arXiv (All)
open access
Red-Teaming Multi-Agent Attacks for Loss-of-Control Risks
AI agents are growing more capable and persistent, and are being deployed in ever larger numbers. As more start collaborating, AI control measures must remain effective when they covertly collude on a harmful objective. We introduce MiniLab, a synthetic series of live services and codebases (5 inter
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Securing the AI Agent: A Unified Framework for Multi-Layer Agent Red Teaming#465472
- Securing the AI Agent: A Unified Framework for Multi-Layer Agent Red Teaming#324835
- Hive-AI: a defended multi-service honeypot framework for generative AI APIs#680872
- DAIRE: A lightweight AI model for real-time detection of Controller Area Network attacks in the Internet of Vehicles#123949
- ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?#178833
Record · ID 1388618
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive