PentesterFlow, an open-source terminal-based AI assistant for authorized security assessments, has gained 301 GitHub stars and 33 forks since launching around May 31, 2026. Built with TypeScript and Node.js, the tool provides a human-in-the-loop agentic workflow for penetration testing, featuring built-in playbooks for common vulnerability classes and integration with Burp Suite, the industry-standard web security testing platform.
Built-in Security Methodology With Evidence-Based Findings
PentesterFlow includes specialized "skills" (playbooks) for common vulnerability classes including IDOR (Insecure Direct Object Reference), SSRF (Server-Side Request Forgery), SSTI (Server-Side Template Injection), JWT vulnerabilities, GraphQL security issues, race conditions, and additional web application vulnerabilities. The system emphasizes reproducible exploitation with actual request/response proof rather than hallucinated security issues, addressing a major concern with AI security tools that generate false positives.
The tool functions as a CLI that guides penetration testers through reconnaissance, enumeration, validation, and reporting workflows while maintaining analyst control. It requires human approval for sensitive actions to prevent accidental damage or unauthorized access, reflecting its design for authorized security assessments only.
Multi-Platform Support With Local and Cloud LLM Options
PentesterFlow supports macOS (ARM64/x64), Linux (ARM64/x64), and Windows (x64) platforms, with binaries compiled using Bun runtime. The modular architecture supports multiple LLM providers including Ollama for local deployment, LM Studio, OpenAI-compatible APIs, Kimi, Groq, Gemini, and custom endpoints. This flexibility allows security teams to choose between local models for sensitive assessments or cloud-based models for performance.
The tool executes shell commands under controlled conditions, makes HTTP requests for web application testing, processes captured network traffic, and documents findings with evidence. A companion Burp Suite integration tool bridges the industry-standard platform with the CLI for traffic import and finding export, enabling seamless workflow integration with existing security testing infrastructure.
Operational Memory Learns From Penetration Testing Sessions
A key differentiator is PentesterFlow's operational memory system, which learns from sessions automatically by storing successful techniques and lessons in local knowledge bases without requiring model retraining. This allows the tool to improve over time based on actual penetration testing experience, building an organization-specific knowledge base of effective techniques and vulnerabilities found in previous assessments.
With 39 commits on the main branch and active development under the Apache 2.0 license, the project shows steady progress. The open-source license makes it accessible for both individual security researchers and enterprise security teams conducting authorized assessments.
Key Takeaways
- PentesterFlow has gained 301 GitHub stars and 33 forks since launching in late May 2026
- Built-in playbooks cover IDOR, SSRF, SSTI, JWT, GraphQL vulnerabilities, and race conditions with evidence-based exploitation
- Supports local and cloud LLM providers including Ollama, LM Studio, OpenAI-compatible APIs, and custom endpoints
- Operational memory system stores successful techniques in local knowledge bases without requiring model retraining
- Burp Suite integration bridges the industry-standard web security platform with the CLI for seamless workflow integration