Menu

Post image 1
Post image 2
Post image 3
Post image 4
Post image 5
Post image 6
Post image 7
Post image 8
Post image 9
1 / 9
0

Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale

Microsoft Research·Brenda Potts·about 1 month ago
#BTPQ2Sqv
Reading 0:00
15s threshold

At a glance Some risks appear only when agents interact, not when tested alone. Actions that seem harmless can cascade causing a chain reaction across an agent network. In our tests, a single malicious message passed from agent to agent, extracting private data at each step and pulling uninvolved agents into the chain. We saw early signs that some agent networks become more resistant to these attacks, but defenses are still an open challenge being worked on. Agents belonging to different users and organizations are beginning to interact with each other. These networks of agents are emerging as advances in large language models (LLMs) and silicon lower barriers to building agents, while tools like Claude, Copilot, and ChatGPT, along with existing platforms such as email and GitHub, bring them into constant contact. As a result, agents are no longer working in isolation but becoming participants in a shared, interconnected environment.…

Continue reading — create a free account

Join HashtagPLUS to read full articles, follow hashtags, vote, and join the conversation.

Read More