HoundDog.ai is a privacy code scanner designed to automate data mapping and detect PII leaks early in the software development lifecycle, particularly for AI applications. It helps enforce privacy rules, discover AI integrations, and prevent risky code from reaching production.
Key Features:
- AI Governance & Shadow AI Discovery: Identifies AI models, SDKs, and agents directly in the codebase, providing visibility into sanctioned and unsanctioned AI usage.
- Sensitive Data Tracing: Tracks over 100 sensitive data types (PII, PHI, CHD, auth tokens) across code paths to detect exposure in LLM prompts and other risky mediums.
- Prompt Governance: Enforces allowlists for LLM prompts, blocking unapproved data types in PRs and CI workflows.
- Data Mapping and Privacy Assessments: Automatically maps data flows in code, generating audit-ready RoPAs, PIAs, and DPA risk flags.
- IDE Plugins: Highlights PII leaks as code is being written (VS Code, Cursor, IntelliJ, and Eclipse).
- Managed Scans: Offloads scanning to HoundDog.ai with direct source control integrations.
- CI/CD Integrations: Integrates with CI/CD pipelines to automatically push CI configurations and embed the scanner for pre-merge checks.
Use Cases:
- Shift-Left Sensitive Data Protection: Prevent sensitive data overlogging early in development.
- Shift-Left Privacy Compliance Automation: Enable evidence-based data mapping at development speed.
- Privacy by Design for AI Applications: Discover AI integrations, detect sensitive data in prompts, and block unapproved data types in code before anything reaches production.
