CodeQL 2.26.0 Adds AI Prompt-Injection Detection With Regression Testing Guide

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GitHub released CodeQL 2.26.0 on July 10, 2026, introducing built-in detection for AI prompt-injection vulnerabilities. The update enables static analysis to trace data-flow paths from untrusted sources to AI model sinks within codebases. Developers are advised to build structured regression fixtures — including positive and negative test cases — to ensure the detection remains effective across future upgrades. Uploading SARIF results alone is insufficient; a proper regression gate must compare expected rule IDs and file locations to catch disappearing or newly appearing alerts. The recommended approach pins the CodeQL CLI version and supplements static analysis with runtime adversarial tests, since custom wrappers or unsupported SDKs may not be fully modeled.

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