Why Data Exfiltration Detection is Paramount?#
The world is witnessing an exponential rise in ransomware and data theft employed to extort companies. At the same time, the industry faces numerous critical vulnerabilities in database software and company websites. This evolution paints a dire picture of data exposure and exfiltration that every security leader and team is grappling with. This article highlights this challenge and expounds on the benefits that Machine Learning algorithms and Network Detection & Response (NDR) approaches bring to the table.
Data exfiltration often serves as the final act of a cyberattack, making it the last window of opportunity to detect the breach before the data is made public or is used for other sinister activities, such as espionage. However, data leakage isn’t only an aftermath of cyberattacks, it can also be a consequence of human error. While prevention of data exfiltration through security controls is ideal, the escalating complexity and dispersion of infrastructures, accompanied by the integration of legacy devices, makes prevention a strenuous task. In such scenarios, detection serves as our ultimate safety net – indeed, better late than never.
images from Hacker News