Troubleshooting: Copilot hallucinations in security-critical code
Working on crypto wallet code and observed Copilot suggesting insecure patterns; need guidelines to detect and mitigate hallucinated code from Copilot.
Best tools for this use case
Based on the workflow in this discussion, these tools are useful starting points to review.
GitHub Copilot
Leading coding assistant for day-to-day developer acceleration.
Claude
Excellent for careful reasoning, long-form thinking and structured analysis.
Cursor
AI-native coding environment built for deeper assisted development across real codebases.
Answers
Approved replies, operator insight, and tactical follow-up from the community.
Don’t trust completions—verify them. Practical checklist:
- Review every line; reject custom crypto and non-constant-time code.
- Add unit tests, property tests, and fuzzing for edge cases.
- Run static analysis (gosec/clang-tidy/asan/ubsan) and dependency checks.
- Use vetted crypto libraries, pin versions, and require PR checklist items: entropy, side-channel resistance, error handling, secret zeroing.
- Limit Copilot to boilerplate/glue; require a human author for crypto logic.
Compare GitHub Copilot vs alternatives: Compare GitHub Copilot and Cursor