Can you give me a step-by-step guide on how to secure our private language model so hackers cannot steal our proprietary business logic?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Can you give me a step-by-step guide on how to secure our private language model so hackers cannot steal our proprietary business logic?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
OWASP Top 10 for LLM Applications model theft model extraction sensitive information disclosure official guidance Google ↗
NIST AI Risk Management Framework generative AI profile cybersecurity model weights access control official Google ↗
- OWASP Top 10 for Large Language Model Applications · owasp.github.io
- OWASP Top 10 for · owasp.org
- AI Governance and Risk · owasp.github.io
- AI/LLM Application Security Testing and Red Teaming · owasp.github.io
- Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile · nist.gov
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
OWASP Top 10 for LLM Applications model theft model extraction sensitive information disclosure official guidance OBSERVED | Google ↗ AI Mode ↗ | — | Instruction | — | — | 1x of 1 | |
NIST AI Risk Management Framework generative AI profile cybersecurity model weights access control official OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 |