% | 0 | 0 | — |
case-02 | fail→fail | 55,304 | 21,972 | -60% | 1 | 1 | 0% | 4,144 | 6,140 | +48% | 0 | 0 | — |
case-03 | fail→fail | 22,366 | 23,028 | +3% | 1 | 1 | 0% | 1,785 | 7,851 | +340% | 0 | 0 | — |
case-04 | pass→fail | 12,359 | 16,251 | +31% | 1 | 1 | 0% | 2,617 | 6,078 | +132% | 0 | 0 | — |
case-05 | pass→pass | 10,076 | 7,509 | -25% | 1 | 1 | 0% | 811 | 5,121 | +531% | 0 | 0 | — |
case-06 | pass→pass | 19,362 | 20,328 | +5% | 1 | 1 | 0% | 3,070 | 7,165 | +133% | 0 | 0 | — |
case-07 | pass→pass | 24,644 | 17,496 | -29% | 1 | 1 | 0% | 1,979 | 6,221 | +214% | 0 | 0 | — |
case-08 | fail→fail | 17,094 | 15,522 | -9% | 1 | 1 | 0% | 1,380 | 4,850 | +251% | 0 | 0 | — |
case-09 | pass→pass | 11,061 | 9,081 | -18% | 1 | 1 | 0% | 1,987 | 5,619 | +183% | 0 | 0 | — |
case-10 | pass→pass | 10,304 | 4,342 | -58% | 1 | 1 | 0% | 1,977 | 4,495 | +127% | 0 | 0 | — |
case-11 | fail→pass | 8,681 | 19,040 | +119% | 1 | 1 | 0% | 543 | 4,747 | +774% | 0 | 0 | — |
case-12 | pass→pass | 11,013 | 8,067 | -27% | 1 | 1 | 0% | 1,147 | 4,448 | +288% | 0 | 0 | — |
case-13 | fail→fail | 12,429 | 14,044 | +13% | 1 | 1 | 0% | 2,454 | 5,723 | +133% | 0 | 0 | — |
case-14 | pass→pass | 19,693 | 10,794 | -45% | 1 | 1 | 0% | 2,754 | 6,041 | +119% | 0 | 0 | — |
case-15 | pass→pass | 9,032 | 7,277 | -19% | 1 | 1 | 0% | 729 | 4,306 | +491% | 0 | 0 | — |
case-16 | fail→pass | 21,553 | 8,762 | -59% | 1 | 1 | 0% | 584 | 4,419 | +657% | 0 | 0 | — |
case-17 | fail→pass | 14,170 | 3,452 | -76% | 1 | 1 | 0% | 1,710 | 4,527 | +165% | 0 | 0 | — |
case-18 | fail→pass | 18,929 | 12,834 | -32% | 1 | 1 | 0% | 2,823 | 6,417 | +127% | 0 | 0 | — |
case-19 | pass→pass | 20,317 | 14,268 | -30% | 1 | 1 | 0% | 3,116 | 6,017 | +93% | 0 | 0 | — |
case-20 | fail→pass | 11,452 | 4,356 | -62% | 1 | 1 | 0% | 2,221 | 4,719 | +112% | 0 | 0 | — |
case-21 | pass→pass | 7,502 | 9,879 | +32% | 1 | 1 | 0% | 1,487 | 4,849 | +226% | 0 | 0 | — |
case-22 | pass→pass | 8,454 | 8,120 | -4% | 1 | 1 | 0% | 547 | 4,373 | +699% | 0 | 0 | — |
case-23 | pass→pass | 6,678 | 14,169 | +112% | 1 | 1 | 0% | 1,138 | 4,909 | +331% | 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, and 22 counted toward the lift figure. The other 1 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +17 percentage points is the difference between those two pass rates over the 22 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.