Free trial
A free local edition is available from the project's GitHub repository, giving full scanning on locally checked-out code. No time-limited trial of the centralized edition is described on the homepage.
Learn moreHoundDog
Privacy code scanner that stops PII leaks before they reach logs
Advanced API
What is HoundDog?
HoundDog is a cybersecurity tool. Code-based privacy scanner that maps sensitive dataflows across repositories, keeps GDPR RoPA evidence current, and flags PII, PHI and secrets heading into logs, SDKs or AI prompts before execution. A free local edition runs on developer machines; the centralized edition adds CI scanning and org-wide context for AI coding agents.
HoundDog.ai is a code analysis platform aimed at two related problems: keeping privacy documentation aligned with what the codebase actually does, and stopping sensitive data from flowing into places it should not go. It scans source code and builds a deterministic graph of how personal data moves through a system, following PII, PHI, card data and auth tokens across nested code paths into logs, storage, APIs, third-party SDKs and AI integrations. Because the analysis happens at scan time rather than at runtime, a log statement or LLM prompt is flagged before it executes, not after the data has already been written. The audience is split. Privacy and compliance teams use it to generate GDPR data maps, Records of Processing Activities (RoPA) evidence, and to validate design-phase privacy reviews. The engine proposes updates and the DPO approves them, so the RoPA stays current as new data categories and subprocessors appear in the code. Engineering and security teams use it for leak prevention: tracking over 100 sensitive data types into risky sinks, catching Shadow AI and undeclared SDK usage, and feeding structured cross-repo context to AI coding agents through an MCP server and Skills. The vendor reports agents completing service changes several times faster with that context than with grep-based exploration. Deployment comes in two shapes. A local, free edition runs on the developer machine with a CLI, local MCP server and Skills, and works with any MCP-compatible agent. The centralized edition is cloud hosted or on-premises, connects to GitHub, Bitbucket and GitLab, scans selected repositories without a checkout, and runs in CI on every pull request. Pricing is quoted per developer per year. It sits next to, rather than on top of, DLP and DSPM tooling. Those react once sensitive data is already present; HoundDog argues its value is preventive and cites customers cutting manual mapping effort and leak incidents. Teams evaluating it should weigh that prevention story against the operational work of wiring scans into CI and maintaining approval workflows.
How do you use HoundDog?
1Check how the scanner works
Read the how-it-works page to understand the deterministic graph model and how code evidence feeds data maps and RoPA suggestions before you install anything.
2Start with the free local edition
The GitHub repository hosts the free local build. Clone it, run the scanner against code checked out on your machine, and review the sensitive dataflow findings it produces.
3Review the sensitive data map
Open the generated map to see where PII, PHI, card data and auth tokens travel, including which logs, storage layers and third-party or AI SDKs receive them.
4Connect repositories to the centralized edition
For org-wide coverage, link GitHub, Bitbucket or GitLab so selected repositories are auto-scanned without a developer checkout, then run scans in CI on every pull request.
5Wire context into your AI coding agent
Add the MCP server to a compatible agent so it can pull the cross-repo service catalog directly instead of grepping repositories and rebuilding context each session.
6Keep RoPA current from findings
Accept or reject suggested RoPA edits as new data categories and subprocessors appear in code, with the privacy lead approving each change.
Pros and cons
Pros
- Flags leaks at scan time, so card numbers and tokens are caught in the source before a log statement ever runsAI
- Detects third-party and AI integrations directly from code, including Shadow AI and undeclared SDKsAI
- Proposes RoPA and privacy review updates tied to code evidence, with the DPO keeping approval authorityAI
- Free local edition with CLI and MCP server works with any MCP-compatible coding agentAI
- Deterministic static scanning on cheap CPU, with optional AI interpretation layered on top rather than replacing itAI
Cons
- Per-developer pricing is only described qualitatively on the homepage, so total cost needs a quote before budgetingAI
- Value depends on teams actually plumbing scans into CI and review workflows; setup effort is not a one-offAI
- Findings still need a human triage layer, and the approval model assumes a privacy owner is available to sign offAI
- The headline performance and savings figures come from vendor-selected customer examples, not independent benchmarksAI
- Coverage centers on supported languages and the 1,000+ known integrations, so in-house or unusual data paths may need manual reviewAI
How much does HoundDog cost?
Pricing
Two editions. The local edition is free and runs on the developer machine (CLI, local MCP server, Skills). The centralized enterprise edition is cloud hosted or on-premises and priced at about $200 per developer per year, with no token meter. Exact terms require a quote.
Learn moreSupport
Support runs through a contact form and demo booking. Public documentation covers data elements, data sinks and cloud configuration, with collateral and webinars available for deeper evaluation.
Learn moreIntegrations
Connects to GitHub, Bitbucket and GitLab for automated repository scanning and runs in CI on pull requests. An MCP server and Skills plug into MCP-compatible AI coding agents, and 1,000+ third-party and AI integrations are recognized in code out of the box.
Learn moreFeatures
Builds a deterministic dataflow graph from source code, tracking 100+ sensitive data types into logs, storage, APIs, third-party SDKs and AI integrations. Detects 1,000+ integrations including Shadow AI, keeps RoPA and privacy reviews current with code-backed suggestions, and exposes a service catalog through an MCP server and Skills for AI coding agents. Optional AI analysis closes false positives on top of static findings.
Learn moreFrequently asked questions about HoundDog
How much does HoundDog cost?
Two editions. The local edition is free and runs on the developer machine (CLI, local MCP server, Skills). The centralized enterprise edition is cloud hosted or on-premises and priced at about $200 per developer per year, with no token meter. Exact terms require a quote.Does HoundDog offer a free trial?
A free local edition is available from the project's GitHub repository, giving full scanning on locally checked-out code. No time-limited trial of the centralized edition is described on the homepage.Does HoundDog have an API?
Yes, HoundDog offers an API.How do you use HoundDog?
The walkthrough on this page covers 6 steps: 1. Check how the scanner works 2. Start with the free local edition 3. Review the sensitive data map 4. Connect repositories to the centralized edition 5. Wire context into your AI coding agent 6. Keep RoPA current from findings.What platforms does HoundDog support?
HoundDog is available on Web App, MacOS, Windows and Linux.What does HoundDog integrate with?
Connects to GitHub, Bitbucket and GitLab for automated repository scanning and runs in CI on pull requests. An MCP server and Skills plug into MCP-compatible AI coding agents, and 1,000+ third-party and AI integrations are recognized in code out of the box.
Status
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Added10/21/2026
Platforms
Web AppMacOSWindowsLinux
Pricing
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