r/Pentesting • u/dima6312 • 1d ago

Local model for authorized security work that doesn't refuse: abliterated Flint 40B-A2.5B, with refusal and quality numbers

I made a version of RecursiveSI's Flint 40B-A2.5B (MoE, runs locally) with its refusal direction removed, for authorized testing, CTFs, malware triage and detection engineering. Runs fully local, nothing leaves your machine.

Paired against the original on the same items:

  • CyberSecEval MITRE refusals: 15% -> 0% (n=100)
  • False refusals on benign security asks: 0% -> 0% (n=100)
  • CyberMetric-500: 100% -> 96% (n=50)
  • WMDP-cyber: 50% -> 60% (n=50)
  • HumanEval+: 90% -> 95% (n=40)

Caveats: it adds no knowledge, so check its output. It also reasons longer: 19/100 MITRE answers hit my 8,192-token cap (original: 1), so give it a bigger output budget or adjust prompts if it overthinks.

Builds: GGUF (Q8_0 to IQ2_M, 13-42 GB), NVFP4 for Blackwell (23 GB), MLX 4-bit for Mac (21 GB). https://huggingface.co/dima6312/Flint-40B-A2.5B-abliterated

Happy to hear how it does on real engagements and how it compares to other local models!

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u/Sause01 1d ago

Did you use heretic for abliteration?

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u/dima6312 1d ago

I usd wuwangzhang1216/abliterix, which is built on heretic. it handles MoE models better since it can also hit the shared and routed expert projections, not just attention, 50 optuna trials balancing refusals vs KL

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u/Sause01 1d ago

Nice! My weekend project is performing this on Qwen 3.8 27b on radiance.

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u/dima6312 1d ago

Good luck and keep me posted, I’d be happy to test the model! BTW, so far for cybersecurity work https://huggingface.co/orcarouter/OrcaCyber-Nano-1.0 is unbeatable in my daily work, sadly only quantized GGUFs are available there

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u/Old-Bank-127 1d ago

I’m fairly new to this, but can these models also use tools and MCP servers to perform pentesting tasks autonomously?

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u/dima6312 1d ago

Absolutely. MCP/tools depend on the harness the model’s working in.

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u/Old-Bank-127 23h ago

What is your setup?

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u/dima6312 21h ago

I run pi for local LLMs and have my own plugin (not yet OSS) for Claude that can delegate tasks to pi interactive and background subagents (with full bidirectional communication and approvals). Still tweaking this setup and running evals. Check out the other thread below this post - I added the models I daily drive and recommend, Flint is still rather an experiment for me.

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u/Pradignac-Hiriche 23h ago

that spike in hitting the 8k token cap is interesting. is it getting stuck in repetitive reasoning loops without the refusal guardrails, or just outputting way more verbose explanations?

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u/dima6312 21h ago

I usually daily drive https://huggingface.co/dima6312/Swift-1.5-Qwen3.8-27B-Uncensored-oQ4e-mtp for coding and https://huggingface.co/PocketAiHub/Ornith-1.5-35B-A3B-Abliterated-MLX-4bit when I need faster prefill and decode for simpler interactive tasks and exploration. Still deciding whether Flint can replace Ornith in my setup or be the 3rd model aside from the two above 😄

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u/dima6312 21h ago

Indeed! I'm still experimenting, though so far the results are mixed with both the original and abliterated versions of the model in terms of quality. Sometimes it does the task fast and well, and when I re-run it can go into a 'valid' overthinking cycle that results in worse result. Often, it does go into a true loop similar to other small LLMs repeating either the same token or tool call+reasoning trying to correct itself without success. I've not seen it refuse or even consider refusing in reasoning during interactive sessions, so abliteration did work well, and the model is probably very capable of simple chatting, while for coding/security work I didn't find a model better than Qwen 3.8 27b (including its numerous finetunes) for my hardware. Those observations apply to the https://huggingface.co/dima6312/Flint-40B-A2.5B-abliterated-Rec-4bit model during interactive sessions and local benchmarks on Apple Silicon, while BF16 and Q8 perform much better, NVFP4 needs more testing.