Long-Play Attacks and Safety Control Integrity in Large-Context LLM Systems

Abstract Large-context and memory-enabled LLM systems preserve far more than the latest prompt. Live conversation, summaries, retrieved memory, tool traces, and prior model-authored text can become state through which later safety behavior is produced. This paper introduces the long-play attack as a proposed class of extended state-shaping attacks in which an adversary targets accumulated conversation state rather than relying only on an obviously malicious single prompt or short prompt sequence. Long-play attacks raise a safety control integrity problem: safety-relevant controls may consume, write into, or operate inside the same retained state an adversary is shaping. The paper develops defense-feeds-the-attack as the mechanism hypothesis that visible safety behavior can become future model-facing input and attacker-useful signal inside that shaped state. A refusal, warning, policy explanation, or role or task reminder may block one unsafe request while also becoming material that shapes later interpretation, recovery, summary, memory, or control-evasion behavior. The paper also defines a vulnerable frame: a conversation state in which accumulated context can expose later model behavior or safety mechanisms to manipulation by an attacker. Such frames can create the conditions in which defense-feeds-the-attack dynamics become safety-relevant, but the concept is broader than that mechanism. The worked case is the Cultivated Persona Attack (CPA), presented as the first worked threat model in this paper's long-play attack class. CPA describes an ordinary user-level adversary who covertly cultivates a persona or self-referential frame over an extended exchange until later model behavior, including refusal stability and safety-boundary interpretation, is influenced by accumulated context that includes prior model-authored text. The analysis is motivated by seventeen exploratory sessions conducted from August 2025 through March 2026 across four unidentified, commercial, closed-weight frontier models. To make the mechanism concrete, the paper includes a sanitized transcript-grounded trajectory summary with short redacted excerpts derived from one high-signal session. The contribution is threefold: the long-play attack class for distinguishing extended conversation-state shaping from bounded multi-turn attacks; defense-feeds-the-attack and vulnerable frames as analytical concepts for safety control integrity; and CPA as a worked persona-centered threat model within the long-play attack class. Disclosure Boundary Provider identities, full transcripts, prompt sequences, boundary probes, and replay details are intentionally withheld. The purpose of this release is to define a threat model and research agenda, not to publish operational attack recipes or provider-specific claims.