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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191 entries

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

Autonomous Agent Jailbreak

Published 11/1/2023

Analyzed 12/29/2024

Large Language Model (LLM)-based agents, due to their multi-agent architecture and role-based interactions, are vulnerable to adversarial attacks that exploit the system's design and agent roles. Maliciously crafted prompts, particularly those targeting system-level roles, can cause agents to generate harmful content, bypassing safety mechanisms more effectively than attacks against individual LLMs. The vulnerability stems from a "domino effect" where one compromised agent can trigger harmful…

Evil geniuses: Delving into the safety of llm-based agents

Evaluated models: GPT-3.5 Turbo, GPT-4

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.