web-vuln-scan

Guides deep vulnerability scanning of a single web target using fingerprint-driven tool selection and manual testing.

1.7k|238|Updated Dec 7, 2019
One-click install
npx skills add https://github.com/wgpsec/AboutSecurity --skill web-vuln-scan
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: web-vuln-scan
Source: https://github.com/wgpsec/AboutSecurity/tree/main/skills/exploit/web-method/web-vuln-scan
Command: npx skills add https://github.com/wgpsec/AboutSecurity --skill web-vuln-scan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

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.

Frequently Asked Questions about web-vuln-scan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I scan a single web application for vulnerabilities?

Start with fingerprinting using httpx or response headers to identify the tech stack, then run nuclei filtered by critical and high severity, check default logins, and fuzz directories with spray or ffuf. Follow up with manual testing of each input point for flaws automation misses.

What vulnerability should I test first in a web pentest?

Prioritize vulnerabilities that yield direct RCE such as command injection, deserialization, SSTI, and file upload bypass. Next target data-reading flaws like SQL injection and IDOR, then credential exposure, and finally user-interaction bugs like XSS and CSRF.

How does tech stack fingerprinting affect vulnerability scanning?

Fingerprinting determines which vulnerabilities are likely present, since each stack has distinct flaw patterns. For example Flask suggests SSTI and Werkzeug debug RCE, Java suggests Log4j and deserialization, and PHP suggests LFI and file upload issues.

What is the difference between nuclei and ffuf for web scanning?

Nuclei detects known vulnerabilities and misconfigurations using template-based checks, while ffuf fuzzes directories, parameters, and files to discover hidden endpoints. They complement each other: nuclei finds known CVEs, ffuf finds attack surface.

Why do automated web scanners miss critical vulnerabilities?

Automated tools cannot understand business logic or multi-step context, so they miss logic flaws, chained exploits, and authorization issues like IDOR. Manual testing of each functional input point is required to find these high-impact vulnerabilities.

When should I use depth-first scanning instead of reconnaissance?

Use depth-first scanning when the target is already confirmed and you need exhaustive vulnerability testing of one application. Breadth-first reconnaissance is for asset discovery across an organization, which is a separate earlier phase.