qazbnm456/awesome-web-security

🐶 A curated list of Web Security materials and resources.

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Summary Information

Updated 51 minutes ago
Added to GitGenius on September 4th, 2026
Created on January 29th, 2017
Open Issues & Pull Requests: 2 (+0)
GitHub issues: Enabled
Number of forks: 1,816
Total Stargazers: 13,776 (+0)
Total Subscribers: 344 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 23.8 days
Mean response time: 461.8 days
90th percentile: 1339.7 days
Tracked items: 26

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 5% of issues opened in the past year have been closed. Three people close 100% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 1
New in 7 days: 1
Closed in 7 days: 3
Avg open age: 42 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 1
Closed in 7 days: 3
Comments in 7 days: 5
Events in 7 days: 9

Top labels

  • health/link-check (4)
  • report-link (1)

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Detailed Description

Awesome Web Security is a curated list of web security materials and resources for learning penetration testing techniques and vulnerability research.

The project addresses the widespread problem of web vulnerabilities caused by misconfiguration, insufficient security knowledge, and engineering gaps. It compiles learning materials, tools, and references organized by security topic to help developers and security researchers build cutting-edge penetration skills. The list covers areas including XSS, SQL injection, SSRF, JWT, OAuth, reconnaissance, WAF evasion, deserialization, SAML, and CTF write-ups.

This resource suits security practitioners, penetration testers, and developers seeking to deepen their web security knowledge. It works best as a reference guide for those actively studying security topics or preparing for capture-the-flag competitions. The project also integrates with AI assistants through a Claude Code Skill, allowing AI agents to query the latest content at runtime rather than relying on static snapshots, and supports integration with other AI tools like Codex.

The project maintains an actively curated collection with contribution guidelines in place. The tool ships structured data in a machine-readable format alongside the human-readable list, enabling programmatic access for AI assistants and other tools. Development activity includes ongoing maintenance of the resource index and support for multiple integration pathways beyond the core repository.