richardyoung/mythos-qwen-1.5b-final-heretic
The richardyoung/mythos-qwen-1.5b-final-heretic is a 1.5 billion parameter Qwen 2.5 Coder model, fine-tuned for cybersecurity research, vulnerability analysis, and exploit development. It is a decensored version of expper/mythos-qwen-1.5b-final, created using Heretic v1.4.0, and excels at generating accurate, production-ready security code with Chain-of-Thought reasoning. This model is specifically optimized for tasks like analyzing CVEs, understanding exploit mechanics, and solving complex security challenges.
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Model Overview
This model, richardyoung/mythos-qwen-1.5b-final-heretic, is a decensored version of the expper/mythos-qwen-1.5b-final model, built using the Heretic v1.4.0 framework. It is based on the Qwen 2.5 Coder 1.5B Instruct architecture and has been specialized through fine-tuning for advanced cybersecurity applications.
Key Capabilities & Differentiators
- Cybersecurity Specialization: Fine-tuned on over 700 high-reasoning security examples, covering PHP internals, MyBB exploitation, deserialization chains, type juggling, and advanced Python exploit synthesis.
- Decensored Output: Compared to its original counterpart, this 'Heretic' version significantly reduces refusals, demonstrating 2 refusals out of 100 queries versus 93/100 for the original model.
- Reasoning & Self-Correction: Employs Chain-of-Thought reasoning with self-correction loops and mathematical logic notation to produce accurate security code.
- Training Details: Fine-tuned using QLoRA (4-bit quantization) with Unsloth over 4 epochs on a dataset of 1000+ examples, with a sequence length of 4096.
Intended Use Cases
- Security Research: Analyzing Common Vulnerabilities and Exposures (CVEs) and understanding exploit mechanics.
- Red Team Education: Learning and practicing exploit development patterns.
- Blue Team Defense: Gaining insights into attack vectors to develop more robust detection mechanisms.
- CTF & Training: Solving complex security challenges and for educational purposes in authorized security testing environments.