Why this matters
Most generalist LLMs explain vulnerabilities; this model is tuned to produce runnable security artifacts instead of prose. That makes it useful when you need a ready-to-run Nuclei YAML, a working CVE PoC, or exploit-level C code rather than a high-level report.
Key Capabilities
- Tooling-first generation: outputs complete, executable artifacts (Nuclei templates, Python/C PoCs, JWT crackers, etc.), minimizing follow-up engineering work — so you can iterate faster during red-team research or triage.
- Domain-tuned on real reports: SFT was performed on ~2,541 bug-bounty reports, CVE writeups and offensive-research examples — so prompts produce pragmatic, practice-grounded payloads rather than abstract examples.
- Quantized, deployable variants: available Q6_K (21 GB) and Q4_K_S (15 GB) builds enable running on consumer GPUs with hardware/VRAM trade-offs — so teams can self-host without large cloud spend.
- Tooling bench validated: internal tooling benchmarks emphasize artifact completeness (Nuclei templates, PoCs) and low refusal rates, making it predictable for automation pipelines.
Who it's for and trade-offs
Great fit if you are an authorized security researcher, bug-bounty hunter, or pentest team that needs machine-assisted exploit development and artifact generation and can accept responsibility for safe/legal use. Look elsewhere if you need deep, multi-step reasoning, threat modeling, or a model constrained by strict content-safety refusal policies—those tasks are better handled by reasoning-focused models.
Where it fits
Use this model when the objective is producing runnable artifacts for validation, automation, or PoC generation inside an approved research environment. For high-level adversary modeling, strategic planning, or defensively oriented analysis, pair it with a reasoning model that provides context and mitigations.
Practical notes
The model is built on a Qwen3.6-derived base and fine-tuned with SFT. Choose the quantized variant that matches your hardware: Q6_K for high-fidelity server/large workstation setups and Q4_K_S for tighter VRAM budgets. Be mindful of legal and ethical constraints when generating offensive tooling.
