Exposed Twitter/X Credential-Stuffing Botnet Reveals Full Infrastructure and Operations Security researchers at GHOST uncovered an unsecured credential-stuffing botnet targeting Twitter/X, exposing its entire command-and-control (C2) infrastructure, worker fleet, and operational details. The botnet’s control panel a Python Flask-based dashboard branded "Twitter Checker Master Panel – FULL FIX v2.3" was left completely unauthenticated, allowing unrestricted access to its management functions. The C2 server, hosted on a Windows Server 2019 instance by Hetzner in Falkenstein, Germany, had multiple services (RDP, SMB, WinRM) exposed alongside the Flask panel. No authentication mechanisms were in place, enabling direct access to all endpoints via HTTP on port 5000. Researchers obtained the full 98 KB source code, confirming the absence of security controls and revealing hardcoded API routes for server management, campaign execution, and data exfiltration. The botnet’s worker fleet consisted of 18 Linux servers in the 31.58.245.0/24 range, owned by Turkish provider Komuta Savunma Yuksek Teknoloji in Ankara. All workers were accessible via root SSH on port 22, with credentials following a predictable pattern: a 12-character lowercase hexadecimal string followed by "kmt.!" likely referencing the hosting provider. The servers were labeled in Turkish (e.g., "Sunucu 8"), suggesting a previous generation of at least seven decommissioned nodes. During a 12-minute observation on April 10, 2026, the botnet tested 722,763 Twitter/X credential pairs, adding 18 newly compromised accounts to its hit list. Lifetime statistics revealed 4.86 million accounts checked, with 138 successful takeovers a 0.0028% success rate. Notably, 85.6% of tested accounts triggered two-factor authentication (2FA) and were discarded, demonstrating 2FA’s effectiveness in blocking such attacks. Only 211,662 accounts had valid passwords without 2FA, with just 138 fully compromised. Attribution indicators point to a Turkish-speaking operator, given the UI’s Turkish language labels (e.g., "Sunucu Ekle" for "Add Server") and the use of Komuta Savunma’s infrastructure. The botnet’s deployment occurred in waves between December 25, 2025, and January 31, 2026, with a tool rollout in late February. Despite its scale, the operation remained undetected on major threat feeds, including VirusTotal, ThreatFox, and AbuseIPDB, highlighting how credential-stuffing campaigns can persist on general-purpose cloud hosts. The exposed infrastructure including plaintext root passwords, bulk control endpoints, and real-time telemetry provided a rare, unfiltered view into the mechanics of a large-scale automated attack.

Massive Exposed Database Leaks Billions of SSNs and Passwords Researchers at UpGuard recently uncovered a misconfigured cloud database containing billions of sensitive records, including 2.7 billion Social Security numbers (SSNs) and 3 billion plaintext email-password combinations. The unsecured data was accessible without authentication, making it easily discoverable during routine internet scans. After notifying the FBI’s Internet Crime Complaint Center (IC3) and the German hosting provider Hetzner, the database was taken offline. Cybersecurity analysts suggest the dataset likely originated from aggregated and refined data from previous large-scale breaches, with estimates indicating over 1 billion unique SSNs and 2.2 billion unique passwords in the collection. To verify the data’s authenticity, researchers cross-checked records with known individuals, confirming that the SSNs were valid. One person in the dataset had previously been a victim of identity theft, reinforcing concerns about the data’s legitimacy. Most of the exposed information appears to have been harvested before 2016, highlighting how old breaches continue to fuel modern cybercrime. The incident underscores the persistent risk of identity theft and fraud, as SSNs remain a critical authentication tool for financial accounts and credit applications. The scale of the leak demonstrates how threat actors compile and exploit stolen data long after initial breaches occur.