pentestagent and pentagi
Both are autonomous AI agent frameworks for penetration testing, but they compete as alternative approaches to automating black-box security assessments—you would select one based on its specific architecture, capabilities, and integration requirements rather than use them together.
About pentestagent
GH05TCREW/pentestagent
PentestAgent is an AI agent framework for black-box security testing, supporting bug bounty, red-team, and penetration testing workflows.
Built on LiteLLM for multi-model LLM support, PentestAgent features a hierarchical agent architecture where instances can spawn isolated child agents via stdio transport (`spawn_mcp_agent`), enabling parallel task delegation without external orchestration. It integrates MCP (Model Context Protocol) servers with automatic RAG-based tool optimization for large tool sets, includes prebuilt attack playbooks for structured assessments, and offers Docker isolation with both minimal and Kali Linux images containing pentesting tools like metasploit and sqlmap.
About pentagi
vxcontrol/pentagi
✨ Fully autonomous AI Agents system capable of performing complex penetration testing tasks
Leverages a multi-agent architecture with specialized AI teams for research, exploitation, and infrastructure tasks, powered by Neo4j knowledge graphs and integration with 10+ LLM providers. Operates in isolated Docker containers with built-in tools (nmap, metasploit, sqlmap) and external search APIs, storing all findings in PostgreSQL with vector embeddings for intelligent memory and context retrieval. Provides REST/GraphQL APIs, real-time Grafana/Prometheus monitoring, and comprehensive vulnerability reporting—designed as a self-hosted, horizontally scalable microservices platform.
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