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כתבה arXiv cs.AI ·

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

תקציר מקורי באנגליתarXiv:2607.18826v1 Announce Type: cross 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, mul
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