Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

From Discovery to Defense: Why AI Red Teaming Is the Next Step After AI-SPM

This week, we announced the general availability of Evo AI-SPM, the first operational layer of Snyk’s AI Security Fabric. AI-SPM gives security teams something they’ve never had before: a system of record for AI risk, with the ability to discover models, frameworks, datasets, and agent infrastructure embedded directly in code. For many organizations, that discovery step is a breakthrough.

Trustworthy AI Starts with Better Agents

The difference between an AI feature and an AI-led operating model becomes clear the moment a security problem becomes difficult. In real-world security operations — where the signal is ambiguous, the evidence spans multiple domains, and the attacker is behaving in unfamiliar ways — architecture matters much more.

Non-Human Identity Sprawl Is the Hidden Cost of AI Velocity

In the current AI boom, we race to use copilots, orchestration scripts, CI workflows, retrieval pipelines, and background jobs. Sometimes, we take for granted that every one of these things needs an identity. Service accounts. OAuth apps. API keys. Short-lived tokens. As AI velocity increases, so does the number of these non-human identities (NHIs). Instead of obsessing over model quality, latency, hallucinations, and GPU costs, we also need to consider how these identities impact security.

Agentic commerce is happening now. Here's what we've learned.

We’ve been collaborating with others to explore when and how agentic commerce will work. Robin Gandhi is the CPO of Lithic, a leading card issuer that’s already seeing agents use its cards to make purchases. Below, he shares his thoughts on what’s changed, and what needs to change, for agentic commerce to become mainstream. Last year, I wrote about the opportunity for agentic payments to revolutionize travel bookings, ad spend management, procurement, and more.

AI can do what now?! - Detecting financial fraud with Elastic Security

Financial fraud is increasingly cyber-enabled, requiring organizations to detect complex campaigns across transactions, identities, and digital systems faster and with greater accuracy. Join cybersecurity experts Lisa Jones-Huff and Joe Murin as they discuss how Elastic Security applies AI, machine learning, and generative AI to modern fraud detection. They’ll share how Elastic Security helps teams connect signals, reduce noise, accelerate investigations, and scale fraud prevention through emerging frameworks and standards across financial services organizations.

How Charlotte AI AgentWorks Fuels Security's Agentic Ecosystem

The era of human-speed defense is over. With eCrime breakout times collapsing to as fast as 27 seconds and attacks from AI-powered adversaries increasing 89% year-over-year, the traditional SOC has reached a breaking point. Manual processes, fragmented tools, and rule-based playbooks were built for a different era. Today, if your defense depends on human reaction time, you’re not just behind — you’re at risk.

Unify Kubernetes, VMs, and AI with VCF 9

Managing modern IT infrastructure often feels like balancing completely different ecosystems. For years, organizations have run separate, hand-built, Kubernetes stacks on top of legacy virtualization platforms. Due to security concerns, it just made sense to build a separate, tailored container environment that they could automate and schedule their exact needs. This fragmented approach leads to inconsistent security policies, fragile integrations between clusters, and operational silos.

WebPromptTrap - New Indirect Prompt Injection Vulnerability in BrowserOS

Cato researchers have discovered a new indirect prompt injection exploit pattern workflow in BrowserOS (an open-source agentic AI browser). We named it “WebPromptTrap” because the prompt originates from untrusted web content and it traps users into approving an authorization step through a trusted-looking AI summary.

Spring 2026 GenAI Code Security Update: Despite Claims, AI Models Are Still Failing Security

The last six months have been nothing short of revolutionary for AI-powered coding. OpenAI‘s “Code Red” release brought us GPT-5.1 and 5.2. Google unveiled Gemini 3 with its touted “unprecedented reasoning capabilities.” Anthropic rolled out Claude 4.5 and 4.6, powering the increasingly ubiquitous Claude Code features. Enterprise adoption of tools like OpenClaw has exploded, with developers praising unprecedented productivity gains.