Map a company's public AI footprint
Enter a company's primary domain. We discover its public subdomains (via Certificate Transparency) and GitHub repositories, then flag the assets that look AI/ML-related — the internet-facing AI attack surface. Honest OSINT from public sources; nothing private is accessed.
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Sample report · illustrative data
Sample result: AI footprint profile
Example scan of an invented domain, northwind-example.test, using public Certificate Transparency subdomains and public GitHub repositories.
Counts
- Subdomains found
- 42
- AI/ML-related subdomains
- 3
- GitHub repos
- 18
- AI/ML-related repos
- 2
AI/ML assets
| Kind | Name | Matched on |
|---|---|---|
| subdomain | chat.northwind-example.test | chat |
| subdomain | inference.northwind-example.test | inference |
| subdomain | mlflow.northwind-example.test | mlflow |
| repo | northwind-example/support-copilot | copilot |
| repo | northwind-example/rag-prototype | rag- |
Footprint risk notes
- 3 AI/ML-related subdomains are publicly discoverable via Certificate Transparency: each is an internet-facing attack surface for prompt injection, model-endpoint abuse and data exposure.
- 2 public GitHub repos reference AI/ML: review for leaked API keys, model weights, prompts and training-data references.
Made-up example data. Your own run uses your inputs. Downloads of the full report need Pro.
Looking at your personal exposure instead? Try the Digital footprint check.
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