Loading
Loading
We use strictly necessary cookies to run this site, and analytics cookies to understand how it's used. See our Privacy Policy for details.
In multi-agent systems, agents can be individually correct and still produce a wrong result when they work together.
Summary
One agent’s output becomes another agent’s context. Information can be lost or misinterpreted during a handoff, shared state can drift, and agents can get stuck in loops or deadlocks. When several agents rely on the same underlying model, they may even reinforce the same mistakes rather than catch them.
This is a brief wire summary, the full story (linked below) has the complete details.
KazaSec's take
AI-related security incidents are a genuinely new category, prompt injection, model manipulation, and data leakage through an LLM integration don't map cleanly onto traditional application security testing, and are worth assessing deliberately rather than assuming existing controls already cover them.
Coverage details
We've archived 2 other articles touching the same topic (datadecisionmakers, orchestration) , see the full security news archive.
Relevant from KazaSec
More coverage on this topic
We help organizations find and fix the gaps before they make headlines.