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Introduction
In the hidden corners of the internet, an invisible economy thrives — one built on stolen data, digital deception, and a new kind of automation. Over the last few years, cybercriminals have refined their craft into something resembling a high-speed data factory, powered not by servers in secret basements but by a familiar platform: Telegram. What began as small-scale credential theft has now evolved into a sprawling ecosystem capable of harvesting tens of millions of stolen accounts every single day.
This is the story of how cybercrime became industrialized — and how a group of researchers decided to infiltrate the chaos, building a monitoring system powerful enough to expose the true scale of this digital black market.
The Rise of an Automated Underground Economy
The underground data theft ecosystem has reached a level of precision and structure once reserved for legitimate corporations. Credential-stealing malware, often referred to as “stealers,” has become the driving force behind this billion-dollar shadow economy. These programs quietly siphon passwords, cookies, and session tokens from infected computers, feeding a massive trade network hidden in plain sight.
Researchers monitoring this activity discovered that Telegram has become the nerve center of the operation. It’s no longer just a messaging app; it’s now the largest data distribution hub for cybercriminals. A single actor, according to analysts, can push up to 50 million stolen credentials per day — an unimaginable scale that turns theft into an industrial process.
Inside the Stealer Ecosystem
The stealer economy operates much like a supply chain, with distinct roles and layers working in perfect coordination.
Primary sellers control private and public Telegram channels, selling or leaking fresh data logs from infected devices. Aggregators then gather these logs from multiple sources, merging them into searchable databases. Finally, traffers distribute infostealer malware, embedding it in software cracks, pirated games, or malicious websites to infect more victims.
Researchers noted that aggregators frequently repackage and repost stolen data, creating duplicates and inconsistencies across the network. To retain dominance, sellers often encrypt archives or lock them with passwords that redirect users to their channels. This strategy doesn’t just obfuscate the origin of the data; it ensures that every click leads back to the seller, reinforcing their influence within the criminal marketplace.
Building a Scalable Monitoring System
To understand and contain the problem, a team of cybersecurity researchers developed an automated surveillance system to track, collect, and analyze stolen data.
Their system, powered by 20 Telegram Premium worker accounts, used a modified version of the Pyrogram library to continuously crawl through Telegram’s vast ecosystem of channels and groups. It automatically joined new groups mentioned in messages and downloaded shared data archives in real time.
The core of their infrastructure was a decoupled downloader service that authenticated independently, extracted stealer logs in multiple formats, and removed processed files to save space. Each dataset was hashed and stored in ClickHouse’s ReplacingMergeTree engine, a design that allowed for lightning-fast deduplication and cross-referencing of reused credentials — exposing how the same stolen passwords circulated through multiple criminal groups.
To locate the most malicious networks, the system implemented a probabilistic ranking model. Channels referenced by known malicious entities were automatically flagged and prioritized for deeper analysis. This eliminated the need for manual tracking, dramatically improving detection coverage.
Data Donation and Impact
In just nine months, the team’s system indexed more than 30 billion Telegram messages and analyzed nearly 80 billion stolen credentials. At its peak, it processed 600 million credentials in a single day — a staggering number that reveals just how automated the cybercrime world has become.
Due to limited storage and processing power, the team made the bold decision to donate its dataset to Have I Been Pwned (HIBP), a well-known breach notification platform. This move transformed private intelligence into public good, allowing users worldwide to check whether their accounts had been compromised.
By contributing this data, researchers aimed to undermine the underground economy’s power and provide legitimate pathways for people to protect themselves, without relying on illegal forums or shady data resellers who often exploit victims again.
What Undercode Say:
This research reveals more than just numbers — it exposes a paradigm shift in how cybercrime operates. Telegram, originally designed as a privacy-focused communication tool, has unintentionally become the backbone of a criminal automation system.
Stealers are no longer simple tools used by hackers; they are part of an industrialized, supply-driven market. The efficiency of this system lies in its automation — from infection to data resale, every step is optimized. The use of bots, self-updating channels, and distributed networks allows one actor to reach millions without any direct contact.
From an analytical standpoint, the key innovation isn’t in the malware itself but in the distribution logistics. By using Telegram as both a hosting and coordination layer, criminals bypass traditional dark web forums, which are often monitored. Telegram’s end-to-end encryption and massive user base offer anonymity and accessibility, creating the perfect storm for large-scale data trading.
Another crucial insight is the monetization structure. Aggregators act like “data brokers,” while traffers behave like “sales representatives,” distributing malware through different channels. Each actor plays a role that mirrors legitimate business hierarchies, complete with quotas, commissions, and client management systems.
The system built by researchers marks a breakthrough in cyber threat intelligence automation. By employing a probabilistic ranking model, it identifies malicious nodes using behavioral data rather than static indicators — a step closer to predictive cybersecurity. It also demonstrates that combating cybercrime at scale requires the same level of sophistication as the attackers themselves.
But there’s a deeper, more disturbing takeaway: the automation of theft has dehumanized cybercrime. With machine learning and AI tools integrating into these processes, the next generation of stealers could self-optimize, self-distribute, and self-update. This turns the cyber underground into an autonomous digital organism, feeding on human data without pause.
For policymakers and cybersecurity teams, the implication is clear — this isn’t a fight against individuals anymore; it’s a battle against an evolving, adaptive machine. The best defense will combine open data sharing, real-time monitoring, and public transparency — exactly what the HIBP integration represents.
The researchers’ contribution to open platforms signals a new trend in cybersecurity: the weaponization of transparency against organized cybercrime. It transforms stolen data from a criminal asset into a public shield.
🔍 Fact Checker Results
✅ Telegram is confirmed as a major hub for data trading in multiple cybersecurity reports.
✅ The scale of credential distribution (tens of millions daily) aligns with verified threat intelligence findings.
✅ The HIBP collaboration has been publicly acknowledged by independent researchers.
📊 Prediction
🔮 Expect Telegram’s role in cybercrime to face stronger regulatory pressure and monitoring tools within the next two years.
💡 Cybercriminals will likely migrate to decentralized or AI-assisted distribution platforms once Telegram becomes more regulated.
⚙️ Defensive automation will rise — companies will use AI-driven crawlers to detect and neutralize stolen data faster than ever before.
🕵️📝✔️Let’s dive deep and fact‑check.
References:
Reported By: cyberpress.org
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