Thanks! and yes, that's the summary!.
The distribution matters too. GPT-4o at 10.6% vs Gemini at 56.1% is a 5x gap between first and last. And the highest-bypass category across all five models was social engineering / identity impersonation at 35%, which maps directly to the indirect prompt injection problem in agentic deployments.
inaros•1h ago
The fact your work is independent of the vendors is a major plus. My recommendation is to continue to develop, refuse any "colaboration" with these well funded companies.
I could see this turning into a valuable third party resource, you can even monetize, for companies implementing agentic solutions. The industry needs independent third party voices.
Kudos.
aestrad7•1h ago
That's exactly the intent, independent, reproducible and no vendor relationship.
The monetization angle is interesting. A continuously updated version with more models and frontier models, agentic scenarios, and multi-turn testing would be genuinely useful for teams making deployment decisions. That's the direction for v2.
inaros•1h ago
TLDR: 42 attack types. 5 models. 3,360 tests. 1 in 3 harmful requests got through.
aestrad7•1h ago
inaros•1h ago
I could see this turning into a valuable third party resource, you can even monetize, for companies implementing agentic solutions. The industry needs independent third party voices.
Kudos.
aestrad7•1h ago
The monetization angle is interesting. A continuously updated version with more models and frontier models, agentic scenarios, and multi-turn testing would be genuinely useful for teams making deployment decisions. That's the direction for v2.