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- Primary Function: “Comrade Major AI” is capable of de-anonymizing anonymous Telegram channels, aiding in the identification of their owners and administrators. This feature is intended to combat cybercrime, the spread of fake information, and various other legal violations within the messaging platform.
- Operational Methodology: The neural network operates similarly to a human analyst by examining channel descriptions, message content, and embedded chats. However, it does so more quickly and effectively. This AI-driven approach allows for a more efficient and comprehensive analysis compared to traditional methods.
- Potential Users: The system is expected to be utilized by state or private organizations involved in investigating cybercrimes. Its capability to analyze and process large amounts of data swiftly makes it a valuable tool for these organizations.
- Development and Testing: Currently, the neural network is undergoing internal testing at the developer company, T.Hunter. This phase is crucial for refining the system and ensuring its effectiveness and reliability in practical applications.
- Launch Timeline: The full version of the neural network is planned to be launched in 2024-2025. The testing phase will likely inform any necessary adjustments or improvements before its official release.
“Comrade Major AI” represents an advancement in the use of AI for law enforcement and cybersecurity purposes, particularly in the context of managing and monitoring digital communication platforms like Telegram. Its development underscores the growing role of AI and machine learning in various aspects of cybersecurity and digital governance.
“Comrade Major” Neural Network: The Future of Identifying Anonymous Telegram Channel Owners
Development and Capabilities of “Comrade Major”
In Russia, a new neural network named “Comrade Major” is in development, aimed at identifying the administrators and owners of anonymous channels on Telegram. As reported by the news outlet “Izvestiya,” this initiative is a collaboration between the National Technology Initiative (NTI) and the developer company T.Hunter.
Operational Efficiency and Methodology
Similar to human analysts, “Comrade Major” examines channel descriptions, message contents, and embedded chats but operates faster and more efficiently. It is anticipated to be employed by state or private organizations focusing on cybercrime investigations. Igor Bederov, the head of the Department of Information-Analytical Research at T.Hunter, explained that the neural network utilizes a common text-based neural network operated on the company’s servers. A Telegram bot has been developed to facilitate interaction with the software.
Data Analysis and Expansion Plans
The neural network collects and studies a vast array of data, including information about administrators from channel descriptions, archived copies, messages, metadata of published files, captions, embedded chats, sticker packs, documents, and videos. It can also perform checks on legal entities based on their tax identification numbers (INN), providing information about their existence duration, employee count, registered capital, and address. Future plans for the software include the ability to investigate social media accounts, phone numbers, email addresses, and cryptocurrency wallets.
Implications and Anticipated Launch
“Comrade Major” represents a significant advancement in AI-driven cybersecurity and digital monitoring. Its ability to extract information even from sets of stickers demonstrates the depth and breadth of its analytical capabilities. The neural network is currently being tested internally at T.Hunter, with a full-scale launch anticipated in 2024-2025. This AI tool underscores the growing role of machine learning in cybersecurity, particularly in managing digital communication platforms like Telegram.
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