The threat extends beyond accidental errors. When AI writes the software, the attack surface shifts: an adversary who can poison training data or compromise the model’s API can inject subtle vulnerabilities into every system that AI touches. These are not hypothetical risks. Supply chain attacks are already among the most damaging in cybersecurity, and AI-generated code creates a new supply chain at a scale that did not previously exist. Traditional code review cannot reliably detect deliberately subtle vulnerabilities, and a determined adversary can study the test suite and plant bugs specifically designed to evade it. A formal specification is the defense: it defines what “correct” means independently of the AI that produced the code. When something breaks, you know exactly which assumption failed, and so does the auditor.
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c0 2c - assigned value for TLS_ECDHE_ECDSA_WITH_AES_256_GCM_SHA384
→ compiler₃: + type inference
Adobe 在 PS 25 周年的时候，还推出过一个图片真假小测验的网站，感兴趣的朋友可以去看看，当时的技术只能是纯 PS，就已经能做到有些图片难以辨别，更不用说现在强大的 AI。