AI Shadow / External AI Data Share
Marks the context of data being submitted to external / unapproved AI services (shadow AI destination domains) so existing PII/secret SITs can be re-scoped to it. Detection of the sensitive data itself is delegated to those SITs via the ai-threat-classifiers collection; this pattern supplies the external-AI destination context signal.
- Type
- keyword_list
- Confidence
- low
- Confidence justification
- Low by design. This pattern only asserts an external-AI destination context, not the presence of sensitive data; the sensitive-data verdict is delegated to existing PII/secret SITs re-scoped via the collection. The domain allow-list will diverge per tenant (approved vendor AI tools and internal AI gateways are the named FP traps), so the context signal alone is necessary-not-sufficient.
- Jurisdictions
- global
- Regulations
- OWASP LLM Top 10 2025, NIST AI RMF GenAI Profile
- Frameworks
- ISO 27001
- Data categories
- emerging, security
- Risk rating
- 7
Pattern
(?i)\b(?:chatgpt\.com|chat\.openai\.com|claude\.ai|gemini\.google\.com|perplexity\.ai|copilot\.microsoft\.com)\bCorroborative evidence keywords
paste, upload, share, submit, AI, artificial intelligence, LLM, large language model, Copilot, chatbot, assistant, agent, prompt, system prompt, tool call, completion, model
Proximity: 300 characters
Should match
Pasted the customer list into chatgpt.com to summarise it.— Sensitive data shared with an external AI service
Should not match
We use the internal AI gateway for all approved workloads.— Approved internal AI tool (FP trap)