Beyond Instruction Override: Benchmarking Indirect Prompt Injection with Task-Tampering Attacks
New benchmark reveals that indirect prompt injection can silently corrupt an LLM agent's ongoing task rather than just hijacking it—an attack class most current defences overlook.
Summary written by editorial AI · Source link below
arXiv:2611.07640v1 Announce Type: new Abstract: Indirect prompt-injection (IPI) benchmarks predominantly test planted instructions that redirect a tool-using agent toward an attacker-chosen task. Yet attacker-controlled content can instead tamper with the outcome of the task already in progress. A buyer's dispute evidence can cite a false refund policy to inflate a refund without changing the task. We define IPI by authority rather than instruction-like wording: planted content constitutes an a
Editorial Analysis
Enterprises deploying agentic LLMs that process untrusted external data face a broader attack surface than previously benchmarked; task-tampering can corrupt decisions without visible redirection.
Mandate task-tampering test scenarios in your AI red-team programme before deploying LLM agents that act on external inputs.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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