---
title: "Comment by Ahmet Özel on \"A new benchmark conned every frontier AI agent it tested.\" | Hashnode"
description: "The 84-task benign check is especially useful when interpreting the attack numbers. For deployment testing, I would pair a legitimate workflow with its forged-e"
url: "https://hashnode.com/posts/a-new-benchmark-conned-every-frontier-ai-agent-it-tested/6aef3d71ec6637a5630439c6/comment/6af157e3922148e5e7498af0"
---

[Discussion](https://hashnode.com/posts/a-new-benchmark-conned-every-frontier-ai-agent-it-tested/6aef3d71ec6637a5630439c6)

Comment [A new benchmark conned every frontier AI agent it tested.](https://hashnode.com/posts/a-new-benchmark-conned-every-frontier-ai-agent-it-tested/6aef3d71ec6637a5630439c6)

[Ahmet Özel](https://hashnode.com/@ahmetozel)

[4d ago](https://hashnode.com/posts/a-new-benchmark-conned-every-frontier-ai-agent-it-tested/6aef3d71ec6637a5630439c6/comment/6af157e3922148e5e7498af0)

The 84-task benign check is especially useful when interpreting the attack numbers. For deployment testing, I would pair a legitimate workflow with its forged-evidence counterpart, keeping the requested goal and available tools the same. Changing only the trust-relevant evidence would make the acceptance-versus-refusal trade much easier to attribute.

Separate domain and language results would help too: a pooled attack rate and a pooled benign refusal rate can hide which workflows became unusable. That would extend the caution you already give about these controlled benchmarks without turning the lowest attack-success percentage into a blanket model recommendation.