DFIR ATT&CK Technique Classification (3-Shot): leaderboard
Multi-label MITRE ATT&CK technique classification of cyber-threat-intelligence sentences (Ryan et al., 2026): 2,076 sentences from 83 incident reports of The DFIR Report, 38 percent carrying no technique, labelled against the 211-technique Enterprise taxonomy supplied in context. Three in-context examples without chain of thought at temperature 0, open-weight models run at Q4_K_M 4-bit quantization; micro-F1 in percent, higher is better.
Metric: Micro-F1 (%; multi-label ATT&CK technique prediction for 2,076 sentences from 83 The DFIR Report incident reports, 211-technique label space; three in-context examples, no chain of thought, temperature 0; models run at Q4_K_M 4-bit quantization). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 6 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | DeepSeek-V2.5 [Q4_K_M] | 20 | |
| 2 | gpt-oss-120b [Q4_K_M] | 19 | |
| 3 | gemma-3-27b-it [Q4_K_M] | 17 | |
| 4 | gemma-3-12b-it [Q4_K_M] | 13 | |
| 5 | Llama-3.1-8B-Instruct [Q4_K_M] | 11 | |
| 6 | gpt-oss-20b [Q4_K_M] | 3 |
Interactive version: theaggregate.ai/benchmark?slug=dfir-att-ck-technique-classification-3-shot · How It Works · Data refreshed daily, snapshot 2026-11-12.