Cybersecurity NER corpus 2019
Stanisław Saganowski · Harvard Dataverse · 2020
The cybersecurity NER corpus 2019 contains two corpora: soft_flaw - 1000 binary annotated tweets (TRUE: tweet mentions a software/system/device related security issue (vulnerability, exploit, patch), a malware, or a hacking method; FALSE: otherwise) class distribution: TRUE - 283, FALSE - 717 soft_flaw_NER - ca. 1000 NER annotations marking the name of the software/system/device/company with a security related issue, or the name of a malware The same tweet might be included in both corpora, however the vast majority of tweets is different across two corpora. Files are in the jsonl format.