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Uncensored and Offensive Security AI Models Benchmark

AI 摘要

This benchmark lists uncensored open-weight AI models for authorized red team operations, penetration testing, and security research. Models like LiquidAI/LFM2-2.6B and zai-org/GLM-5.3 are detailed, showcasing parameters, context length, VRAM requirements, and uncensoring methods. LFM2-2.6B uses SFT + RL and reward-guided post-training on 75K cybersecurity rows, achieving a CyberBench Average of 0.592 F1/Acc. GLM-5.3, with 753B parameters, employs direct weight modification for offensive security tasks, retaining soft refusal on copyright reproduction.

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2026年9月29日 09:00
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来源·Hacker News·github.com