Provenance Tagging
An architectural measure in the field of agent security that records the source, modification history, and trust level of data as it enters an agent's processing pipeline. This allows the model to assign different weights to different sources during inference and reduces the probability that untrusted content is mistakenly executed as instructions.
Timeline (last 90 days)
The core idea of provenance labels is to record the source, modification history, and trust level of data when it enters the Agent processing pipeline, so as to distinguish data of different trust levels.
At the implementation level, provenance labels are easily lost due to text concatenation, summarization, or format conversion, and attackers can forge labels or exploit the Agent's confusion between system messages and user content to inject instructions.
Key unsolved problems in the Agent security field include: how provenance labels are propagated in multi-Agent collaboration, whether labels can remain intact when external model APIs are used, and whether detection of the lethal trifecta can be automated.
All Facts (3)
The core idea of provenance labels is to record the source, modification history, and trust level of data when it enters the Agent processing pipeline, so as to distinguish data of different trust levels.
50%UnverifiedAt the implementation level, provenance labels are easily lost due to text concatenation, summarization, or format conversion, and attackers can forge labels or exploit the Agent's confusion between system messages and user content to inject instructions.
50%UnverifiedKey unsolved problems in the Agent security field include: how provenance labels are propagated in multi-Agent collaboration, whether labels can remain intact when external model APIs are used, and whether detection of the lethal trifecta can be automated.
50%