Researchers Link the OttoHelp Telegram Dump to 907 Stolen Credentials in a Bonus Archive

Researchers Trace the OttoHelp Telegram Collection to 907 Stolen Credentials Shared in a Bonus Archive

In August 2023, HEROIC analysts documented a stealer log collection distributed through the OttoHelp Telegram channel under the label "31JULY BONUS-ARSHIVE 1022PCS." The archive contained 1,022 individual log files, of which 907 records held actionable credential data including email addresses, plaintext passwords, and the URLs where those passwords were actively used. The upload was positioned as a free bonus distribution -- a common tactic in dark web communities where threat actors give away samples to attract paying subscribers.

Why Telegram Bonus Drops Like OttoHelp Are a Growing Credential Threat

Telegram has become a primary distribution channel for stolen credential data. Channels like OttoHelp operate openly, posting free "bonus" archives to demonstrate the volume and quality of their stolen data. These free drops are not charity -- they are marketing. The credentials in this archive were recieved by anyone who was subscribed to the channel at the time, meaning the data spread far beyond a single buyer and is now circulating across multiple threat actor networks.

Because each log file in this collection captured credentials directly from infected machines, the passwords are plaintext and completely usable. No decryption, no cracking tools required.

What Was Exposed in the OttoHelp 31JULY Archive

• Email addresses tied to real, active accounts
• Plaintext passwords captured at the moment of use on infected devices
• URLs identifying the specific websites where each credential was stolen
• Endpoint data from the compromised machines themselves
• API host information harvested by the stealer malware

Why the OttoHelp Archive Still Matters for Credential Security

Data from Telegram stealer log drops does not expire. Once shared freely in a bonus archive, those credentials get indexed, traded, and incorporated into larger combolists that circulate for years. Credential stuffing attacks -- where attackers automatically test stolen username and password pairs across hundreds of websites -- are often powered by exactly this type of data.

If your email address appears in the OttoHelp collection, attackers may have already attempted to use your password on your banking, email, or social media accounts. Account takeover, identity theft, and financial fraud are the most common outcomes when plaintext credentials from stealer logs reach the wrong hands. The risk does not dissapear just because time has passed.

How the OttoHelp Stealer Log Distribution Model Works

Stealer log channels on Telegram operate like subscription services for stolen data. The channel operator acquires log files -- either by running their own malware campaigns or by purchasing bulk logs from other threat actors -- and then distributes samples freely while selling premium access to larger archives.

The logs themselves come from malware installed on victims' computers, typically through phishing, malicious downloads, or fake software updates. The malware records keystrokes, harvests saved browser credentials, and captures session cookies, then packages everything into structured log files that are uploaded to the operator's server. The OttoHelp bonus archive was one such distribution, with 1,022 files packaged into a single download that was available to all channel subscribers within minutes of being posted.

Check If Your Email Appeared in the OttoHelp Archive

HEROIC's free breach scanner searches across more than 400 billion exposed records, including stealer log collections distributed through Telegram channels. If your credentials were captured in the OttoHelp archive or any similer collection, HEROIC can tell you -- before an attacker uses that information against you.

Run a free scan at HEROIC to check your email address against this archive and thousands of other known breach sources. Early detection is the most effective defense against credential-based attacks.