AI Skinny Filter — agentic threat model

Not certain from the listing — likely utilizes a specialized computer vision or diffusion model for image-to-image translation. Threats include adversarial image inputs designed to cause model denial of service, bypass safety filters, or exploit model vulnerabilities.

Not certain from the listing — processes user-uploaded images for body and facial analysis. Threats include unauthorized retention of sensitive biometric/personal photos, lack of data encryption in transit/at rest, and potential data leakage if uploads are used for model training.

Not certain from the listing — does not appear to use a complex agentic orchestration framework, operating instead as a simple pipeline. Threats are limited to insecure integration of image processing libraries (e.g., Pillow, OpenCV) which may be vulnerable to remote code execution via malformed image metadata.

Not certain from the listing — hosted on an external AI platform. Threats include server-side request forgery (SSRF) if the tool allows uploading images via URL, resource exhaustion from processing high-resolution images, and container compromise.

Not certain from the listing — no mention of content moderation or output guardrails. Threats include the generation of inappropriate, offensive, or highly distorted body-image outputs without automated detection or logging.

Not certain from the listing — open-source tool with no explicit compliance certifications. Threats include non-compliance with biometric privacy regulations (like BIPA or GDPR) due to facial and body-shape analysis of user uploads without explicit consent frameworks.

Not certain from the listing — operates as a standalone horizontal utility. Minimal ecosystem risk unless integrated into automated social media posting pipelines where compromised outputs could lead to reputational damage.