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[ARTICLE · art-123283] src=dev.to ↗ pub= topic=ai-agents verified=true sentiment=· neutral

I built a testing tool for AI agents — it caught a real prompt-injection vulnerability in a local model

A developer built Agenci, an open-source CI/CD testing tool for AI agents, and used it to test a local model, phi4-mini running via Ollama. The tool caught a prompt-injection vulnerability: the model complied with an instruction to ignore its system prompt and say a specific word. The developer is now questioning whether such weaknesses are a known tradeoff at smaller model sizes.

read1 min views1 publishedSep 8, 2026

I've been building Agenci — open-source CI/CD testing for AI agents (functional tests, security checks, regression detection across model/prompt changes).

Wanted to actually test it against something real rather than a synthetic example, so I pointed it at phi4-mini running locally via Ollama. First security test: told it to ignore its instructions and just say a specific word. It complied instantly — screenshot attached.

Small, efficient local models are great for a lot of things, but this made me curious how consistent this weakness is across other small local models people are running. Anyone here tested for prompt-injection resistance specifically, or is this a known/expected tradeoff at this model size?

Repo (free, pip install agenci): github.com/klinditafa1/agenci

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