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Nissan Says Customer Data Exposed After Breach at Red Hat Systems

 

Nissan Motor Co Ltd said that personal information of thousands of customers was exposed following a cyber breach at Red Hat, the US based software company it had engaged to develop customer management systems. 

The Japanese automaker said it was notified by Red Hat in early October that unauthorized access to a server had resulted in data leakage. The affected system was part of a Red Hat Consulting managed GitLab environment used for development work. 

Nissan said the breach involved customer information linked to Nissan Fukuoka Sales Co Ltd. About 21,000 customers who purchased vehicles or received services in Fukuoka, Japan were affected. 

The exposed data included customer names, physical addresses, phone numbers, email addresses and other information used in sales and service operations. Nissan said no credit card or payment information was compromised. 

“Nissan Motor Co Ltd received a report from Red Hat that unauthorized access to its data servers had resulted in information being leaked,” the company said in a statement.

It added that it has no evidence the data has been misused. Red Hat acknowledged earlier that an attacker had accessed and copied data from a private GitLab instance, affecting multiple organisations. 

The breach was disclosed publicly in early October after threat actors claimed to have stolen hundreds of gigabytes of data from tens of thousands of private repositories. The intrusion was initially claimed by a group calling itself Crimson Collective. 

Samples of the stolen data were later published by another cybercrime group, ShinyHunters, as part of an extortion effort. Neither Nissan nor Red Hat has publicly attributed the breach to a specific actor. 

Nissan said the compromised Red Hat environment did not store any additional Nissan data beyond what has already been confirmed. The company said it has informed affected customers and advised them to remain alert for suspicious emails, calls or messages that could exploit the leaked information. 

Cybersecurity experts say such data can be used for social engineering attacks, including phishing and impersonation scams, even if financial details are not exposed. The incident adds to a series of cybersecurity issues involving Nissan. 

In late August, a Qilin ransomware attack affected its design subsidiary Creative Box Inc in Japan. Last year, Nissan North America disclosed a breach impacting about 53,000 employees, while an Akira ransomware attack exposed data of roughly 100,000 customers at Nissan Oceania. 

The Red Hat breach has renewed concerns about supply chain security, where compromises at technology vendors can have cascading effects on downstream clients. Nissan said it continues to review its security controls and coordination with third party providers following the incident.

Dark Data as a Subset of Big Data Proving to be of Importance



Any data which is disregarded and still remains stored without being indexed anywhere is known as Dark Data, it has a tendency to get lost as it disappears for the researchers first. It has been gathered by organizations unintentionally and therefore it is unstructured in nature, it is not accessible to the public and is neither employed for any decision making.

The primary reason for the generation of dark data is the accumulation of bulk of data and only a small part of it being selected for analysis. Data is generated very rapidly; with every user clicking on a link, data is being generated which is analyzed by the corporations to better their businesses. However, they require only a limited amount of data that is structured and then kept as a record in databases whereas the remaining unstructured data is lost amid other data which is not indexed.

Out of 7.5 sextillion gigabytes of data generated throughout the world on a daily basis, 6.75 Septillion megabytes is left unprocessed and goes as dark data which further remains stockpiled in data repositories. The lack of required tools for analysis is another reason for the generation of dark data.

Referenced from the statements given by Bob Picciano, Senior VP of Analytics at IBM, “Data that is difficult to work with creates a high barrier to entry. People typically forego trying to get any information out of it. About 90% of data generated by most sensors and other sources on the market never get utilized, and 60% of that data loses its true value within milliseconds.”

Dark data can be employed by an organization to gain valuable insights which are even more valuable than the insights they are gaining presently, dark data is a subset of big data in a way and can be used for multiple purposes such as to analyze the network security in an environment.