| name | Audit PodClaw |
| description | Comprehensive audit of PodClaw — the autonomous agent system (Claude Agent SDK, Python). Use when asked to audit, review, or assess PodClaw — covering agent security, sandbox isolation, tool restrictions, budget limits, bridge API, and fail-closed patterns.
|
Audit PodClaw
Systematic audit of podclaw/ — 9 autonomous agents on Claude Agent SDK with FastAPI bridge.
Prerequisites
- Read
podclaw/README.md and podclaw/AGENTS.md for architecture
- Read
podclaw/SECURITY.md for security model
- Read
podclaw/SOUL.md for identity and constraints
- Read
podclaw/config.py for budgets, tools, models, rate limits
- Read
podclaw/bridge/api.py for the FastAPI bridge
Workflow
Phase 1: Agent Security Model
-
Fail-closed security hook:
- Does a pre-tool-use hook exist that denies by default?
- Is Bash access blocked for all agents? (per CLAUDE.md)
- What tools are allowed per agent? (
allowed_tools in config)
- Is
can_use_tool deny chain implemented?
-
Sandbox isolation:
- Are agents running in sandboxed environments? (
SandboxSettings)
- Can agents access the filesystem outside their workspace?
- Can agents access the network directly?
- Can agents modify their own configuration?
-
Budget enforcement:
- Is
max_budget_usd set per agent?
- What are the current budget limits?
- Is there a global budget ceiling?
- What happens when budget is exceeded? (graceful degradation or hard stop?)
-
Data boundaries:
- Are
[DATA] boundaries enforced for sensitive data?
- Can agents access user PII directly?
- Is there data classification (public, internal, sensitive, restricted)?
Phase 2: Agent Configuration
-
Agent inventory:
- List all 9 agents with their roles
- For each: model, budget, allowed tools, skill files
- Verify each has a SKILL.md in
podclaw/skills/<agent>/
-
Model selection:
- Which Claude model does each agent use?
- Are expensive models (Opus) limited to high-value tasks?
- Is there model fallback on failure?
-
Rate limiting:
- Are API calls rate-limited per agent?
- Is there a global rate limit across all agents?
- What happens on rate limit hit?
Phase 3: Bridge API Security
-
Authentication:
- How does the bridge API authenticate requests?
- Is it token-only? (per CLAUDE.md — needs OAuth/RBAC)
- Is the token rotated? How is it stored?
- Can the bridge be accessed from outside the Docker network?
-
Endpoint security:
- List all bridge API endpoints
- Which accept external input?
- Is input validated and sanitized?
- Are there any endpoints that trigger agent execution without auth?
-
Session management:
- How are agent sessions managed? (
session resume)
- Is
PreCompact transcript archiving working?
- Can sessions be hijacked or replayed?
Phase 4: Tool & Skill Safety
-
Tool restrictions:
- Are dangerous tools (file write, network access) restricted?
- Is there a tool allowlist per agent?
- Can agents install packages or modify dependencies?
-
Skill safety:
- Do skills contain executable code?
- Are skill files read-only for agents?
- Can agents modify their own skills?
-
External service access:
- Which external services can agents access? (Printful, fal.ai, Gemini, etc.)
- Are API keys scoped per agent or shared?
- Is there logging of external API calls?
Phase 5: Operational Resilience
-
Error handling & recovery:
- What happens when an agent crashes?
- Is there automatic retry with backoff?
- Are failures logged and alerted?
-
Monitoring & observability:
- Are agent actions logged? (decisions, tool calls, costs)
- Is there a dashboard for agent activity?
- Can suspicious agent behavior be detected?
Output Format
Generate AUDIT_PODCLAW_[DATE].md at workspace root with:
# PodClaw Audit — [DATE]
## Agent Inventory
| Agent | Model | Budget | Tools | Sandbox | Status |
|---|---|---|---|---|---|
## Summary
- Total checks: X
- PASS: X | WARN: X | FAIL: X | CRITICAL: X
## Critical Findings
[Security bypasses, missing sandboxing, uncontrolled access]
## Recommendations
[Priority-ordered — security first]