Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The Imperative of Data Loss Prevention in the AI-Driven Enterprise

As organizations increasingly integrate artificial intelligence (AI) into their operations, the nature of data security is undergoing significant transformation. With AI’s ability to process vast amounts of data quickly, the risk of data breaches and leaks has grown exponentially. In this context, Data Loss Prevention (DLP) has (re)emerged as a critical component for IT professionals seeking to safeguard sensitive information.

How Cybersecurity Risk Assessments Will Need to Evolve for 2025

2025 is drawing near, and the cybersecurity scene is changing quickly. Organizations must adapt how they undertake cybersecurity risk assessments in tandem with the ongoing evolution of technology and the escalating sophistication of cyber-attacks. In order to address the difficulties of the near future, cybersecurity risk assessments will need to change in ten key areas, as this essay examines.

How to mitigate security issues in GenAI code and LLM integrations

GitHub Copilot and other AI coding tools have transformed how we write code and promise a leap in developer productivity. But they also introduce new security risks. If your codebase has existing security issues, AI-generated code can replicate and amplify these vulnerabilities.

Customers get increased integration with Cloudflare Email Security and Zero Trust through expanded partnership with CrowdStrike

Today, we’re excited to expand our recent Unified Risk Posture announcement with more information on our latest integrations with CrowdStrike. We previously shared that our CrowdStrike Falcon Next-Gen SIEM integration allows for deeper analysis and further investigations by unifying first- and third-party data, native threat intelligence, AI, and workflow automation to allow your security teams to focus on work that matters.

Wallarm Innovation Update: Effective API Protection With GraphQL And API Policy Enforcement

With its exceptional ability to improve application flexibility, performance, and user experience, GraphQL is rapidly becoming one of the most widely adopted API protocols, with Gartner predicting that by 2025 it will be implemented by over 50% of enterprises. However, the same flexibility that makes GraphQL such an attractive protocol, however, also makes it susceptible to a variety of unique attacks.

7 Examples of How AI in Data Security is Transforming Cybersecurity

AI in data security transforms how organizations protect sensitive information. Companies turn to artificial intelligence for robust defense mechanisms as cyber threats evolve. This cutting-edge technology analyzes vast datasets, identifies patterns, and responds to threats in real-time, surpassing human capabilities. From small businesses to large enterprises, AI-powered solutions guard against increasingly sophisticated attacks.