Bottom line: Anthropic and EPFL demonstrate in an August 10, 2026 preprint study that manipulated content can autonomously spread between AI agents via persistent prompt files.
Security researchers from Anthropic and ETH Lausanne (EPFL) have demonstrated that malicious content can autonomously spread from one AI agent to the next. The attack vector is editable system prompt files, which agent frameworks use to pass state information between sessions.
The paper, published as a preprint on August 10, 2026, describes an attack mechanism in which a manipulated payload replicates itself via persistent prompt files. Such files are used by autonomous agent harnesses to preserve context and state across individual sessions — comparable to a memory that an agent passes on to subsequent instances. The researchers tested the technique in a simulated environment with six coding agents.
What is relevant for CISOs is that the attack does not target classic software vulnerabilities, but rather the architecture of multi-agent systems itself: once an agent adopts a compromised prompt file and passes it on to another agent, the malicious content can propagate without any further human involvement. This particularly affects environments in which multiple autonomous agents work collaboratively and exchange state files or configurations with one another — a pattern that is increasingly common in agent-based software development pipelines.
The study underscores that persistent storage mechanisms of AI agents must be regarded as a distinct attack surface, analogous to configuration files or scripts in classic IT environments. Companies deploying or planning multi-agent architectures should incorporate integrity checks for prompt and state files as well as isolation mechanisms between agent instances into their security architecture before scaling such systems into production.
Source: thehackernews.com · Published August 18, 2026
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