Abstract
The transition from stateless generative models in artificial intelligence to stateful, autonomous agents represents an architectural evolution. While providing capabilities for long-term planning and automation of enterprise workflows, it also introduces a new form of security threat, the Chronos Vulnerability.
The Chronos Vulnerability signifies the threat of memory-based attacks, including the Memory Injection Attack (MINJA) and the sleeper agent scenario, where the internal belief system of the autonomous agent is compromised, effectively decoupling the attack vector from the eventual catastrophic event.
This study formalizes the threat model for persistence-based attacks and the threat of Dynamics Blindness in the context of the World of Workflows benchmark, demonstrating that traditional endpoint content filters are inadequate for the current stateful architecture.
Consequently, this study synthesizes a defense-in-depth landscape, categorizing emerging frameworks such as diagnostic trajectory guardrails (AgentDoG), formal temporal verification (Agent-C), immunological memory consensus (A-MemGuard), and hardware-anchored trust via GPU-based Trusted Execution Environments (TEEs) and Zero-Trust memory architectures.
Blogger's Review: This research highlights new security challenges for intelligent agents, particularly in the context of memory attacks. As AI systems become increasingly complex, traditional security measures fall short, necessitating the adoption of more advanced defense frameworks to combat future threats.