--- title: RavenX-Sec-8B-GGUF canonical_url: "https://www.modelscope.ai/models/Deadbydawn101/RavenX-Sec-8B-GGUF" md_url: "https://www.modelscope.ai/models/Deadbydawn101/RavenX-Sec-8B-GGUF.md" repository: Deadbydawn101/RavenX-Sec-8B-GGUF last_updated: 2026-06-29 license: apache-2.0 pipeline_tag: text-generation tasks: - text-generation base_model: - georgehenney/Qwen3-8B-heretic base_model_relation: quantized library_name: - gguf - pytorch frameworks: - pytorch language: - en downloads: 264 stars: 0 tags: - security - cybersecurity - pentest - CVSS - OWASP - red-team - bug-bounty - 128k-context - gguf - qwen3 - ravenx - rath-protocol - tool-calling --- # RavenX-Sec-8B-GGUF > RavenX-Sec-8B-GGUF - An open-source model by Deadbydawn101 on ModelScope. RavenX-Sec Qwen3-8B v4.0 — Autonomous Security Intelligence Model 128K (GGUF) Deadbydawn101/RavenX-Sec-8B-GGUF is a text-generation model on ModelScope. licensed under apache-2.0. derived from georgehenney/Qwen3-8B-heretic. - **Repository**: Deadbydawn101/RavenX-Sec-8B-GGUF - **License**: apache-2.0 - **Tasks**: text-generation - **Base model**: georgehenney/Qwen3-8B-heretic - **Tags**: security, cybersecurity, pentest, CVSS, OWASP, red-team, bug-bounty, 128k-context, gguf, qwen3, ravenx, rath-protocol, tool-calling - **Downloads**: 264 - **Stars**: 0 - **Last updated**: 2026-06-29 Source: https://www.modelscope.ai/models/Deadbydawn101/RavenX-Sec-8B-GGUF --- # RavenX-Sec Qwen3-8B v4.0 — Autonomous Security Intelligence Model 128K (GGUF) > **GGUF** · Ollama / llama.cpp / LM Studio · 128K context · 6-step RATH protocol · 610K training examples · 21 datasets This is the GGUF version of [`RavenX-Sec-8B-Security-RATH-128k-mlx-4bit`](https://huggingface.co/deadbydawn101/RavenX-Sec-8B-Security-RATH-128k-mlx-4bit) — the model **self-evolved** from 4 to 6 RATH steps during training. > 🍎 **Looking for the MLX version?** → [RavenX-Sec-8B-Security-RATH-128k-mlx-4bit](https://huggingface.co/deadbydawn101/RavenX-Sec-8B-Security-RATH-128k-mlx-4bit) **Built by [@DeadByDawn101](https://github.com/DeadByDawn101) (RavenX LLC)** ## Quick Start ```bash ollama run hf.co/deadbydawn101/RavenX-Sec-8B-GGUF:ravenx-sec-v4.0-128k-Q8_0 ``` ## Available Quantizations ### v4.0-128k (Latest — Recommended) | Filename | Quant | Size | |----------|-------|------| | `ravenx-sec-v4.0-128k-Q4_K_M.gguf` | Q4_K_M | 4.7 GB | | `ravenx-sec-v4.0-128k-Q5_K_M.gguf` | Q5_K_M | 5.4 GB | | `ravenx-sec-v4.0-128k-Q8_0.gguf` | Q8_0 | 8.1 GB | | `ravenx-sec-v4.0-128k-f16.gguf` | F16 | 15.3 GB | ### Previous Versions v3.0-128k, v3.0, v2.0 also available in this repo. ## Related Models | Model | Format | Link | |-------|--------|------| | RavenX-Sec v4.0 MLX 4-bit | MLX Safetensors | [MLX version](https://huggingface.co/deadbydawn101/RavenX-Sec-8B-Security-RATH-128k-mlx-4bit) | | **RavenX-Sec v4.0 GGUF** | GGUF | This repo | ## What This Is A fine-tuned Qwen3-8B specialized for the complete vulnerability lifecycle: **find → classify → fix → verify → report → prevent**. Trained on 610,220 examples from 21 security-specific datasets with 8192 sequence length (zero truncation). Extended to 128K context via YaRN rope scaling. The model **self-evolved** from a 4-step to a **6-step RATH protocol** during training: | Step | What It Does | |------|-------------| | **R — Risk / Identify** | Finding context, affected systems, exposure | | **A — Assessment** | CVSS score + vector, CWE, scope, ground truth | | **T — Threat** | Attacker objectives, attack vectors, likelihood | | **H — Highlight / Remediate** | Immediate action, recommended fix, workaround, verification | | **D — Document** | Severity, weakness classification, steps, SLA | | **P — Prevent** | Process improvements, controls, training, monitoring | ## Example Output (v4.0 — 6-Step RATH) ``` RATH STEP 1: IDENTIFY - Finding: OpenSSH 7.4 running on port 22 of production server - Context: Older version with known vulnerabilities RATH STEP 2: ASSESS - CVSS Score: 6.3 for multiple vulnerabilities - Impact: Remote code execution, information disclosure - Scope: Entire server and SSH-dependent services RATH STEP 3: THREAT - Attacker Objective: Exploit known CVEs in OpenSSH 7.4 - Attack Vectors: Remote code execution via SSH - Likelihood: High — well-documented and widely exploited RATH STEP 4: REMEDIATE - Immediate: Apply latest security patches - Recommended: Upgrade to OpenSSH 8.x or higher - Workaround: Apply all available security updates - Verification: Check version post-remediation RATH STEP 5: DOCUMENT - Severity: Critical - Weakness: Outdated software - SLA: Follow org patching SLA for critical vulns RATH STEP 6: PREVENT - Process: Implement automated patch management - Controls: Deploy CVE scanning, maintain system inventory - Training: Educate team on software update importance - Monitoring: Enable continuous vulnerability scanning ✅ RATH VERDICT: REMEDIATE IMMEDIATELY ``` ## Model Details | Parameter | Value | |-----------|-------| | **Architecture** | Qwen3-8B | | **Base** | georgehenney/Qwen3-8B-heretic (abliterated) | | **Context Window** | 128K (YaRN rope scaling, factor 4.0) | | **Training Data** | 610,220 examples | | **Security Content** | 53% (323K examples) | | **Agent/Tool Content** | 37% (228K examples) | | **Datasets** | 21 sources | | **Max Seq Length** | 8192 (zero truncation) | | **Tokens Trained** | 3,644,923 | | **Method** | MLX LoRA (rank 32, 8 layers, 1e-5 LR, 2000 iters) | | **Hardware** | Apple M4 Max 128GB | | **Peak Memory** | 69.5 GB | ## Training Datasets (21) **Security (11):** Trendyol/Cybersecurity-Instruction-Tuning (50K) · SkywardNomad92/pentest-findings-v2 (50K) · WNT3D/Ultimate-Offensive-Red-Team (25.6K) · auren-research/cve-sft-v5 (10K) · theelderemo/pentesting-explanations (5.9K) · Rootkit7/pentest-redteam-steering (2K) · acnimatic3722/kali-linux-pentesting-data (343) · AYI-NEDJIMI/bug-bounty-pentest-en · CJJones/Synthetic_PenTest_Reports · Whoisjutanlee/4-Security-Tools-Pentesting · cpagac/venomx-pentesting-harmful **Agent/Tool/Coding (5):** burtenshaw/agent-tools · Nanbeige/ToolMind · togethercomputer/CoderForge-Preview · automatelab/mcp-servers-tool-catalog · Jackrong/Claude-opus-4.7-TraceInversion-5000x **Agentic:** WithinUsAI/AgentAngel_100k (50K capped) · WithinUsAI/claude_mythos_distilled_25k (16K security) **Extracted:** hackingBuddyGPT · PentestGPT · Shannon · Ghidra · OpenMythos + Synthetic RATH chains ## Frameworks Supported CVSS 3.1 · NIST CSF 2.0 · OWASP Top 10 · CWE · MITRE ATT&CK · PCI DSS · HIPAA · SOX ## Source Code & Training Pipeline **[github.com/DeadByDawn101/RavenX-Sec](https://github.com/DeadByDawn101/RavenX-Sec)** ## License Apache-2.0 --- *"We don't give up. We do what others don't and build what isn't possible." — RavenX LLC*