Use cases
Information systems security: preventing leaks of sensitive information
Protect your sensitive information and prevent leaks with our information system security solution.
The need
Secure its information system:
Our customer, one of Europe's leading private bankers, wanted to minimize the risk of leaks of sensitive information (identities, financial transactions, etc.). As this type of leakage is most often due to internal malicious acts, the Information Systems Security Manager (ISSM) wanted to identify exhaustively the sensitive information present on the internal IS in order to better protect it.
Two questions arose:
- Where exactly are all the sensitive data held by the bank stored? Which databases? Which tables? Which columns? But also which files (notably Excel files and other listings scattered across the internal network)?
- What types of sensitive data are involved?
Proposed solution
Tale of Data helps you prevent data leakage from your information system.
Our "Mass Data Discovery" technology has enabled us to automatically scan:
- All relational databases
- Shared network drives: all directories and sub-directories were scanned for Excel, CSV, XML or JSON files.
- CRM and content management systems (e.g. Sharepoint)
The results were compiled at field level (whether in a database, Excel file or CSV listing): at the end of the scan we could say, for example, that the file aaa.xlsx, located in the directory x/y/z, contains N surnames in the 3rd field of the 2nd tab.
Benefits
To secure its information system, Tale of Data enabled data scanning (= "Bottom - Up" approach) and provided CISO with an exhaustive identification and localization of sensitive data.
The resulting map enabled security teams to greatly minimize the risk of data leakage:
- By tracking down queries that they had previously thought to be innocuous (= any SQL query that went back to columns on the list of sensitive columns established by the mapping).
- By systematically checking access to network directories that they didn't previously know contained sensitive data listings.
- By checking the effectiveness of anonymization procedures: cross-referencing (= fuzzy Tale of Data joins) anonymized files with a list of known clients should not normally generate any matches.
- By controlling the risk of leakage over time through regular scans: up to several times a day. In fact, new listings may appear on the network for a few hours just before a leak.
Product Benefits
Integrate
Seamless integration of AI and No-Code technology for effective data refinement.
Collaboration
Shareable
Visualize
Powerful
Quality
Achieve superior data quality faster and at a lower cost, while demonstrating the tangible value of investing in data excellence.