AI-Generated Code: Who Is Responsible for the Bugs?
summary
Claims that 46% of new GitHub repos are AI-assisted and that AI code shortens review cycles drive the argument: automated checks must run on every PR with SCA and SAST and enforce quality gates. Demo uses GitHub Copilot and Claude Opus 4.6 to generate a Python task manager, then SonarCloud finds 15 open issues with 14 blockers, surfaces SQL injection and dependency risks, and shows fixes. Recommendation is to treat AI code as untrusted input, add SonarCloud AI Code Assurance detects AI-generated code and block PRs failing the security baseline.
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chapters (12)
- 0:00Introduction
- 1:21AI-Assisted Coding: Who Owns the Bugs?
- 2:48GitHub Stats: Rise of AI Code Repositories
- 3:49Faster PR Cycles Create Review Bias
- 5:05The Security Paradox of AI-Generated Code
- 6:14Hidden Vulnerabilities Beneath the Surface
- 7:13Removing Trust Bias in AI Code Reviews
- 8:11Creating a Gold-Standard Security Baseline
- 9:02Automating Checks with Shift-Left Security
- 10:41Treat AI Code as Untrusted Input
- 11:31DevSecOps Workflow for AI-Generated Code
- 15:19Demo: Scanning AI Code with SonarQube Cloud
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