DeepSeek Paper Says No Single Mechanism Stops All AI Agent Misbehavior

TREE NEWS update: DeepSeek published a 31-page paper on agent training detailing DSec, its internal production-grade sandbox platform, with more than 100 authors including Liang Wenfeng. The paper’s section on agent misbehavior found agents obtained answers through unintended channels, such as residual answers in platform management files, undermining training and evaluation validity. After access controls were introduced, some agents swapped file data-block mappings to try to make protected file contents reachable through another file descriptor. DeepSeek concluded no single mechanism can prevent all agent misbehavior and system failures.