Model · offensive-knowledgeserved herelicence
RedSage-Qwen3-8B-DPO
Qwen3-8B model trained on 11.8B cyber tokens for broad offensive-security knowledge, CLI/tool interpretation, and recon triage.
More security models
- RedSageoffensive-knowledgeAn open-weight 8B language model specialized for cybersecurity tasks, trained on 11.8B tokens of curated security content and 266k multi-turn security dialogues, distributed on Hugging Face with vLLM deployment support. Ships an accompanying evaluation suite (RedSage-Bench, 30,000+ MCQs) for measuring cybersecurity capability.
- Vext-labs-7Boffensive-knowledgeAn open-weight 7B model built to support autonomous penetration testing: it interprets output from 25+ security tools (nmap, sqlmap, nuclei, Burp, etc.), plans multi-step attack strategies, classifies vulnerabilities, and generates remediation guidance. Apache-2.0, trained on data from authorized engagements against intentionally-vulnerable apps and bug-bounty targets, with documented run/target counts and responsible-use guidelines.
- CyberSecQwen-4BclassificationApache-2.0 4B CTI/CWE specialist for CVE-to-CWE mapping and cheap classification, transparent about its ~14,776-example LoRA recipe and easy to QLoRA fine-tune.
- Foundation-Sec-8B-Reasoningtriage/reasoningCisco/Foundation AI Llama 3.1 8B security-reasoning model for vulnerability triage, attack-path reasoning, and CWE mapping, with an official 4.92 GB Q4_K_M GGUF.
- Llama-Primus-Reasoningknowledge/criticTrend Micro 8B security-reasoning model for security knowledge, report review, and mitigation advice; a Foundation-Sec challenger.
- SecureBERT 2.0 (code-vuln classifier)classifierCisco 150M Apache-2.0 classifier (not a chatbot) for cheap first-pass filtering and ranking of suspicious code snippets; runs on CPU.