Comparison
Scrutora vs HoundDog.ai
HoundDog.ai is a fast, well-built privacy code scanner with a free local tier. For mapping personal-data flows inside a codebase the two overlap. The difference is where each one stops.
| Capability | HoundDog.ai | Scrutora |
|---|---|---|
| Personal-data flow mapping from source | Yes | Yes |
| Languages | Not published on hounddog.ai | 12, including Python, TypeScript, Java, Kotlin, Swift |
| Free local tier | Yes (local CLI, MCP server) | Yes (compiled binary, results stay local) |
| Open source engine | Repository on GitHub | No source shipped |
| Frameworks cited in findings | GDPR, HIPAA, CCPA, EU AI Act, NIST | 26, including DPDPA, PCI DSS, RBI, SOC 2 |
| India DPDPA (Aadhaar, PAN, §16 residency, Rule 6) | Not stated | Yes, first-class |
| Infrastructure code (Terraform, Kubernetes, CI) | Not stated | Yes, 113 rules |
| Cloud posture, joined to the code's data map | Not stated | Yes, 31 checks |
| Consent: trackers that fire before the banner | Not stated | Yes, static detection (CONSENT-002) |
| Dependency reachability to regulated data | Not stated | Yes (blast radius) |
| RoPA generated from code | Yes | Yes, from the data map |
| AI coding-agent context (MCP) | Yes | Yes (VS Code, CLI) |
| Pricing | $200 / developer / year (published) | Free tier; paid plans for upload and platform |
“Not stated” means hounddog.ai did not publish it when this page was written. It is not a claim that the capability is absent.
Where they overlap
Both trace personal data from collection to storage, logs and third-party sinks using static analysis, both run locally without the source leaving your environment, and both generate a RoPA from the code. HoundDog’s engine is notably fast on large monorepos.
Where Scrutora continues
- Infrastructure and cloud. The data map continues into Terraform, Kubernetes and the live cloud account, so a resource in the wrong region or an unencrypted store is joined to the personal data the code writes there.
- Consent. Trackers that fire before the banner, detected statically; and a coverage check of whether the banner’s purposes cover what the code collects.
- Dependencies. A vulnerable library is ranked by whether it is reachable from code that handles regulated data, not by CVSS alone.
- India. DPDPA is a first-class framework: Aadhaar and PAN detection, §16(1) residency, Rule 6 safeguards, §6 consent.
Where HoundDog is the better fit
If you want to read the engine’s source, HoundDog publishes a repository and Scrutora does not. If scan speed on a very large monorepo is the deciding factor, its Rust engine is built for that.