Post
1497
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
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
