r0oth3x49/ghauri

An advanced cross-platform tool that automates the process of detecting and exploiting SQL injection security flaws

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Summary Information

Updated 39 minutes ago
Added to GitGenius on September 16th, 2026
Created on October 1st, 2022
Open Issues & Pull Requests: 25 (+0)
GitHub issues: Enabled
Number of forks: 423
Total Stargazers: 4,082 (+0)
Total Subscribers: 40 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 3.3 days
Mean response time: 25.7 days
90th percentile: 44.1 days
Tracked items: 36

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Issue Activity (beta)

Open issues: 17
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 502 days
Stale 30+ days: 16
Stale 90+ days: 16

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (12)
  • enhancement (12)
  • help wanted (8)
  • Intended response (6)
  • can't reproduce (6)
  • invalid (6)
  • wontfix (4)
  • duplicate (1)

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Detailed Description

Ghauri is a SQL injection detection and exploitation tool that automates the discovery and abuse of SQL injection vulnerabilities in web applications.

The tool addresses the need for efficient identification and testing of SQL injection flaws during security assessments. It works by sending crafted requests to target endpoints, analyzing responses to detect injection points, and then executing payloads to extract data or manipulate database behavior. The automation reduces manual effort in vulnerability discovery and exploitation workflows.

Ghauri suits security researchers, penetration testers, and developers performing security audits on their own applications. It is designed for scenarios where you need to quickly identify whether SQL injection vulnerabilities exist and assess their severity through exploitation. The tool's cross-platform nature means it runs on different operating systems without requiring platform-specific setup.

The project shows consistent maintenance with regular updates addressing bug fixes and feature improvements. Development activity demonstrates responsiveness to reported issues and incorporation of user feedback into the codebase. The tool receives ongoing refinement to its detection logic and exploitation capabilities based on real-world testing scenarios.