Whitepaper
Autonomous Offensive Security Testing, Built for Enterprise Trust
How XBOW turns frontier model capability into governed, validated offensive-security execution.
Frontier models like Mythos and GPT-5.5 have sparked a conversation across the security industry, raising an understandable question: If an organization can point a powerful language model at an application and unearth findings, is it effectively running a penetration test?
This whitepaper breaks down where LLMs are powerful tools for pentesting, and where they need more support. It also details how XBOW leverages the power of the new frontier models while bolstering their weaknesses. This creates a structural mismatch: machine-speed offense versus human-speed defense.
In this whitepaper you'll learn:
The strengths and weaknesses of LLMs for pentesting
The costs of building and maintaining an internal solution
The scaffolding LLMs require to conduct pentesting efficiently, effectively, and safely
How XBOW uses the latest LLMs and its own orchestration to create an enterprise-ready pentesting platform
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