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tegridydev
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https://tegridydev.com

AI & ML interests

Mechanistic Interpretability (MI) Research & sp00ky code stuff

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reacted to theirpost with 🔥 about 13 hours ago
What can you actually build with a cybersecurity dataset? I've been updating a few of mine on Hugging Face, and they now cover some pretty different parts of the security workflow. - open malsec has 1,104 defensive security scenarios across 20 subsets covering phishing, malware, scams, cloud security, API security, AI security and more - opensec triage has 50,000 contextual alert examples, plus compact model and edge training sets for testing whether models classify from the evidence around an event - infosec tool output has 1,004 examples across 19 tools for turning raw security output into evidence backed explanations, limitations and defensive next steps You could use them for: * phishing and scam explainers * alert triage tools * SOC assistants * scanner output explainers * analyst training * model comparisons * grounding and hallucination tests * small specialised security models * edge and local model experiments Or combine them into something like: scenario → evidence → triage → explanation → next action You also don't need to train anything straight away. Grab a few examples, run them through whatever model you already use and see where it gets confused :) Datasets: https://huggingface.co/datasets/tegridydev/open-malsec https://huggingface.co/datasets/tegridydev/opensec-triage https://huggingface.co/datasets/tegridydev/infosec-tool-output
reacted to theirpost with 🧠 about 13 hours ago
What can you actually build with a cybersecurity dataset? I've been updating a few of mine on Hugging Face, and they now cover some pretty different parts of the security workflow. - open malsec has 1,104 defensive security scenarios across 20 subsets covering phishing, malware, scams, cloud security, API security, AI security and more - opensec triage has 50,000 contextual alert examples, plus compact model and edge training sets for testing whether models classify from the evidence around an event - infosec tool output has 1,004 examples across 19 tools for turning raw security output into evidence backed explanations, limitations and defensive next steps You could use them for: * phishing and scam explainers * alert triage tools * SOC assistants * scanner output explainers * analyst training * model comparisons * grounding and hallucination tests * small specialised security models * edge and local model experiments Or combine them into something like: scenario → evidence → triage → explanation → next action You also don't need to train anything straight away. Grab a few examples, run them through whatever model you already use and see where it gets confused :) Datasets: https://huggingface.co/datasets/tegridydev/open-malsec https://huggingface.co/datasets/tegridydev/opensec-triage https://huggingface.co/datasets/tegridydev/infosec-tool-output
reacted to theirpost with 👀 about 13 hours ago
What can you actually build with a cybersecurity dataset? I've been updating a few of mine on Hugging Face, and they now cover some pretty different parts of the security workflow. - open malsec has 1,104 defensive security scenarios across 20 subsets covering phishing, malware, scams, cloud security, API security, AI security and more - opensec triage has 50,000 contextual alert examples, plus compact model and edge training sets for testing whether models classify from the evidence around an event - infosec tool output has 1,004 examples across 19 tools for turning raw security output into evidence backed explanations, limitations and defensive next steps You could use them for: * phishing and scam explainers * alert triage tools * SOC assistants * scanner output explainers * analyst training * model comparisons * grounding and hallucination tests * small specialised security models * edge and local model experiments Or combine them into something like: scenario → evidence → triage → explanation → next action You also don't need to train anything straight away. Grab a few examples, run them through whatever model you already use and see where it gets confused :) Datasets: https://huggingface.co/datasets/tegridydev/open-malsec https://huggingface.co/datasets/tegridydev/opensec-triage https://huggingface.co/datasets/tegridydev/infosec-tool-output
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