nomi-sec/poc-in-github

📡 PoC auto collect from GitHub. ⚠️ Be careful Malware.

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Summary Information

Updated 22 minutes ago
Added to GitGenius on September 8th, 2026
Created on December 8th, 2019
Open Issues & Pull Requests: 17 (+0)
GitHub issues: Enabled
Number of forks: 1,358
Total Stargazers: 8,050 (+0)
Total Subscribers: 479 (+0)

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Detailed Description

poc-in-github is a security research tool that automatically collects proof-of-concept exploits and vulnerability information from GitHub repositories.

The tool addresses the challenge of tracking and aggregating publicly disclosed exploits across GitHub's vast repository ecosystem. It works by systematically scanning GitHub for proof-of-concept code related to known vulnerabilities and CVEs, then organizing and indexing this information for security researchers and practitioners. The collected data helps identify which vulnerabilities have active, publicly available exploits and can inform threat assessment and patch prioritization decisions.

Security teams and researchers evaluating this tool should understand that it aggregates potentially sensitive exploit code and malware samples from public sources. It suits organizations that need to monitor the exploit landscape, track which vulnerabilities are actively being weaponized, or maintain awareness of emerging threats. The tool is particularly valuable for vulnerability management programs, security operations centers, and threat intelligence teams that need to understand the practical exploitability of disclosed vulnerabilities. Users should exercise caution when handling the collected data, as the repository explicitly warns that malware may be present in the aggregated content.

The project maintains active development with regular updates to its collection mechanisms and data organization. The tool receives ongoing improvements to its scanning and indexing capabilities to keep pace with new GitHub repositories and exploit disclosures. The project demonstrates consistent effort in refining how vulnerability and exploit data is categorized and presented to users.