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RedTeamLab/Qwen3.6-27B-blueteam-v5
Qwen3.6-27B-blueteam-v5 is a machine learning model from RedTeamLab. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for gguf. The card lists the license as apache-2.0.
Defensive security LLM fine-tuned from Qwen/Qwen3.6-27B using QLoRA on the blueteam-comprehensive-v5 dataset.
Downloads · 30 days
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.gguf30.7 GB · 99%
From the Hugging Face model README
Defensive security LLM fine-tuned from Qwen/Qwen3.6-27B using QLoRA on the blueteam-comprehensive-v5 dataset.
Produces detection queries, investigation chains, remediation guidance, and defensive strategies with concrete tool commands across Splunk, KQL, Kusto, PowerShell, Sigma, YARA, Zeek, and more.
Training: 2,298 records / 256 val, loss 0.208, 2 epochs, A100-40GB (2.5h)
| File | Size | Description |
|---|---|---|
blueteam-v5-Q4_K_M.gguf | 15.4 GB | Main model -- standalone inference |
blueteam-v5-mtp-Q4_K_M.gguf | 1.9 GB | MTP draft head -- for speculative decoding |
llama-server -m blueteam-v5-Q4_K_M.gguf -c 2048 -ngl 30
llama-server -m blueteam-v5-Q4_K_M.gguf --model-draft blueteam-v5-mtp-Q4_K_M.gguf --spec-type draft-mtp -c 2048 -ngl 30
Generated from 714 red-team skills with multi-language detection coverage:
| Category | Languages/Tools |
|---|---|
| SIEM Queries | Splunk SPL, KQL (Azure Sentinel), Kusto |
| Endpoint Detection | PowerShell, Sigma rules, YARA |
| Network Detection | Zeek scripts, Suricata rules, Wireshark filters |
| Cloud Forensics | AWS CloudTrail, Azure Monitor, GCP Audit Log |
| EDR Hunting | Velociraptor artifacts, Wazuh queries |
Phase-based chain classification (see also: recon, exploit, priv esc, persist, post-exploit).