Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How AI-Powered Tools Are Revolutionizing Online Education security

Let's face it: the digital shift in education is permanent. Virtual classrooms, remote assignments, cloud-based exams-these are no longer futuristic concepts; they're the present-day norm. But while the benefits of flexibility and accessibility are undeniable, the vulnerabilities lurking beneath the surface are equally real. Imagine a scenario: a student logs into a popular education app from a public Wi-Fi network. That very act, innocent on the outside, can be a digital goldmine for cyber intruders if the platform lacks proper safeguards.

Why AI Trust Will Shape Your Next Decade of Software Development

AI is often compared to electricity, but without trust, it’s just a live wire. As organizations adopt AI to move faster, reduce manual effort, and push the boundaries of what’s possible, one truth is becoming clear: trust in AI isn’t optional. It’s foundational. And for software development teams, AI Trust is now the north star that guides safe, scalable innovation.

The privacy illusion: when deleting your data doesn't actually delete your data

Let’s talk about privacy—specifically, the kind you thought you had when you hit “delete.” OpenAI received a court order to retain every single ChatGPT conversation, even the ones you erased. Yep. Even the awkward ones. Even the ones that start with, “Hypothetically, if I were to…” Why? Because The New York Times is suing them over copyright, and now everyone’s deleted chats are potential evidence.

Defending at Machine Speed: Guiding LLMs with Security Context

Large Language Models (LLMs) provide strong reasoning and data summarization capabilities, making them valuable proxies for a variety of cybersecurity operations tasks. However, their performance can decline when applied to highly specific or enterprise-contextual tasks, particularly if the models rely solely on public internet data.

CISOs Brace for a Wave of AI-Powered, Domain-Based Cyber Threats

Domain-name system (DNS)- based cyber attacks are becoming increasingly complex, and AI will only make managing them even more challenging. According to a recent report, Chief Information Security Officers (CISOs) anticipate a tumultuous season of cyber threats, with low confidence in their abilities to defend against them effectively.

First Look, Then Leap: Why Observability is the First Step in Securing your AI Agents

AI Agents aren’t coming - they’re already here! reshaping industries, enhancing productivity, and unlocking new possibilities. Embedded in tools like Microsoft 365 Copilot, Salesforce Einstein, and custom-built assistants, they’re making decisions, automating workflows, and interacting with sensitive business data in real time. This wave of innovation is moving fast, but for once, security doesn’t have to play catch-up.

The future of identity security Is AI-driven but human-led

Cyber threats continue to move faster, operate smarter and hit harder than ever before. Against this backdrop, one truth has emerged: identity is the new perimeter – your people’s digital identities are the new front line of defense. And that brings identity into focus for every attacker. To truly protect your business, you need an AI-enabled, dynamic, intelligent, unified Identity Fabric to deliver next generation protection and control without impacting productivity.

Building AI Trust with Snyk Code and Snyk Agent Fix

Many businesses are using AI to innovate and boost productivity. But to truly benefit from AI, you need to trust it. That's where the Snyk AI Trust Platform comes in. As we announced at the 2025 Snyk Launch, the Snyk AI Trust Platform is designed to unleash innovation, reduce business risk, and accelerate software delivery in the age of AI.

Scan your AI-generated code from Cursor using Model Context Protocol (MCP)

We’re happy to announce that Cursor has validated Snyk’s CLI MCP server and added Snyk to their curated set of MCP tools from official providers. At Snyk, we recognized early on that although AI assistants accelerate development, they can inadvertently introduce vulnerable patterns, leverage outdated libraries, or even code with known security flaws. In order to maintain the rapid iteration cycles that AI enables, developers need security to be as agile as AI itself.