The General Data Protection Regulation (GDPR) is a comprehensive data protection law covering the European Union (EU) and is widely regarded as one of the world’s strictest privacy regulations. The GDPR unifies data regulation within the EU and provides individuals control over their personal data. The GDPR includes information about Data Protection Officers (DPOs).

Social engineering and phishing are involved in 70% to 90% of all successful cybersecurity attacks. No other initial root hacking cause comes close. This is not a recent development. Social engineering has been the number one type of attack since the beginning of networked computers. Despite this long-time fact, most organizations do not spend 3% of their IT/IT Security budget to fight it.

New analysis of incident data shows threat actors are evolving their attack techniques to take advantage of budget and resource-strapped small businesses. We’ve seen industry data showing that cybercriminals have been slowly creeping downward from solely going after enterprises to targeting the SMB.

One of the biggest issues facing government and industry is how to securely share sensitive and classified information. While information sharing and collaboration have tremendous benefits for productivity and service outcomes, they do come with risks. A dynamic, data-centric approach is key to securing sensitive information and achieving compliance.

In the busy domain of artificial intelligence (AI), the emergence of Private Language Model Models (LLMs) marks a pivotal development in addressing the escalating concerns surrounding data protection. As organizations harness the power of AI to glean insights and streamline operations, the need for safeguarding sensitive information has become more pronounced than ever.

Netskope Threat Labs has observed an evasive Azorult campaign in the wild that employs multiple defense evasion techniques from delivery through execution to fly under the defender’s radar as it steals sensitive data. Azorult is an information stealer first discovered in 2016 that steals sensitive information including user credentials, browser information, and crypto wallet data.

In order to prevent worst-case data leak and data loss scenarios, security teams need to have both proactive and reactive measures in place. Let’s explore this further with an example. Imagine your sensitive data as valuables within a house. There are multiple ways to secure that house, including the following. To put this example into practice, security teams would need to: The first and last of these bullet points fall under the umbrella of SaaS Security Posture Management, or SSPM.