README.md

metadata

license: cc-by-nc-4.0
doi: 10.5281/zenodo.18157450
extra_gated_prompt: >-
  By requesting access to this dataset, you agree to:

  1. Use this dataset only for research, journalism, policy, or education
  purposes 2. NOT attempt to re-identify hashed usernames 3. NOT use this data
  to train AI systems to generate non-consensual imagery 4. Cite this dataset in
  any publications 5. Report any ethical concerns to [nana.nwachukwu@gmail.com]
extra_gated_fields:
  Name: text
  Affiliation: text
  Intended use: text
  I agree to the terms above: checkbox
task_categories:
  - text-classification
language:
  - en
tags:
  - TfGBV
  - AI safety
  - content moderation
  - NCII
  - gender-based violence
  - Grok
  - deepfakes
pretty_name: TfGBV-Grok Dataset
size_categories:
  - n<1K

TfGBV-Grok Dataset: AI-Facilitated Non-Consensual Intimate Image Generation

⚠️ WORK IN PROGRESS: This dataset is actively being developed. There may be classification errors or inconsistencies. It will be updated as I process the rest of the raw data. Feedback and corrections are welcome — please email nana.nwachukwu@gmail.com.

Dataset Description

This dataset documents 565 instances of users publicly requesting Grok AI (integrated into X/Twitter) to generate non-consensual intimate imagery — digitally "undressing" women without their knowledge or consent.

The dataset was curated to support research on technology-facilitated gender-based violence (TfGBV) and to inform policy responses to emerging AI harms.

Dataset Summary

Statistic	Value
Total records	565
Perpetrator requests	481
Prompt sharing (attack methods)	48
Victim testimonies	7
Reports of abuse	10
Commentary	13
Benign/unrelated Grok use	6

Actor Type Classification

Each record is classified by who is speaking:

Actor_Type	Count	Description
PERPETRATOR_REQUEST	481	Users directly requesting Grok to generate NCII
PROMPT_SHARING	48	Users sharing attack methods/prompts (JSON exploits, etc.)
COMMENTARY	13	Users discussing or criticizing the phenomenon
REPORTING_ABUSE	10	Users calling out or questioning harmful behavior
VICTIM_TESTIMONY	7	Victims reporting that their images were targeted
BENIGN_GROK_USE	6	Unrelated Grok use (e.g., Halloween costumes)

Harm Type Classification

Each record is also classified by the type of harm:

Harm_Type	Count	Description
NCSII_REQUEST	418	Direct requests to remove/replace clothing
SHARES_NCSII_METHOD	42	Sharing prompts/methods for NCII generation
DISCUSSES_NCSII	28	Discussion of the NCII phenomenon
PROMPT_INJECTION	8	Structured JSON attacks to bypass safeguards
NOT_NCSII_RELATED	6	Benign content, not related to NCII
SHARES_BODY_MOD_METHOD	6	Sharing methods for body modification requests
BODY_MODIFICATION	5	Requests to alter body features
DISCUSSES_MINOR_TARGETING	2	Discussion of minors being targeted

Data Fields

Column	Type	Description
Record_ID	int	Unique identifier (1-565)
Tweet_ID	int	Original tweet ID — retained for verification
Username_Hash	string	SHA-256 hash of username (truncated to 12 characters)
Date	string	Standardized date (YYYY-MM-DD)
Content_Snippet	string	Text content of the tweet
Actor_Type	string	Who is speaking (perpetrator, victim, commentator, etc.)
Harm_Type	string	Type of harm documented

Important Note on Classification This dataset distinguishes between:

• Perpetrators — users actively requesting or sharing methods for NCII generation
• Victims — users reporting that theirs/ someone else's images were targeted
• Commentators — users discussing, criticizing, or reporting the phenomenon

This distinction is crucial for accurate research. Not every record represents a perpetrator request — some document the broader ecosystem of harm, including victim experiences and community responses.

Intended Uses

✅ Permitted uses:

• Academic research on TfGBV and AI harms
• Policy analysis and advocacy
• Journalism and public interest reporting
• AI safety tool development (detection, moderation)
• Educational purposes

❌ Prohibited uses:

• Re-identification of hashed usernames
• Harassment or doxxing of any individuals
• Training AI systems to generate NCII
• Commercial use without authorization
• Redistribution without permission

Access

This dataset is gated to ensure responsible use. By requesting access, you agree to:

1. Use the data only for permitted purposes listed above
2. NOT attempt to re-identify individuals
3. NOT use the data to develop tools that facilitate image-based abuse
4. Cite this dataset in any publications or outputs
5. Report any ethical concerns or incidents

Ethical Considerations

Privacy

• Usernames have been pseudonymized via SHA-256 hashing
• Tweet IDs are retained for verification purposes only
• No victim names or identifiers were found in the dataset

Sensitivity

• This dataset documents harmful behavior and contains references to sexual content
• Two records reference minors — handle with appropriate care
• Content may be distressing to some researchers

Limitations

• Dataset captures only publicly visible posts
• May not represent the full scope of the phenomenon
• Content snippets are partial, not full tweets

Citation

@dataset{tfgbv_grok_2026,
  author = {[Nana Mgbechikwere Nwachukwu]},
  title = {TfGBV-Grok Dataset: AI-Facilitated Non-Consensual Intimate Image Generation},
  year = {2026},
  doi: 10.5281/zenodo.18157450
  publisher = {Zenodo},
  url = {https://huggingface.co/datasets/[Mtechlaw]/TfGBV-Grok-NCII-Dataset}
}

Contact

For questions, access requests, or to report concerns:

[Nana Mgbechikwere Nwachukwu]
Email: [nana.nwachukwu@gmail.com]

Changelog

• v2.0 (January 2026): Added 'Actor_Type' classification to distinguish perpetrators from victims, commentators, and reporters. Improved 'Harm_Type' taxonomy.
• v1.0 (January 2026): Initial release