ai-code-review

To scan for prompt injection and PII leakage, run Whitney on your repository to generate findings, then review the structured JSON output for severity, file paths, and remediation guidance to fix AI security flaws.

Detecting hardcoded keys and unguarded agents requires an automated AI-security scan of your repository prompts and config files, which identifies misconfigurations and provides actionable remediation steps with severity tagging.

Yes, you can apply AI security code reviews across languages and codebases in both startup and enterprise environments during security audits to identify misconfigurations, credential leakage, and unguarded agents.

PII detection scans your repository prompts and config files to identify exposed sensitive information, delivering actionable remediation steps and prioritized fixes with severity tagging for software teams.

Yes, AI code review can load Whitney findings in JSON format using the --json flag, providing structured data including severity, checks, file paths, and remediation guidance for pipeline integration.

AI security scans apply across languages and codebases to detect prompt injection and hardcoded keys, but require generated Whitney findings to provide structured remediation guidance for your specific environment.