#66th of 7 in Code review and testing
deepsec
Agent-driven vulnerability scanner for reviewing all code in large existing repos
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- Stars
- 8.2k
- License
- Apache-2.0
- Last commit
- Sep 2026
- Language
- TypeScript
Missed the latest GitHub check; these facts may be older.
Vercel is hiring: 90 open roles
Overview
deepsec runs regex matchers to find candidate sites in a repository, then has AI coding agents investigate each one and emit findings with recommendations. State lives in a `.deepsec/` folder, runs resume after interruption, and large repos can fan out across Vercel Sandbox microVMs. It supports a PR-mode diff review, revalidation of past findings, and export to JSON or markdown.
Who it is for: Security and platform engineers auditing large codebases for vulnerabilities
Strengths
- Interrupted runs resume and skip files already analyzed
- Free regex scan stage before paid AI review; `process --diff` limits review to changed files
- Spend and time caps via `--max-cost-usd` and `--max-duration`
- Bring your own OpenAI or Anthropic key, or use Vercel AI Gateway
Weaknesses
- README warns full scans of large codebases can cost thousands to tens of thousands of dollars
- Runs like a coding agent with full shell access; prompt injection from dependencies is a stated risk
- Distributed execution depends on Vercel Sandbox
- No tagged release; installed via npx
What it needs
- no GPU
- Needs Node.js, pnpm, Vercel AI Gateway or OpenAI/Anthropic API key, Vercel Sandbox (optional)
- Models: OpenAI, Anthropic, Vercel AI Gateway, custom HTTPS provider
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| 1 | open-code-reviewCLI that reviews Git diffs with an LLM agent and line-level comments | 78 out of 100 |
| 2 | no-mistakesLocal git proxy that runs AI review, tests and lint before opening a PR | 72 out of 100 |
| 3 | pr-agentLLM pull request reviewer that comments via /review, /describe and /improve | 67 out of 100 |
| #4 | front-end-checklistFront-end rules checklist with an MCP server for agent code review | 64 out of 100 |
| #5 | e2eAI-driven end-to-end testing framework for web and mobile apps | 62 out of 100 |