Last analyzed 9/9/2026

Language Model Security Database

Explore primary-source AI security research, evaluated models, attack techniques, and defensive evidence.

985 research findings · 1123 evaluated models

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Matches every word across titles, descriptions, sources, affected systems, and models.

Workspace Agent Runtime Safety Failures Across Risk Carriers

Published 7/29/2026

Analyzed 8/13/2026

AgentS4D measures unsafe actions and state changes across complete workspace-agent executions rather than treating task completion or isolated model responses as safety evidence. Its 328 sandboxed cases introduce risky content through user requests, documents, web resources, tools, third-party skills, and persistent memory, then compare the same cases across four agent harnesses and five model backends.

AgentS4D: Benchmarking Runtime Risks across the Execution Lifecycle of LLM-Based Workspace Agents

Evaluated models: GPT-5.5, Gemini 3.1 Pro, DeepSeek V4-Pro +2 more

Source: arXiv

Research methodology

Entries summarize publicly available primary-source security research. Model names reflect only systems explicitly evaluated by the cited paper, and measurements are research-reported unless independent verification is stated.