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lintsinghua avatar

lintsinghua/DeepAudit

0
View on GitHub↗
4,668 stars·544 forks·Python·agpl-3.0·19 views

DeepAudit

DeepAudit is a privacy-preserving code audit platform that combines multiple specialized AI agents to identify and verify security vulnerabilities in source code. It functions as a local LLM vulnerability scanner, an automated security report generator, and a sandboxed exploit verifier, all operating entirely within an internal network to keep sensitive code and data on premises.

What distinguishes DeepAudit is its multi-agent cooperative approach: teams of AI agents jointly plan, analyze, and cross-check findings across the codebase, moving beyond single-pass scanning. The platform also sandbox-confirms exploitability by running proof-of-concept scripts in an isolated environment, reducing false positives while validating real-world risk. All analysis runs locally using on-premises large language models, ensuring no data leaves the internal network.

DeepAudit complements these differentiators with configurable audit scopes — allowing teams to target specific directories and file patterns — and rule-based vulnerability matching against known patterns. After analysis, it automatically produces a structured report with severity levels and remediation steps.

Features

  • Cooperative AI Auditors - Teams of specialized AI agents cooperatively plan, analyze, and verify vulnerabilities across the codebase.
  • Security Audit Reports - Aggregates findings, severity levels, and remediation steps into a structured report automatically after analysis.
  • Local Model Runtimes - Perform analysis locally using internal-network models to ensure data never leaves the premises.
  • Local Inference Engines - Runs large language models entirely within the internal network for analysis, ensuring data never leaves the premises.
  • Privacy-Preserving Code Auditors - Runs entirely within the internal network, ensuring source code and analysis remain on premises.
  • Sandboxed Exploit Verifiers - Executes PoC exploit scripts in a controlled sandbox to confirm vulnerability exploitability without risk.
  • Security and Vulnerability Scanning - Scan source code and configuration files for security vulnerabilities using rule-based analysis and known databases.
  • Vulnerability Detection - Compare code against known vulnerability patterns to detect security flaws and misconfigurations.
  • Security Report Generation - Producing a comprehensive report with findings, severity levels, and remediation steps automatically after the audit completes.
  • LLM-Orchestrated Scanners - Automates vulnerability scanning by orchestrating local large language models for private code analysis.
  • Source Code Vulnerability Scanning - Scanning source code and configuration files for known security vulnerabilities using rule-based pattern matching and vulnerability databases.
  • Audit Scope Configurations - Specify which directories and file patterns the audit scans to focus analysis on relevant code.
  • Vulnerability Matching - Scans code by comparing against a database of known vulnerability patterns and signature rules.

Star history

Star history chart for lintsinghua/deepauditStar history chart for lintsinghua/deepaudit

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Frequently asked questions

What does lintsinghua/deepaudit do?

DeepAudit is a privacy-preserving code audit platform that combines multiple specialized AI agents to identify and verify security vulnerabilities in source code. It functions as a local LLM vulnerability scanner, an automated security report generator, and a sandboxed exploit verifier, all operating entirely within an internal network to keep sensitive code and data on premises.

What are the main features of lintsinghua/deepaudit?

The main features of lintsinghua/deepaudit are: Cooperative AI Auditors, Security Audit Reports, Local Model Runtimes, Local Inference Engines, Privacy-Preserving Code Auditors, Sandboxed Exploit Verifiers, Security and Vulnerability Scanning, Vulnerability Detection.

What are some open-source alternatives to lintsinghua/deepaudit?

Open-source alternatives to lintsinghua/deepaudit include: securego/gosec — gosec is a static analysis security tool designed to scan Go source code for vulnerabilities and common coding flaws.… crytic/slither. pycqa/bandit — Bandit is a static analysis security testing tool and vulnerability detection scanner for Python source code. It… snyk/cli — The Snyk CLI is a command-line security scanner that detects known vulnerabilities across open-source dependencies,… ajinabraham/nodejsscan — nodejsscan is a static analysis security tool and vulnerability detection engine designed to scan Node.js source code… bearer/bearer — Bearer is a static analysis security testing tool and privacy compliance auditor. It identifies security…