mandiant / mandiant/stringsifter
EMBER training set: malicious and benign samples?
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- Dominant language
- Python
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Description
Hi! Is this trained on both malicious and benign samples from the EMBER set? Unclear from the documentation whether the weak supervision of importance labels comes from exclusively malicious distributions. Using this tool in a research setting where this is a potentially important distinction.
Thanks!
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Review the repository documentation and the EMBER training and labeling setup to determine whether both malicious and benign samples are used and how importance labels are assigned. Done means documenting that distinction clearly for research users.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100