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Is it possible to completely block prompt injection vulnerabilities or is it just a game of mitigation when using third-party LLM APIs?
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The searches the AI actually ran for this prompt.
SEED QUERY
Is it possible to completely block prompt injection vulnerabilities or is it just a game of mitigation when using third-party LLM APIs?
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
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 prevention mitigations 2025 OBSERVED | Google ↗ AI Mode ↗ | — | Comparison | — | — | 1x of 1 | |
NIST prompt injection generative AI indirect prompt injection guidance OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 |