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Whitepaper
The Model That Wrote Your Code Can’t Secure It
A practitioner framework for governing AI-driven risk across the software development lifecycle, and why architectural independence is the only defense that holds.
u003cspan data-contrast=u0022noneu0022u003eAI coding tools accelerate development. They also introduce vulnerabilities at scale, hallucinate security findings, and cannot audit the supply chains they’re embedded in. Asking an LLM to certify the safety of its own code is asking the student to grade their own exam.u003c/spanu003eu003cspan data-ccp-props=u0022{u0026quot;335559739u0026quot;:160}u0022u003e u003c/spanu003ernrnu003cspan data-contrast=u0022noneu0022u003eThis paper explains why, and what to do about it.u003c/spanu003e
Why LLMs cannot govern their own security, and why future better models won’t fix it
The four control points in the AI development lifecycle where independent governance must be applied
Independent vulnerability detection test: Checkmarx AI-Augmented SAST vs. Claude Opus 4.7
A hybrid deterministic-plus-AI architecture that provides ground truth no LLM can fabricate or bypass
A five-dimension governance framework for assessing and closing your current posture gaps
Market u0026 Technology Leadership
40%
of Fortune 100
1800+
Customers in 70 countries
75+
Languages u0026 100+ frameworks
7X
Leader at Gartner® Magic Quadrant™ for Application Security Testing
Industry Recognition
