Most Security Pros Admit Shadow SaaS and AI Use
Next DLP study finds majority of security professionals have used unauthorised apps in past year
Data Loss Prevention detects and blocks sensitive information leaving approved systems, reducing breach impact when paired with access controls and monitoring.
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Data Loss Prevention (DLP) encompasses technologies and policies designed to detect and prevent unauthorized transmission or exposure of sensitive data outside an organization’s controlled environment. It monitors data in use, in motion, and at rest to block or alert on actions like copying, emailing, or uploading confidential information. DLP aims to reduce risks from insider threats, accidental leaks, or external attackers exploiting compromised accounts.
Effective DLP requires accurate data classification, contextual analysis of user behavior, and integration with access controls to minimize false positives and operational disruption. It is most relevant for protecting intellectual property, personal data subject to privacy regulations, and critical business information. While DLP cannot stop all data exfiltration attempts, it strengthens defense-in-depth by enforcing data handling policies and supporting forensic investigation of suspicious activities.
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Next DLP study finds majority of security professionals have used unauthorised apps in past year
Menlo Security’s latest report also revealed a 26% surge in security policies tailored for generative AI sites
The hacker breached the DLP company's internal update servers to deliver malware within its network