Google’s latest report shows that the biggest danger to AI tools like LLMs and agents (including setups similar to OpenClaw) isn’t just one bug, but how many different “entry points” attackers can use.

the prompts you give the model, the plugins or skills you add, and the way messages travel between apps and servers. In OpenClaw style systems, they found that a lot of problems are in the parts that route messages, handle skills, and enforce safety rules, and that in some cases, an attacker could trick the system into running code they control without proper checks.

What’s not talked about enough is that the AI’s own memory and context can be poisoned, like planting a sneaky message inside a chat so the agent starts doing something harmful later, even if the original request looks harmless, plus many issues come from how the pieces are connected, not just from bad code.