What problem does it solve?
Once a target URL is confirmed, testers often waste time running blind full-scope scans or miss high-impact flaws that automated tools cannot detect. This Skill provides a depth-first methodology for thoroughly testing one web application, combining fingerprint-driven scan strategy with manual testing of logic and context-dependent vulnerabilities.
Core Features & Use Cases
- Tech-Stack-Driven Strategy: Maps fingerprint results (PHP, Java, Python, Node.js, .NET) to prioritized automated scan focuses and manual test areas, since vulnerability distribution differs greatly across stacks.
- Automated Scanning Workflow: Covers nuclei severity-filtered scans, default credential checks, and directory/sensitive-file discovery with spray or ffuf, highlighting admin panels, config leaks, and debug endpoints.
- Manual Testing Matrix & Prioritization: Maps input points (search, upload, JWT, API) to vulnerability classes and ranks testing order with RCE first, then credential/data access, then user-interaction bugs.
- Use Case: Given a confirmed Flask target with Werkzeug debug mode enabled, the Skill directs you to prioritize SSTI, debugger PIN exploitation, Pickle deserialization, and SECRET_KEY leakage before lower-value checks.
Quick Start
Ask the AI to perform a deep vulnerability scan of a confirmed target URL using the web-vuln-scan methodology, starting with fingerprinting and ending with a prioritized attack path plan.