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Pricchaa releases Best Practices Guide for managing Data Breach Risks in MongoDB
Several recent data breach incidents involved misconfigured MongoDB databases. MongoDB is a popular open source document database for big data and often used for storing sensitive data including Personally identifiable information (PII) and Protected Health information (PHI) data. Off late, Data breach has become a business reality. It is no longer a question of if but when. As businesses leverage the power of big data, cloud, and internet of things to deliver new services and products, they need to take appropriate steps to manage and mitigate the data breach risks.
Security researchers1 found many MongoDB servers running in publicly accessible space on the internet. In the absence of appropriate security protocol, this often resulted in data breaches. Following list highlights some of the recent data breach incidents involving Mongo DB.
· Oct,2016 – Hacker stole 58 million customer information from MongoDB database of Modern Business Solution2- A Texas-based data management solution provider.
· Jun,2016 – Hacker leaked 36 million+ Mongo DB accounts3
· Apr, 2016 – AWS hosted MongoDB configured incorrectly – No password was required to access this database - resulting in data exposure of 93 million Mexican voters4.
· Dec, 2015 – A MongoDB database exposed personal information of over 191 million US voters5
"With accelerating adoption of MongoDB-based big data repositories, the detection and protection of sensitive information has become an imperative."
Pricchaa's leading product Alpha is the Lightening fast in-process solution to detect sensitive information within Big Data repositories. Alpha leverages predefined and custom configured logic to inspect all transactions housed within various repositories such as HDFS (Apache, MapR, Cloudera, Hortonworks)
About Pricchaa inc.
Pricchaa is a Chicago based company that provides software for sensitive data detection and protection. It has 20+ years of experience in implementing data governance and machine learning algorithms in fortune 1000 companies.