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Security: priyadip/ITDF

Security

SECURITY.md

Security Policy

Supported Versions

Version Supported
Latest (main)
Older commits

Reporting a Vulnerability

Do NOT open a public GitHub issue for security vulnerabilities.

Report privately via GitHub Security Advisories:

  1. Go to the repository → Security tab → Report a vulnerability
  2. Provide a detailed description, reproduction steps, and potential impact
  3. You will receive a response within 72 hours

Responsible Use Policy

This codebase processes human facial images. By using this repository you agree to:

  • Consent — Only process images of individuals who have given explicit informed consent
  • No mass surveillance — Do not use for bulk de-anonymization, surveillance, or identity tracking
  • No deception — Do not use outputs to deceive, impersonate, or defraud individuals
  • No biometric databases — Do not use model outputs to build unauthorized biometric databases
  • Authorized contexts only — Permitted uses: academic research, authorized forensics, security testing with consent

Violation of this policy also violates the CC BY-NC-ND 4.0 license under which this code is released.


Known Limitations & Risks

Risk Description
Privacy Model can reveal the appearance of individuals without makeup — use only with consent
Bias Trained on FFHQ-Makeup; may perform differently across skin tones and demographic groups
Misuse Could be used to "unmask" individuals who prefer their cosmetic presentation
No guarantees Outputs are model predictions, not ground truth — do not use for legal identification

Model Weights Access

Pretrained weights are stored in a private Hugging Face repository (priyadip/itdf-model). Access requires explicit approval. Approved access does not grant redistribution rights.


Dependencies

Keep dependencies up to date. Known critical packages:

pip install --upgrade torch torchvision timm Pillow

Run pip audit periodically to check for vulnerabilities in dependencies.

There aren't any published security advisories