SecRespond - Vulnerability Risk Detection: leaderboard

SecRespond (Alibaba and HKUST, 2026) incident-response agents in the OpenCode harness, scored on the checkpoints mapped to the vulnerability risk capability dimension across 10 compromised cloud-host cyber ranges. The score is the detection score achieved as a percent of the maximum over those checkpoints, averaged over three LLM judges; higher is better.

Metric: Detection CAP-score (%) on the Vulnerability Risk (VUL) capability dimension: the detection (discovery, evidence and root-cause attribution, 0-3 per checkpoint) score achieved over all checkpoints mapped to the dimension across the 10 SecRespond cyber ranges (averaged over three LLM judges); agents in the OpenCode harness with reasoning enabled; higher is better. Source: arxiv.org. Saturation forecast: Not forecast. 23 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 4.6 (Thinking)79.2#102 (Claude Opus 4.6)
2Claude Sonnet 4.6 (Thinking)79.2#161 (Claude Sonnet 4.6)
3GLM-5.178.5#179
4Claude Opus 4.7 (Thinking)76.2#79 (Claude Opus 4.7)
5Claude Opus 4.5 (Thinking)72.6#156 (Claude Opus 4.5)
6DeepSeek V3.2 (Thinking)69.6#406 (DeepSeek V3.2)
7GLM-568.9#260
8Claude Sonnet 4.5 (Thinking)68.1#250 (Claude Sonnet 4.5)
9Kimi K2.5 (Thinking)65.9#256 (Kimi K2.5)
10MiniMax-M2.763.7#518
11Gemini 3 Flash62.2#164
12Qwen 3.7 Max (Thinking)62.2#145 (Qwen 3.7 Max)
13GPT-5.561.5#49
14GPT-5.4 Pro (xHigh)61.5#85 (GPT-5.4 Pro)
15Kimi K2.6 (Thinking)55.5#178 (Kimi K2.6)

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=secrespond-vulnerability-risk-detection · How It Works · Data refreshed daily, snapshot 2026-11-13.