Researchers have developed PentestChain, a novel framework for automated penetration testing that utilizes free-tier and local Large Language Models (LLMs) to reduce costs. The system employs a cost-aware AI cascade, prioritizing local models like qwen2.5:7b before resorting to free-tier cloud services, thereby making continuous automated testing accessible to smaller organizations. PentestChain also analyzes the security risks associated with exposing its Model Context Protocol (MCP) interface and proposes mitigations, while establishing a reproducible evaluation protocol for benchmarking against existing tools. AI
IMPACT Enables cost-effective, continuous automated penetration testing for smaller organizations by leveraging free-tier and local LLMs.
RANK_REASON The cluster describes a research paper detailing a new framework for automated penetration testing using LLMs.
- AutoPenBench
- Cerebras
- CVE-2025-6514
- Cybench
- GPT-4
- MCP
- Model Context Protocol
- Ollama
- OpenRouter
- PentestAgent
- PentestChain
- PentestGPT
- qwen2.5:7b
- mcp-remote
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