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Sleeper Channels and Provenance Gates: Persistent Prompt Injection in Always-on Autonomous AI Agents

topic: current_projecttop score: 100released: 2026-05-14first surfaced: 2026-05-14arXivPDFthreats2026-05-14

Authors: Narek Maloyan, Dmitry Namiot

arXiv · PDF

Summary

arXiv:2605. 13471v1 Announce Type: new Abstract: Always-on AI agents (OpenClaw, Hermes Agent) run as a single persistent process under the owner's identity, folding messaging, memory, self-authored skills, scheduling, and shell into one authority boundary.

Relevance

Read next because Sleeper Channels and Provenance Gates: Persistent Prompt Injection in Always-on Autonomous AI Agents overlaps with clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", clean result "Only continuous soft prefixes hit both EM axes at once on Qwen-2.5-7B-Instruct: discrete prompt searches split between the alignment objective and the distributional objective, and both discretizations of the soft prefix collapse (MODERATE confidence)", clean result "Training one persona to emit a [ZLT] marker without bystanders adopting it has a one-cell-wide LR x epochs window on Qwen2.5-7B-Instruct (LOW confidence)". Matching terms: class, under, eval, source, fires, rate, prompt, test. Source: arxiv cs.CR (Cryptography and Security).

Threat model

Potential threat/caveat for clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)": this item discusses evaluation.

Abstract

arXiv:2605.13471v1 Announce Type: new Abstract: Always-on AI agents (OpenClaw, Hermes Agent) run as a single persistent process under the owner's identity, folding messaging, memory, self-authored skills, scheduling, and shell into one authority boundary. This configuration opens what we call \emph{sleeper channels}: an untrusted input to one surface persists as a memory, skill, scheduled job, or filesystem patch, then fires later through a different surface with no attacker present. Two independent axes define the class: persistence substrate and firing-separation. We walk a confused-deputy cron attack end-to-end through OpenClaw at a pinned commit. The defense is tiered (D1, D2, D3), and D2 carries a soundness theorem against seven named deployment invariants. D2 keys on a canonical action-instance digest with one-shot owner attestations, defeating paraphrase laundering, multi-input grant reuse, and replay. A companion artifact ships the gate, a static audit over the vendored source, and a runtime adapter realising five of the ten mediation hooks (H1, H2, H3, H6, H9) around the cron path (42 tests, Node~$\geq{}20$, at \href{https://github.com/maloyan/sleeper-channels}{github.com/maloyan/sleeper-channels}). Empirical evaluation is preregistered as follow-on.