RIFT-Bench: Dynamic Red-teaming For Agentic AI Systems
Agentic AI systems powered by large language models (LLMs) are rapidly evolving into autonomous decision-making systems, exposing attack vectors beyond those of traditional LLM vulnerabilities. Existing security evaluations are often tied to specific implementations or domains, limiting unified comparison across heterogeneous systems. To address this gap, we introduce RIFT-Bench, a representation-driven methodology for dynamic red-teaming that enables unified evaluations across diverse agentic architectures. Building on a novel hierarchical representation, RIFT-Bench operates in two automated phases: Discovery, which extracts system structure, and Scanning, which executes adaptive adversa...
| Authors | Yarin Yerushalmi Levi, Roy Betser, Amit Giloni et al. |
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| Primary category | cs.AI |
| Published | 22 June 2026 |
| Last updated at source | 30 August 2026 |
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