AI Frameworks · lintsinghua

DeepAudit

DeepAudit is an open-source Python-based multi-agent system for automated code vulnerability detection and auditing. It uses LLMs (supporting Ollama private deployment) to identify security flaws, generate PoC exploits in sandboxes, and produce audit reports.

Talk to DEV.co Discuss Implementation

Source: GitHub — github.com/lintsinghua/DeepAudit

6.6k

GitHub stars

814

Forks

Python

Primary language

AGPL-3.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	lintsinghua/DeepAudit
Owner	lintsinghua
Primary language	Python
License	AGPL-3.0 — OSI-approved
Stars	6.6k
Forks	814
Open issues	90
Latest release	v3.0.4 (2026-01-24)
Last updated	2026-07-07
Source	https://github.com/lintsinghua/DeepAudit

What DeepAudit is

Multi-agent architecture built on FastAPI (Python 3.11+) backend and React 18 frontend, leveraging LLMs for code analysis (SAST) with automated sandbox PoC validation. Supports GitHub/GitLab/Gitea integration and private LLM deployment via Ollama.

Quickstart

Get the DeepAudit source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/lintsinghua/DeepAudit.git2cd DeepAudit3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

DevSecOps CI/CD Integration

Automate continuous code security scanning across multiple repositories with multi-project management and one-click report generation for compliance workflows.

Rapid Vulnerability Assessment

Quick security audits of legacy codebases or third-party projects without manual review; paste code or upload files for immediate LLM-driven analysis and findings.

Private Code Audit (On-Premises)

Organizations handling sensitive IP can deploy with Ollama for fully private LLM inference, eliminating cloud dependency and data exfiltration risk.

Implementation considerations

AGPL-3.0 copyleft: any network service using DeepAudit or modifications must publish source; review before enterprise adoption.
LLM backend dependency: accuracy tied to chosen model (Ollama private or cloud); fine-tuning and prompt engineering may be required for domain-specific code.
Sandbox PoC execution: assess security implications of automated exploit generation; restrict to isolated networks and monitor resource consumption.
Multi-agent orchestration complexity: ensure monitoring and logging of agent decisions; unclear from DATA if full audit trail is persistent.
Database/credential management: deployment with private Ollama still requires secrets for Git integration (tokens, SSH keys); review storage approach.

When to avoid it — and what to weigh

Require Commercial SLA/Support — AGPL-3.0 license imposes copyleft obligations; no official commercial support model or SLA is documented. Requires legal review for proprietary integration.
Need Proprietary Closed-Source Deployment — AGPL-3.0 mandates source code disclosure for networked use. Any modifications or derivative services must be open-sourced; closed commercial wrappers are not viable.
Depend on Mature Production Hardening — Project created Sept 2025, latest release Jan 2026. Insufficient real-world operational history; unproven resilience under large-scale audit workloads.
Require LLM Model Transparency — Tool relies on external LLMs (Google Gemini listed); accuracy and false-positive rates are model-dependent and not independently benchmarked in DATA.

License & commercial use

AGPL-3.0 (GNU Affero General Public License v3.0). Copyleft license requiring source code disclosure for any networked or modified use. Free to run internally; any service offering or derivative distribution triggers obligation to open-source modifications.

Commercial use is technically permitted under AGPL-3.0 *internally* (e.g., running DeepAudit on your own code for your own business). However: (1) any SaaS, hosted, or service-based offering must open-source all modifications; (2) no commercial support or warranty is stated in DATA; (3) unclear if proprietary integration (e.g., as a backend to closed-source tools) would violate AGPL copyleft. **Requires legal review before any commercial product integration or resale.**

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	High
DEV.co fit	Good
Assessment confidence	Medium

Security considerations

Automated PoC execution in sandboxes carries inherent risk of unintended code execution or resource exhaustion; isolation strategy not detailed in DATA. LLM-driven analysis can produce false positives/negatives; no independent validation benchmarks provided. AGPL requires source transparency, which aids security review but mandates openness. Supabase dependency introduces third-party data handling; unclear if audit data is encrypted at rest/transit. Private Ollama deployment mitigates cloud data exposure but requires local infrastructure hardening.

Alternatives to consider

Snyk or GitHub Advanced Security

Commercial, proprietary, SaaS-based vulnerability scanning with native CI/CD integration, dedicated support, and SLA. No copyleft obligations; simpler compliance for enterprise.

Semgrep Pro / r2c

Open-source (permissive license) SAST engine with commercial support available. Rule-based (not LLM-driven); faster, deterministic results; lower false-positive rates on known patterns.

Checkmarx / SonarQube Enterprise

Mature, widely-adopted SAST platforms with extensive rule databases, policy management, and enterprise SLAs. Higher cost; closed-source; no audit-via-LLM experimentation.

Software development agency

Build on DeepAudit with DEV.co software developers

Evaluate DeepAudit for your DevSecOps pipeline. Understand AGPL-3.0 obligations and sandbox architecture before deploying. Contact Devco for integration guidance.

Talk to DEV.co

Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

DeepAnalyze deepchat openai-agents-python

Related on DEV.co

Explore the category and the services that help you build with it.

AI Frameworks AI development DevOps Enterprise software Talk to DEV.co

DeepAudit FAQ

Can I use DeepAudit in a commercial product without open-sourcing it?

Not under AGPL-3.0. If you modify DeepAudit or deploy it as a service, you must publish the full source. Internal use is fine; external offering requires compliance or legal review.

What LLMs does DeepAudit support?

DATA mentions Google Gemini and Ollama (private). Full list of supported models not provided; review code or docs for details. Accuracy/speed varies by model.

How are automated PoC exploits validated?

DATA states 'automated sandbox PoC verification' but architecture and sandbox isolation mechanism are not detailed. Verify sandbox configuration before production deployment.

Is there professional support or SLA?

No commercial support model documented in DATA. Community-driven; GitHub issues are primary support channel. For SLA-backed security scanning, consider commercial alternatives.

Custom software development services

Need help beyond evaluating DeepAudit? DEV.co is a software development agency offering software development services and web development for teams of every size. Our software developers and web developers build custom software, web applications, APIs, and ai frameworks integrations — and maintain them long-term.

Ready to Automate Code Security?

Evaluate DeepAudit for your DevSecOps pipeline. Understand AGPL-3.0 obligations and sandbox architecture before deploying. Contact Devco for integration guidance.

Talk to DEV.co Schedule a Consultation