Agent/MCP Audit Sprint

Public AI agent scan radar

AI Agent Security Radar

A no-execution snapshot of popular public AI agent repos across browser automation, coding agents, multi-agent frameworks, graph runtimes, code-execution agents, and MCP-backed tool surfaces. Scores are heuristic triage signals, not confirmed vulnerabilities, certification, endorsement, or commissioned audit results.

Sample8 public AI agent repos
Method90 selected public text files per repo via GitHub API
SafetyNo clone, dependency install, target execution, or live-service calls
HandoffUSD $1,000 human audit for one agent, repo, or slice

How to read this

Use the score to prioritize review, not to claim a bug

The scanner fetched public GitHub metadata and selected text blobs on June 20, 2026 Asia/Shanghai time. It looked for agent/tool surfaces, remote listeners, write actions, credential paths, auth gates, redaction, tests, and CI.

A lower score means the selected files produced more review signals. It can still miss controls outside the fetched slice, so paid work starts with fresh scope confirmation and evidence review.

Browser agents need review for authenticated sessions, clicks, downloads, page content, and JavaScript execution.
Coding agents and code-execution agents need sandbox, filesystem, network, token, and patch/write boundaries reviewed.
Multi-agent frameworks need memory, tool routing, human approval, remote runtime, and tenant boundary tests.

Radar snapshot

Popular public AI agent repos with review signals

Convert a signal

When to use the paid audit

  1. You ship an AI agent that can browse, write files, execute code, call cloud APIs, use memory, or mutate workspace data.
  2. The free scan points to write actions, credential paths, remote listeners, missing redaction evidence, or weak test visibility.
  3. You need human validation, source-specific evidence, a ranked fix plan, and launch notes.
  4. Payment starts only after written scope acceptance; the fixed quote is USD $1,000.