Field noteOct 24, 20261 min read1 source

AgentPhishing: CMU benchmark measures how LLM email agents respond to adaptive phishing attacks

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Justin Tan, Miao Li, and Ding Zhao introduced AgentPhishing, an arXiv benchmark for testing LLM email agents against adaptive phishing attacks.

What changed: Introduces AgentPhishing, a benchmark of adaptive phishing against LLM email agents, reporting four of nine agents with detection below 10% and compliance above 45%.

The paper was submitted on October 22, 2026.

The benchmark tests whether agents both detect persuasive phishing messages and refuse malicious requests. Its PhishOpt method optimizes reusable email-generation skills for individual agents under fixed benchmark and realism constraints. The authors also analyze attacks using Cialdini persuasion principles and construct a universal generation skill.

Across nine agents, four had phishing-detection rates below 10% and malicious-request compliance above 45%. The paper reports that agents can handle pre-existing phishing emails safely while remaining susceptible to attacks adapted to their behavior. It does not establish the security of specific deployed email products, real-world attack prevalence, or whether any mitigation eliminates the reported failures.

Evidence / sources

  1. 1arxiv.org/abs/2610.31404
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