security-audit

To run a security audit on your repository, use an AI-driven tool that scans for exposed secrets, gitignore gaps, and configuration weaknesses. It evaluates vulnerabilities, filters false positives, and generates a detailed remediation report.

AI-driven PII detection scans repository files using a Python-based scanner to identify personally identifiable information. The AI model triages the findings to assess severity, filter false positives, and suggest remediation steps for compliance.

Yes, you can customize the security audit scope to target specific areas like secrets, pre-commit configurations, gitignore issues, constitutional compliance, or run a full audit across all dimensions.

Yes, Python is required to run the PII scanner and other security auditing tools. The AI-driven audit relies on Python scripts to identify vulnerabilities, evaluate compliance, and generate the final report.

The best way to check for prompt-injection surfaces is using an LLM-powered security audit. It comprehensively scans for configuration weaknesses and prompt-injection surfaces, utilizing AI to triage severity and suggest remediation.

An LLM-powered security audit relies on Python and AI triage to filter false positives, but limitations include potential missed vulnerabilities in complex configurations and the need for manual review of constitutional compliance findings.