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Malware Classification datasets

archive 2025-07-28

7 datasets carry the task tag "Malware Classification" (the task itself: Malware Classification), ordered by the archive's paper count. Page 1 of 1: 7 shown of 7. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

Malware Classification datasets 1–7 of 7

A labeled benchmark dataset for training machine learning models to statically detect malicious Windows portable executable files.
115 papers · 0 benchmarks
The Microsoft Malware Classification Challenge was announced in 2015 along with a publication of a huge dataset of nearly 0.5 terabytes, consisting of disassembly and bytecode of more than 20K malware samples.
36 papers · 1 benchmark
The Malimg Dataset contains 9,339 malware byteplot images from 25 different families.
6 papers · 1 benchmark
BODMAS (Blue Hexagon Open Dataset for Malware AnalysiS)
We collaborate with Blue Hexagon to release a dataset containing timestamped malware samples and well-curated family information for research purposes.
1 paper · 0 benchmarks
IoT-23 (IoT-23: A labeled dataset with malicious and benign IoT network traffic)
IoT-23 is a dataset of network traffic from Internet of Things (IoT) devices.
1 paper · 0 benchmarks
MOTIF (MOTIF: A Large Malware Reference Dataset with Ground Truth Family Labels)
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
1 paper · 0 benchmarks
This dataset is comprised of the dynamic analysis reports generated by CAPEv2, from both malware and goodware.
0 papers · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.