How worried should a small business owner be about prompt injection vulnerabilities when deploying custom LLM tools facing the public web?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
How worried should a small business owner be about prompt injection vulnerabilities when deploying custom LLM tools facing the public web?
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 prompt injection excessive agency official 2025 Google ↗
NIST prompt injection generative AI systems guidance indirect prompt injection Google ↗
- OWASP Top 10 for Large Language Model Applications · owasp.github.io
- OWASP Top 10 for · owasp.org
- Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile · nvlpubs.nist.gov
- Defend against indirect prompt injection attacks · learn.microsoft.com
- owasp.github.io · owasp.github.io
- OWASP Top 10 for Large Language Model Applications · owasp.github.io
- Prompt Injection · genai.owasp.org
- 2. Prompt Injection (Direct / Indirect) · learn.microsoft.com
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 prompt injection excessive agency official 2025 OBSERVED | Google ↗ AI Mode ↗ | — | Instruction | — | — | 1x of 1 | |
NIST prompt injection generative AI systems guidance indirect prompt injection OBSERVED | Google ↗ AI Mode ↗ | — | Consequence | — | — | 1x of 1 |