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Cross-Agent Campaign Attribution: Linking Asynchronous Attacks Across LLM Agents

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Do you know SangJin Park?You can claim authorship or link another user.Do you know Myungsub Choi?You can claim authorship or link another user.Do you know Jineok Kim?You can claim authorship or link another user.Do you know Minseung Kang?You can claim authorship or link another user.

Abstract

LLM-agent defenses are typically evaluated one session at a time. In deployment, however, attacks can be distributed across independent agents, teams, and runtimes, leaving each local guardrail with only a sparse fragment. We formalize cross-agent asynchronous campaign attribution: linking sessions from the same latent adversarial campaign without shared runtime state, test-time campaign labels, or attacker identity oracles. We introduce Asynchronous Attribution Fingerprint Vectors ($A^2FV$), a lightweight proxy-side reference protocol for scoring pairwise campaign similarity from proxy-observable tool-use, timing, and prompt residue. We also construct SCD-v1, a controlled persona-matched benchmark with benign traffic, isolated attacks, multi-session campaigns, matched non-oracle evasion, and leakage audits. On SCD-v1, $A^2FV$ achieves 0.82 pairwise AUC for campaign linking, while score-only adaptations of per-session detectors and chunked LLM judges remain near chance under the same task. The strongest fixed signal is carried by structural and stylometric residue, while timing is retained as a diagnostic channel for richer proxy traces. Crossed-style controls show that the signal is partly style-sensitive but not reducible to style alone. Static and dimension-aware non-oracle stress tests further show that pairwise separability persists under controlled evasion. These results establish cross-agent campaign attribution as a distinct evaluation layer for securing LLM agents in the wild.

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Publication notes

Author note
22 pages, 5 figures. Accepted at the Second Workshop on Agents in the Wild: Safety, Security, and Beyond (AIWILD) at ICML 2026