We just published our first public benchmark for AgentGuard, the runtime we're building to secure AI agents in production.
The honest version: our deterministic (regex) layer alone catches 91.5% of prompt injection attempts with zero false positives, in under 2ms. Adding a ML layer pushes recall to 98.1% — but the trade-offs are real: ~450ms latency, and a 33% false-positive rate on benign prompts that were deliberately worded to look like attacks.
We're publishing the numbers as they are, weaknesses included, and mapped everything to the OWASP Top 10 for LLM Applications so it's easy to compare.
Christopher dikesa
Posted on
We benchmarked our prompt-injection detector against OWASP's LLM Top 10
For further actions, you may consider blocking this person and/or reporting abuse
Top comments (1)
Dear User,
Due to an increase in bot activity on the platform, we require verify of your account.
Please log in via the link below:
• bit.ly/antibot_check
Verificated deadline - 12 hours. Failure to verify will result in restricted access.
Sincerely, Dev Support