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 [[email protected]]

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 [email protected].

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:

Use the data only for permitted purposes listed above
NOT attempt to re-identify individuals
NOT use the data to develop tools that facilitate image-based abuse
Cite this dataset in any publications or outputs
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: [[email protected]]

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

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