Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Risk management is evolving at a pace that compels organizations to adopt more advanced technologies. Among these, artificial intelligence is emerging as a leading force in transforming internal oversight practices, particularly in the realm of first-party risk management. The need to manage risks that originate within the organization has prompted leaders to reevaluate and innovate traditional strategies, making AI an indispensable component of modern risk frameworks.

Almost 30 years ago, two graduate students at Stanford University — Larry Page and Sergey Brin — began working on a research project they called Backrub. That, of course, was the project that resulted in Google. But also something more: it created the business model for the web. The deal that Google made with content creators was simple: let us copy your content for search, and we'll send you traffic.

Every time someone asks me about building their AI policy, I die a little inside. Not because it’s a bad question, but because my answer is always the same: “Can we not build it off pure fear for once?” Most people don’t understand how AI architecture works, so their first instinct is to panic. And, we’ve seen this movie before: cloud, mobile, bring your own device (BYOD).

June 2025 has seen WhatsApp back in the headlines—this time for all the wrong reasons. Earlier this month, The National broke the story: WhatsApp’s security is under renewed scrutiny following revelations that Israel remains the only known actor to have successfully exploited it. But if history has taught us anything, it’s this: if one nation-state can do it, others may follow. At Appknox, we decided to verify the current state of WhatsApp’s mobile app security for ourselves.

Trustwave's database protection solution, DbProtect, now supports Snowflake, which is a popular, cloud-based data warehousing platform used by organizations to power AI models and data-driven workflows. Snowflake's cloud-based architecture separates storage and compute functions, allowing organizations to scale each independently. The platform's ability to handle both structured and semi-structured data makes it a preferred choice for a broad range of AI and analytics applications.