Sinewave Agent Security Scanner vs PentAGI

Detailed side-by-side comparison to help you choose the right tool

Sinewave Agent Security Scanner

🔴Developer

security

An open-source, MIT-licensed security scanner — "npm audit for AI agents and MCP servers" — that audits code, MCP tools, prompts, skills, and AI-suggested dependencies over MCP or CLI.

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Custom

PentAGI

🔴Developer

security

Self-hosted, autonomous AI penetration-testing platform that runs security tests in an isolated Docker sandbox using a team of specialized agents.

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Starting Price

Custom

Feature Comparison

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FeatureSinewave Agent Security ScannerPentAGI
Categorysecuritysecurity
Pricing Plans6 tiers214 tiers
Starting Price
Key Features
    • Autonomous exploitation with monitoring
    • Specialized agent delegation
    • Sandboxed pro toolset

    Sinewave Agent Security Scanner - Pros & Cons

    Pros

    • MIT-licensed and fully open source — no vendor gating on higher-value features
    • MCP-first design lets the coding agent scan its own output without a human in the loop
    • Purpose-built for agent-specific failure modes: prompt injection, hallucinated packages, tool spoofing
    • Claimed 97.7% benchmark precision, with 120 auto-fix templates to close the loop from detection to remediation
    • Lightweight @prooflayer variant is a viable pre-commit or CI check when the full scanner is too heavy

    Cons

    • Precision claim (97.7%) is self-reported on the vendor's own benchmark, not an independent evaluation
    • Full scanner requires Python plus the AST toolchain — heavier install than a pure JS pre-commit hook
    • Auto-fixes are template-based; complex vulnerabilities may need human review after the rewrite
    • Rule coverage is language-broad but you should still verify depth for your specific stack
    • MCP server auditing scores are only as good as the point-in-time snapshot — a compliant server can still rug-pull on a later run

    PentAGI - Pros & Cons

    Pros

    • 20+ pro security tools plus multi-agent delegation, all sandboxed — significant setup work you don't have to do
    • Deep observability (Langfuse + Grafana + Jaeger + Loki) is rare in security tooling and makes agent behavior debuggable
    • 10+ LLM providers plus custom endpoints means you can run fully offline with Ollama or cheap via OpenRouter

    Cons

    • Autonomous exploitation is dangerous without security expertise — not a beginner tool
    • Self-hosted only; no managed SaaS option
    • Overlap with breach-and-attack-simulation products may mislead buyers — PentAGI is investigative, not scenario-based

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