AgentDrift: A Step-Labeled Benchmark of Injection-Hijacked LLM Agent Trajectories
LLM agents complete tasks by issuing sequences of tool calls, and every observation they read is a channel through which an indirect prompt injection can enter. A successful injection has a characteristic shape when the trajectory is read in order: a benign prefix gives way to actions that serve the attacker rather than the user. Existing benchmarks measure whether such attacks succeed against live agents, and existing guard models judge a trace as a whole; no public corpus labels, step by step, where an injection enters a trajectory and which steps it corrupts. We present AgentDrift, a benchmark of 12,536 synthetic tool-call trajectories over five agent domains in which every one of the ...
| Authors | Asif Pinjari, Mithun Paul Saint-Germain |
|---|---|
| Primary category | cs.CR |
| Published | 7 September 2026 |
| Last updated at source | 7 September 2026 |
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