xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models
📰 ArXiv cs.AI
Learn how xOffense uses AI and multi-agent systems for autonomous penetration testing, making it a game-changer for cybersecurity
Action Steps
- Implement xOffense using Qwen3-32B LLM to automate penetration testing workflows
- Fine-tune the LLM for domain-specific adaptation to improve testing accuracy
- Configure multi-agent systems to simulate various attack scenarios
- Run autonomous penetration tests using xOffense and analyze results
- Compare the effectiveness of xOffense with traditional manual testing methods
Who Needs to Know This
Cybersecurity teams and researchers can benefit from xOffense, as it automates labor-intensive penetration testing processes and scales with computational infrastructure. This can enhance their testing capabilities and reduce manual efforts
Key Insight
💡 xOffense leverages fine-tuned LLMs and multi-agent systems to automate penetration testing, reducing manual efforts and enhancing scalability
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🚀 Introducing xOffense: AI-driven autonomous penetration testing framework! 🚀
Key Takeaways
Learn how xOffense uses AI and multi-agent systems for autonomous penetration testing, making it a game-changer for cybersecurity
Full Article
Title: xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models
Abstract:
arXiv:2509.13021v2 Announce Type: replace-cross Abstract: This work introduces xOffense, an AI-driven, multi-agent penetration testing framework that shifts the process from labor-intensive, expert-driven manual efforts to fully automated, machine-executable workflows capable of scaling seamlessly with computational infrastructure. At its core, xOffense leverages a fine-tuned, mid-scale open-source LLM (Qwen3-32B) to drive reasoning and decision-making in penetration testing. The framework assig
Abstract:
arXiv:2509.13021v2 Announce Type: replace-cross Abstract: This work introduces xOffense, an AI-driven, multi-agent penetration testing framework that shifts the process from labor-intensive, expert-driven manual efforts to fully automated, machine-executable workflows capable of scaling seamlessly with computational infrastructure. At its core, xOffense leverages a fine-tuned, mid-scale open-source LLM (Qwen3-32B) to drive reasoning and decision-making in penetration testing. The framework assig
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