NeuroSploitv2 is an AI-powered penetration testing framework that automates critical aspects of offensive security operations through advanced language models.
The framework, available on GitHub, integrates with multiple LLM providers, including Claude, GPT, Gemini, and Ollama, to enable specialized vulnerability analysis and exploitation strategies.
The framework stands out for its modular architecture, which features specialized AI agent roles designed for specific security tasks.
These agents include bug bounty hunters for web application vulnerability discovery and red team operators for simulated attack campaigns. Malware analysts for threat analysis, and blue team specialists for defensive operations.
Each agent role operates with tailored parameters and tool access controls, enabling controlled and ethical security operations.
NeuroSploitv2 uses advanced methods to reduce false outputs, which is important when using LLMs for security work.
The framework employs grounding techniques, self-reflection mechanisms, and consistency checks to ensure LLM-generated security assessments remain grounded in reality.
Configurable safeguards add extra safety, including keyword filtering and content checks. The framework’s extensibility distinguishes it from previous penetration testing tools.
| Feature | Description |
|---|---|
| Multi-LLM Support | Integrates Claude, GPT, Gemini, and Ollama with flexible provider selection |
| AI Agent Roles | Pre-configured personas including Red Team, Bug Bounty Hunter, Malware Analyst, Blue Team, and OWASP/CWE Experts |
| Hallucination Mitigation | Implements grounding, self-reflection, and consistency checks to reduce LLM errors |
| Granular LLM Profiles | Customizable temperature, token limits, context levels, and caching per agent |
| Tool Integration | Supports Nmap, Metasploit, Subfinder, Nuclei, SQLMap, Burpsuite, and Hydra |
| Safety Guardrails | Keyword filtering, content validation, and ethical adherence controls |
| Interactive Mode | Conversational CLI interface for direct agent control and execution |
| Structured Reporting | JSON campaign results and HTML reports for workflow integration |
| Markdown Prompts | Dynamic prompt templates for context-aware agent instructions |
| Extensibility | Custom agent roles and tools easily added via JSON configuration |
Users can integrate external security utilities such as Nmap, Metasploit, Subfinder, Nuclei, and SQLMap via a straightforward JSON configuration.
Granular LLM profiles allow security teams to customize parameters, including temperature settings, token limits, context levels, and caching behavior for each agent role.
According to the GitHub advisory, NeuroSploitv2 is designed with operational flexibility, allowing organizations to run the framework via command-line interfaces for automated scanning or use interactive mode for conversational testing.
The framework generates structured JSON results and human-readable HTML reports, facilitating integration into existing security workflows.
The open-source MIT-licensed project represents a significant shift toward AI-augmented offensive security.
However, security professionals should recognize that LLM-generated penetration testing requires careful validation and experienced oversight.
The framework is designed to augment human expertise rather than replace it, with ethical considerations and operational security built into its core architecture.
Development continues with regular updates to agent capabilities and tool integrations, positioning NeuroSploitv2 as an evolving solution for contemporary penetration testing challenges.
