datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
pwn-scenarios
pwn-scenarios
36,457 records, 47 vulnerability classes. A dataset of penetration testing / bug bounty scenarios -- generalized, reusable condition → step → impact → remediation playbooks for common vulnerability classes, each grounded in a real, publicly disclosed report or writeup.
Full source, collection scripts, the companion attack decision graph, and complete docs live on GitHub: https://github.com/AlaBYahya/pwn-scenarios
Example record
{
"vulnerability":… See the full description on the dataset page: https://huggingface.co/datasets/aeby/pwn-scenarios.aeb_tdu_Atomic20perafrica-comoros-comoros-social-protection-and-labor-aebfb39a
Comoros - Social Protection and Labor | Africa (Comoros official open data)
3,191 rows - 1 Africa country - 1980-2025 - Repackaged by Electric Sheep Africa
TL;DR
This dataset packages one official CSV resource from Comoros as
ML-ready Parquet. The source file is the provenance boundary; all usable
indicators or tabular columns from the resource stay together in this repo.
About the source
Source: Comoros - Social Protection and Labor… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-comoros-comoros-social-protection-and-labor-aebfb39a.aeb_tdu_AtomicImmersive5000_10aeb_tdu_AtomicFullaeb_tdu_ex02
Dataset Card for "aeb_tdu_ex02"
More Information needed
AEB_1_EMOLLM
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
aeb_tdu_Atomic10peraeb_tdu_Atomic40peraeb_tdu_exInvalid50Peraeb_tdu_Atomic30peraeb_tdu_Atomic50peraebsaaeb_tdu_exInvalid40Peraeb_tdu_AtomicImmersive30AEB_2_FT
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
aeb_tdu_exRef2aeb_tdu_ex03aeb_tdu_AtomicImmersive10000_8-12AEB_1_FT
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
aeb_tdu_exRefmonoling_aebAEB_1_ZS
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
aeb_tdu_ex04aeb_tdu_AtomicImmersive40AEB_1_FS
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
aeb_tdu_exInvalid20PerAEB_2_ZSaeb_tdu_exInvalid10PerMetaGDPO