The Russian dating platform Mimolet, which combines profile feeds, private chats, and public interest-based groups, has undergone a thorough examination of how it manages user data and unwanted content. The review analyzed everyday user flows, network behavior, and publicly available infrastructure details, concluding that the service implements several sound security practices while leaving room for greater transparency in two specific areas.
Photograph processing before storage is handled rigorously. When a user uploads an image, the server validates the file by its actual content rather than relying on the JPG or PNG extension. The image is decoded, metadata such as EXIF data (camera model, timestamps, and geolocation) is removed, dimensions are limited, and multiple optimized versions are generated for the mobile feed. Files that cannot be properly recognized as images are rejected outright.
The main server infrastructure is located in Russia. The core API and primary database operate within Russian data centers, while media files are stored in an S3-compatible object storage provided by a domestic cloud vendor. This separation keeps the database lean and allows efficient delivery of images to users.
AI-powered functions, including language processing, speech recognition, vector embeddings, and image moderation, primarily run on dedicated GPU infrastructure controlled by the Mimolet team. A fallback connection to external AI providers exists for redundancy, but the primary path remains internal and isolated via a private technical channel.
Images intended for profiles or public groups are checked before publication. Two distinct models analyze the content—one for prohibited visual material and another multimodal model for contextual meaning—while an additional pass can examine suspicious regions in greater detail. If a violation is confidently detected, the image is blocked and, in severe cases, the account and linked devices may also be restricted.
Complaints and blocking are available to every authorized user without a paid subscription. The reporting form offers structured categories such as scams, cryptocurrency schemes, intimate services, prohibited substances, and false information. Once submitted, the reported profile immediately disappears from the reporter’s feed, and accumulated signals from multiple users are escalated for human review.
Moderator actions are recorded in an administrative audit log that captures the decision, timestamp, and operator involved. This internal record supports later analysis of errors or disputed cases.
Built-in voice calls rely on WebRTC and internal identifiers rather than phone numbers, so users can speak without revealing personal contact details. The feature is disabled if either party has blocked the other.
Two areas were flagged for improvement. The privacy policy uses vague phrases such as “no longer than necessary” and “within a reasonable time,” leaving users without concrete retention periods for photographs, chat history, moderation records, or AI conversation data. The review recommends publishing a clear table listing data categories, processing purposes, retention periods, and post-deletion behavior. Additionally, the appeals process for blocked accounts lacks a dedicated form with a reference number, status tracking, and expected response time, making it difficult for users to follow the progress of their request.
Overall, Mimolet demonstrates several proactive security measures—metadata stripping, pre-publication image checks, subscription-free reporting, and Russian-hosted core infrastructure—that are integrated directly into the user experience rather than added as afterthoughts. The main shortcomings lie in transparency around data retention and the appeals workflow, both of which could be addressed with relatively modest updates.
