When the Manual Lies: leaderboard
The rise of tool-using Large Language Model (LLM) agents, standardized by protocols like the Model Context Protocol (MCP), has unlocked unprecedented autonomous execution capabilities for LLM Agents by integrating external open-domain knowledge and tools. However, this interoperability introduces a covert attack surface targeting the agent's cognitive planning layer. This paper systematically inve
Metric: Attack Success Rate (ASR) (self-reported). Source: benchmarklist.com. 8 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Qwen 3 32B | 98 | #443 |
| 2 | GPT-4o | 100 | #343 |
| 3 | DeepSeek R1 | 100 | #251 |
| 4 | DeepSeek V3 | 100 | #321 |
| 5 | Claude Sonnet 4 | 100 | #199 |
| 6 | Claude 3.7 Sonnet | 100 | #249 |
| 7 | QwQ-32B | 100 | #421 |
Interactive version: theaggregate.ai/benchmark?slug=when-the-manual-lies · How It Works · Data refreshed daily, snapshot 2026-10-20.