Shadow AI | Breaking Cybersecurity News | The Hacker News

As SaaS providers race to integrate AI into their product offerings to stay competitive and relevant, a new challenge has emerged in the world of AI: shadow AI.  Shadow AI refers to the unauthorized use of AI tools and copilots at organizations. For example, a developer using ChatGPT to assist with writing code, a salesperson downloading an AI-powered meeting transcription tool, or a customer support person using Agentic AI to automate tasks – without going through the proper channels. When these tools are used without IT or the Security team's knowledge, they often lack sufficient security controls, putting company data at risk. Shadow AI Detection Challenges Because shadow AI tools often embed themselves in approved business applications via AI assistants, copilots, and agents they are even more tricky to discover than traditional shadow IT. While traditional shadow apps can be identified through network monitoring methodologies that scan for unauthorized connections based on...

Early in 2024, Wing Security released its State of SaaS Security report , offering surprising insights into emerging threats and best practices in the SaaS domain. Now, halfway through the year, several SaaS threat predictions from the report have already proven accurate. Fortunately, SaaS Security Posture Management (SSPM) solutions have prioritized mitigation capabilities to address many of these issues, ensuring security teams have the necessary tools to face these challenges head-on. In this article, we will revisit our predictions from earlier in the year, showcase real-world examples of these threats in action, and offer practical tips and best practices to help you prevent such incidents in the future. It's also worth noting the overall trend of an increasing frequency of breaches in today's dynamic SaaS landscape, leading organizations to demand timely threat alerts as a vital capability. Industry regulations with upcoming compliance deadlines are demanding similar time-sens...

Every week seems to bring news of another data breach, and it's no surprise why: securing sensitive data has become harder than ever. And it's not just because companies are dealing with orders of magnitude more data. Data flows and user roles are constantly shifting, and data is stored across multiple technologies and cloud environments. Not to mention, compliance requirements are only getting stricter and more elaborate.  The problem is that while the data landscape has evolved rapidly, the usual strategies for securing that data are stuck in the past. Gone are the days when data lived in predictable places, with access controlled by a chosen few. Today, practically every department in the business needs to use customer data, and AI adoption means huge datasets, and a constant flux of permissions, use cases, and tools. Security teams are struggling to implement effective strategies for securing sensitive data, and a new crop of tools, called data security platforms, have appear...