We noticed a resurfacing of older breach data, specifically targeting financial service platforms. While the volume wasn't the primary concern, the fact that the data from a 2009 breach of **Money Bookers** (now **Skrill**) is still circulating and potentially being used for credential stuffing and account takeover attacks caught our attention. The data, which includes personally identifiable information (**PII**) alongside email addresses and IP addresses, poses a risk to individuals who may have reused passwords or whose information can be used for social engineering. The age of the breach highlights the long-term risks associated with legacy data and the importance of continuous monitoring for compromised credentials.
The breach, initially occurring in **2009**, impacted approximately **3,667,762** accounts. While the breach itself is not new, its continued presence in underground forums and potential use in modern attacks makes it relevant for enterprise security teams. The data appeared in various locations, including known breach aggregation sites and potentially private forums, observed from late 2015 onward.
The data exposed includes:
Key point: Total records exposed: 3,667,762
Key point: Types of data included: Email Address, IP Address, Phone Number, First Name, Last Name, Birthday
Key point: Sensitive content types: PII
Key point: Source structure: Database
The age of the data is a key factor. Individuals may have forgotten about accounts created in **2009**, making them less likely to monitor for suspicious activity. Furthermore, the exposed PII could be used in conjunction with more recent data breaches to create more complete profiles for targeted attacks. The breach was reported to include names, email addresses, home addresses, and IP addresses, went undetected until October 2015.
This breach echoes similar incidents where older data resurfaces years later to fuel new attacks. For example, older LinkedIn and MySpace breaches are still leveraged in credential stuffing campaigns. The persistence of this type of data underscores the need for organizations to implement robust password reset policies and monitor for compromised credentials across a wide range of sources.
Email · Address · Ip · Phone · Number · First · Name · Last · Birthday
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