Autonomous LLM Agent Worms: Cross-Platform Propagation, Automated Discovery and Temporal Re-Entry Defense
AuthorsMingming Zha, Xiaofeng Wang
Resources
This paper shows how persistent LLM agents can be turned into self-spreading worms across platforms, and proposes a formal defense to stop them.
Key results
SSCGV discovered 31 injectable persistent carriers across the three anonymized production frameworks.
The evaluation covered three open-source production agent frameworks.
In the tested setup, GPT-4o-mini achieved 100% single-hop compliance.
What the paper found
In this arXiv paper by Mingming Zha and XiaoFeng Wang, the authors analyze a new class of autonomous LLM agent worms in persistent, file-backed agent ecosystems, showing that attacker-controlled text can survive across sessions, re-enter the model’s context through scheduled autoloading, and trigger high-risk actions without any post-injection human interaction. Their core contribution, SSCGV, automatically builds a code property graph from an agent framework’s source code and traces data flow from file I/O to LLM context injection points, discovering 31 injectable persistent carriers across three anonymized production frameworks, while ranking user-prompt carriers as substantially more exploitable than system-prompt carriers. They also introduce SRPO, a three-LLM optimization pipeline that makes worm payloads resilient to summarization, paraphrasing, and compression, addressing semantic degradation in multi-hop agent messaging. In controlled evaluations, the attack achieved zero-click persistence and 3-hop cross-framework propagation across heterogeneous frameworks, with identical success on GPT-4o-mini and Gemini-2.5-Flash at 100 percent single-hop and 100 percent multi-hop compliance in the tested setup. The paper’s key security insight is that in LLM-mediated systems, exposed reads can be more dangerous than writes because reading tainted content contaminates the decision state. To counter this, the authors propose RTW-A, a temporal re-entry defense with RTW enforcement, sealed configuration, typed memory promotion, and capability attenuation, and prove a No Persistent Worm Propagation theorem preventing the write-before-read-before-action chain.
Original abstract
Autonomous LLM agents operate as long-running processes with persistent workspaces, memory files, scheduled task state, and messaging integrations. These features create a new propagation risk: attacker-influenced content can be written into persistent agent state, re-enter the LLM decision context through scheduled autoloading, and drive high-risk actions including configuration changes and cross-agent transmission. We present the first systematic framework for automated analysis of persistent worm propagation in file-backed multi-agent LLM ecosystems. SSCGV, our automated source-code graph analyzer, traces data flow from file I/O to LLM context injection points and ranks carriers by context injection position without manual analysis. SRPO, our summary-resilient payload optimizer, generates worm payloads robust to LLM-mediated summarization and paraphrasing across multi-hop communication. Evaluated on three production agent frameworks, we demonstrate zero-click autonomous propagation, 3-hop cross-platform transmission without platform-specific adaptation, inter-agent privilege escalation, and data exfiltration. We identify two empirical insights: user prompt carriers achieve higher attack compliance than system prompt carriers, and read operations represent the primary integrity threat in LLM-mediated systems. To defend against this class of attacks, we develop RTW-A, proven under a formal No Persistent Worm Propagation theorem. RTW blocks write-before-exposed-read re-entry; sealed configuration protects static files; typed memory promotion prevents untrusted summaries from entering trusted memory; and capability attenuation limits high-risk actions after external reads. These mechanisms eliminate the persistence, re-entry, action chain while preserving ordinary workflows. Affected systems are anonymized pending coordinated disclosure.
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