Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How to Ensure Data Privacy with AI: A Step-by-Step Guide

AI sits in everyday workflows: assistants answering customer questions, copilots helping developers, and RAG apps searching internal knowledge. That means personal and sensitive data flows through prompts, vector stores, and integrations you didn’t have a year ago. Privacy can’t be an end-of-quarter compliance push anymore. It needs to live in your pipelines and apps the way logging and monitoring do.

Securing AI Applications in the Cloud: Shadow AI, RAG & Real Risks | Mend.io

What does it take to secure AI-based applications in the cloud? In this episode, host Ashish Rajan sits down with Bar-el Tayouri, Head of Mend AI at Mend.io, to dive deep into the evolving world of AI security. From uncovering the hidden dangers of shadow AI to understanding the layers of an AI Bill of Materials (AIBOM), Bar-el breaks down the complexities of securing AI-driven systems. Learn about the risks of malicious models, the importance of red teaming, and how to balance innovation with security in a dynamic AI landscape. What is an AIBOM and why it matters The stages of AI adoption.

Hybrid Detection Architecture: Rules, ML, and LLMs in Concert

Security teams are drowning in complexity. Modern networks generate millions of events daily, attackers constantly shift tactics, and the tools meant to protect us often work in isolation, blind to what their neighbors are seeing. That mythical single solution that would catch everything? It's sitting in the graveyard next to perpetual motion machines and honest vendor pricing.

A CISO's Guide to the Business Risks of AI Development Platforms

The tools designed to build your next product are now being used to build the perfect attack against it. Generative AI platforms can spin up a pixel-perfect replica of your brand's login page in minutes, launching high-fidelity phishing campaigns at a scale and speed that legacy security models cannot handle. This isn't an emerging threat; it's an industrialized phishing engine that’s already being weaponized against businesses.

Snyk and Cognition partner to enhance security for AI-native development

Today, Snyk is excited to announce a new partnership with Cognition that significantly advances security within the software development lifecycle, validating our "Secure at Inception" model. This collaboration introduces new integrations, Snyk for Devin and Snyk for Windsurf, which directly embed Snyk Studio's security intelligence into Cognition's AI-native developer tools.

What is shadow AI and what can you do about it?

Organizations across industries are actively investing in AI to streamline operations, boost productivity, and stay ahead in competitive markets. However, most proceed with caution when rolling out new AI solutions internally as they need to meet standards for AI security, compliance, and responsible use through rigorous testing and assessments. ‍ At the same time, teams may occasionally adopt AI solutions outside formal channels to simplify their workload.

Building a Privacy-First AI Stack for Highly Regulated Industries

In a bid to quickly join the AI race, enterprises are steadily pouring time and money to adopt it. While designing a new AI tool, security and compliance are often an afterthought for developers and product managers. For industries that don’t handle sensitive data, AI adoption does not necessitate embedding strong privacy controls. However, highly regulated sectors like healthcare, finance, or government defence contractors can’t afford to launch without adhering to regulations.