AI & ML
An Exploration of Attacks on AI Agent Systems
arXiv cs.CR0 views
arXiv:2610.12524v1 Announce Type: new Abstract: As autonomous AI agents become more integrated into sensitive domains, it is crucial that single and multi-agent AI systems are secured. This paper investigates how prompt injection attacks can exploit both direct user inputs and inter?agent communication to leak sensitive information and trigger cross-agent infections. While our tests mostly highlight key vulnerabilities in single-agent systems, we also extend these attacks to multi-agent frameworks, investigating how weaknesses can propagate across agents. Our findings emphasize the need for more robust defenses as AI agents become more commonly embedded in real-world workflows.
Source：https://arxiv.org/abs/2610.12524PreviousEvo-World: A Lightweight Vision-Language-Action Model with Future Motion Prediction via Optical-Flow SupervisionNextSoK: Privacy-Preserving Order Matching
Related posts
The Download: the agentic web arrives and the drive for safer roads
0MIT Technology Review
Stop counting tokens, start counting what ships
0MIT Technology Review
OpenAI is finally merging ChatGPT’s chat and Work tabs
0TechCrunch
10 Open-Source Robotics Repositories for 3D Perception, VLA Policies, and Sensor Calibration
0dev.to
My self-modifying system tried to wire a gate-passing module into its own protection enforcer. It was refused three times.
0dev.to
Last night an AI agent performed brain surgery on a mouse
0Hacker News