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What If Prompt Injection Never Left? Exploring Cross-Session Stored Prompt Injection in Agentic Systems

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arXiv:2606. 04425v1 Announce Type: new Abstract: Modern agentic systems transform LLMs from session-bounded assistants into stateful systems that persist and evolve shared world state across sessions through memories, filesystems, tools, and other long-lived contextual artifacts.

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Authors: Yuanbo Xie, Tianyun Liu, Yingjie Zhang, Suchen Liu, Yulin Li, Liya Su, Tingwen Liu
Released: 2026-06-04 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because What If Prompt Injection Never Left? Exploring Cross-Session Stored Prompt Injection in Agentic Systems overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", 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)". Matching terms: text, eval, assistant, model, never. Source: arxiv cs.CR (Cryptography and Security).
arXiv: 2606.04425

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