63.9 TFLOPS 106
followers ·
583 following Mechanistic Interpretability (MI) Research & sp00ky code stuff
reacted to their post with 🔥 about 2 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 their post with 🧠 about 2 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 their post with 👀 about 2 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
View all activity view post 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: tegridydev/open-malsec tegridydev/opensec-triage tegridydev/infosec-tool-output See translation
So, let’s make our own dataset 
