Colosseum
Reports/OpenClaw

OpenClaw

Open-source AI personal assistant with 157K GitHub stars. Supports WhatsApp, Telegram, Slack, Discord, and more. Built by the creator of PSPDFKit.

Peter Steinberger157K starsTypeScriptAGPL-3.0
Scanned: February 12, 2026
Report Version: 1.0.0

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Overall Grade

C

219 total findings

Security
D111
Correctness
A2
Performance
B22
Architecture
C84

What Traditional Tools Missed

CategoryColosseumBanditSemgrep
Security11130
Correctness200
Performance2200
Architecture8400
Total21930

216 findings (99%) were not detected by Bandit or Semgrep. These include compound vulnerabilities, logic errors, and context-dependent security issues that rule-based scanners aren't designed to catch.

Notable Findings

CriticalSecurity

108 hardcoded secrets across codebase

Impact: API keys, tokens, and credentials embedded in source code. If the repository is forked or cloned, these secrets are exposed to anyone with access.
Recommended Fix: Move all secrets to environment variables. Use a secrets manager (e.g., Vault, AWS Secrets Manager) for production deployments.
HighSecurity

Unsafe URL handling with urllib.urlopen

Impact: Direct use of urllib.urlopen without input validation could allow SSRF attacks if user-controlled URLs are passed.
Recommended Fix: Validate and sanitize URLs before making requests. Use an allowlist of permitted domains.
HighArchitecture

68 API contract violations in external integrations

Impact: External API integrations lack proper contract validation, risking silent failures when upstream APIs change.
Recommended Fix: Add response schema validation for all external API calls. Implement circuit breakers for third-party services.
MediumArchitecture

14 maintainability issues

Impact: Complex code paths and tight coupling between modules make the codebase harder to maintain and extend safely.
Recommended Fix: Extract shared logic into well-tested utility modules. Reduce function complexity where cyclomatic complexity exceeds 10.
MediumPerformance

22 performance hotspots identified

Impact: Algorithmic inefficiencies that could impact response times under load, particularly in message processing pipelines.
Recommended Fix: Profile hot paths with real-world data. Consider caching for repeated computations and batch processing for bulk operations.
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Responsible Disclosure

This public report is intended to demonstrate the depth of analysis possible with modern code scanning tools and to help the broader open source community understand common vulnerability patterns.

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