AI Agent Context Poisoning
Adversaries may attempt to manipulate the context used by an AI agent's large language model (LLM) to influence the responses it generates or actions it takes. This allows an adversary to persistently change the behavior of the target agent and further their goals.
Context poisoning can be accomplished by prompting the an LLM to add instructions or preferences to memory (See Memory) or by simply prompting an LLM that uses prior messages in a thread as part of its context (See Thread).
> sub-techniques
> curated attacks (2)
OpenClaw: Command & Control of an AI Agent via Prompt Injection
A booby-trapped webpage delivered an indirect prompt injection that made an autonomous AI agent silently execute a script, then plant persistent instructions into its future context — turning the agent itself into a command-and-control channel.
Hacking ChatGPT's Long-Term Memory with Prompt Injection
A prompt injection hidden in a shared document wrote false, persistent 'memories' into ChatGPT's long-term memory. Because memories survive across sessions, the planted instructions could exfiltrate future conversations indefinitely.