AI Didn’t Just Speed Up Development. It Changed the Attack Surface.
Most modern dev workflows now rely on AI in some form:
code generation, dependency updates, CI/CD automation, and even remediation bots.
But here’s the uncomfortable truth: Our security assumptions didn’t evolve at the same pace.
In 2025, some of the most impactful applications and supply-chain attacks didn’t use zero-days or clever exploits. Instead, they:
- Abused trusted open-source packages
- Executed inside legitimate CI/CD pipelines
- Hid in build artifacts and cached outputs
- Blended into AI-generated code that “looked fine” in review
Once inside, automation did the rest.
That’s the shift: AI is no longer just a productivity layer; it’s a core execution layer.And when execution runs at machine speed, traditional AppSec signals (CVEs, severity scores, static scans) start to break down.
We’ve just published a deep-dive report analyzing:
- How AI changed the economics of supply-chain attacks
- Why trust and automation became primary attack surfaces
- How persistence moved from access → build outputs → artifacts
- What this means for developers and DevSecOps teams heading into 2026
If you build software in an AI-first world, this is worth understanding.
