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The Latest Cybersecurity News & Insights From Around The World
The API Security Dilemma: Why Traditional Approaches Are Failing in the AI Era
Throughout the past few years, APIs have become the backbone of digital infrastructure. They enable software-to-software communication, improve integration and interoperability, support modular architecture, and more. But as API use has exploded, so has API traffic volume and complexity, making them increasingly difficult to secure. And the rise of AI agents and automation have complicated matters further. The result? APIs have become a favourite attack vector for cybercriminals.
Securonix - Breach Ready. Board Ready. AI-Powered.
Security teams today are expected to do it all. Stop threats faster. Prove value to the board. Scale with fewer resources. Securonix makes it possible. Breach Ready means unified detection and response with up to 60 percent faster time to containment and 50 percent less analyst workload. Board Ready means 193 percent ROI, a six-month payback period, and reporting that drives strategic decisions. AI Powered means modular agents that cut false positives by 90 percent and automate triage with precision, keeping your team in control. This is modern security. This is Securonix.
Trustwave Security Colony's 8 Commandments for AI Adoption
The advent and continuing widespread adoption of artificial intelligence for basic research, document creation, code writing, or any other purpose increases an organization’s threat level if done incorrectly. However, when an organization implements AI as a tool in a thoughtful and well-considered manner, it can be a great benefit.
Securing AI Transformation: Why Cato Networks Acquired Aim Security
Every major technology wave reshapes enterprise security. The rise of the Internet gave us firewalls. The move to SaaS brought CASB and DLP. The migration to the cloud and rise of the hybrid workforce demanded a new architecture like SASE to enable network transformation. Today, the AI revolution is creating an entirely new attack surface – one that is as transformative as it is urgent.
What AI Means for Your Cybersecurity!
Understanding AI security threats before they become your next crisis On this episode of Razorwire, I explore the emerging frontier of AI security with leading experts Jonathan Care and Martin Voelk. We examine the latest risks, show you how adversaries are exploiting AI systems and share practical advice for professionals working with these rapidly advancing technologies.
Context-Driven Guardrails: The Future of AI Security
Context-Driven Guardrails: The Future of AI Security How do you protect AI and LLMs without slowing them down? A10 Networks' security experts Jamison Utter, Madhav Aggarwal, and Diptanshu Purwar share why context-driven guardrails are the future of AI security.
Securing LLM Superpowers: When Tools Turn Hostile in MCP
In Part 1 of this blog series, we explored the architecture, capabilities, and risks of the Model Context Protocol (MCP). In this post, we will focus on two attack vectors in the MCP ecosystem: prompt injection via tool definitions and cross-server tool shadowing. Both exploit how LLMs trust and internalize tool metadata and responses, allowing attackers to embed hidden instructions or persistently influence future tool calls without direct user prompts.
The CSA AI Controls Matrix: A Framework for Trustworthy AI
The Cloud Security Alliance, a respected non-profit founded in 2008 to pursue cloud security assurance, has now unveiled its Artificial Intelligence Controls Matrix (AICM), a quiet revolution for trustworthy AI. It has come at a time when generative AI and large language models are moving quickly into every sector. These systems can transform business, but they can also fail, or be made to fail. Because of this, trust becomes the measure of success.
Examples of AI Privacy Issues in the Real World
What’s the fastest way to lose trust? Expose private data. With AI moving from pilots to core workflows in support, finance, HR, and healthcare, one careless prompt or leaky integration can turn into headlines, fines, and weeks of incident response. The most useful way to understand the risks is to study AI privacy issues examples from the real world.