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Cyber Security
Independent · Digital
Thehackingpost
CybersecurityAI-assisted

880,000 Exposed Credentials Trace Back to 50 Major Global Companies, Including AT&T, Verizon, Walmart, Uber, FedEx and More

An analysis of credential leaks reveals significant exposure for major global corporations due to weak passwords, user errors, and automated attack tools. Research from Social Links and ParanoidLab identified approximately 880,000 leaked credentials…

An analysis of credential leaks reveals significant exposure for major global corporations due to weak passwords, user errors, and automated attack tools. Research from Social Links and ParanoidLab identified approximately 880,000 leaked credentials associated with 50 major companies during Q2 2025.

The data comprises both corporate accounts and external user logins sourced from infostealer logs, combo lists, darknet forums, and Telegram channels. Researchers found a total of 879,654 leaked records, comprising 263,669 corporate-domain credentials and 615,986 user account credentials outside corporate networks.

Telecom Industry Faces Significant Exposure

The telecom sector exhibited the highest volume of leaks, with companies like AT&T, BT Group, and Verizon accounting for over 344,000 compromised credentials in the second quarter. This is attributed to both their large customer bases and the attractiveness of their systems to attackers.

Retail and e-commerce platforms recorded over 145,000 leaked credentials, involving brands such as Walmart, Etsy, and Rakuten. Transportation companies, including Uber and EasyJet, reported over 140,000 compromised accounts, while major delivery operators like FedEx, UPS, and DHL collectively experienced 100,840 exposed credentials.

An analysis of credential leaks reveals significant exposure for major global corporations due to weak passwords, user errors, and automated attack tools.
Peter Collins · Thehackingpost

Banks reported a lower total of 86,974 leaked accounts. However, poor password practices at institutions like SBI and China Construction Bank increased operational risk despite fewer leaks overall.

Weak Password Practices Persist Across Industries

A significant pattern in the research is the reliance on weak or predictable passwords. Only 26.5% of all credentials analyzed met high-security criteria. Common passwords such as “password,” “123456,” and “admin” remain prevalent, facilitating automated attacks and phishing campaigns. In corporate accounts, the prevalence of weak credentials ranged from 71% to 92%, varying by industry.

AI-Driven Threats Enhance Security Challenges

The surge in leaked credentials coincides with an increase in AI-powered cyberattacks. The report indicates a 1,265% increase in phishing activity, with AI-generated messages constituting over 80% of all phishing attempts. Generative AI-driven fraud is projected to rise from $12.3 billion in 2023 to $40 billion by 2027, as attackers leverage automation to personalize lures and exploit weak authentication practices.

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Industry Response: Emphasis on Identity Protection

Security experts highlight that much of the exposure results from the availability of infostealer logs and automated credential-harvesting tools. Attackers are increasingly targeting human vulnerabilities using industrial-scale phishing tools and AI-driven impersonation techniques. This shift necessitates a focus on user identity security and continuous monitoring of account behavior.

The findings indicate a fundamental change in breach dynamics. Security controls centered on infrastructure are proving inadequate when human errors, such as password reuse, present significant risks. As attackers increasingly utilize automation and AI-assisted phishing, they gain a clearer understanding of potential entry points. This necessitates a strategic pivot for security teams, emphasizing identity protection and user-level risk in defensive planning.

Based on reporting by TechBullion.

AI transparency. This article was produced with the assistance of artificial intelligence and published under human editorial oversight. AI systems can make mistakes. Read how we use AI (EU AI Act, Art. 50).
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