CAI Dataset is presented as the largest described corpus of LLM-driven hacker trajectories, with the claim that operator data concentration in frontier-model providers creates a major security risk best addressed by on-premise specialized LLMs.
Hackphyr: A local fine-tuned LLM agent for network security environments.arXiv:2409.11276, 2024
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Controlled experiments across 96 LoRA adapters show that reduced optimizer updates explain nearly all observed memorization drops in DP-SGD fine-tuning, HMAC pseudonymization cuts exposure 40-61% without creating new targets, and 1-3B models achieve only 0.19-0.28 F1 under the tested budget.
citing papers explorer
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Cybersecurity AI (CAI) Dataset
CAI Dataset is presented as the largest described corpus of LLM-driven hacker trajectories, with the claim that operator data concentration in frontier-model providers creates a major security risk best addressed by on-premise specialized LLMs.
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Decomposing Memorization Reduction in Privacy-Preserving Fine-Tuning of SLMs for CSIRTs
Controlled experiments across 96 LoRA adapters show that reduced optimizer updates explain nearly all observed memorization drops in DP-SGD fine-tuning, HMAC pseudonymization cuts exposure 40-61% without creating new targets, and 1-3B models achieve only 0.19-0.28 F1 under the tested budget.