Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The challenge isn’t just that AI agents are new. It’s that they blur traditional boundaries of data control, creating hidden sub-processors and uncontrolled data flows. For CISOs, compliance officers, and security leaders, this presents a fundamental governance problem: if you don’t know which AI services are touching your data, you cannot prove compliance.

In August 2025, AWS made native support available to deploy AWS Lambda functions straight from GitHub Actions. With this integration, a lot of the complexity developers have had to undergo conventionally with serverless automatic deployment is eliminated. As a valuable practical improvement, teams will now gain the ability to utilize declarative GitHub workflows with OIDC-secured authentication and auto-packaging of code for simpler CI/CD pipelines.

Manual ticketing slows response time and invites errors. Forward Networks simplifies this by detecting drift, anomalies, or changes—and automatically creating ServiceNow incidents based on verified data. Incidents are enriched with hostname, config diff, device roles, and severity, saving time and ensuring accuracy. Implementing change management for network modifications has multiple benefits.

What if a single developer pastes sensitive code into a chatbot and, in seconds, exposes your company’s most valuable secrets? That’s not a thought experiment. Incidents at Samsung, Amazon, and other enterprises show how generative AI can turn everyday work into an unintentional leak.

As Generative AI revolutionizes businesses everywhere, security and IT leaders find themselves in a tough spot. Executives are mandating speedy adoption of Generative AI tools to drive efficiency and stay abreast of competitors. Meanwhile, IT and Security teams must rapidly develop an AI Security Strategy, even before the organization really understands exactly how it plans to adopt and deploy Generative AI.

Large Language Models (LLMs) are rapidly evolving from impressive information retrieval tools into active, intelligent agents. The key to unlocking this transformation is the Model Context Protocol (MCP), an open-source standard that allows LLMs to securely connect to and interact with any application — from Slack to Canva, to your own internal databases. This is a massive leap forward.

Application Security Posture Management (ASPM) is a unified intelligence layer that transforms scattered security data into actionable business insights. Why should you care about this new security approach when you already have a working structure in place? To understand this, let’s first look at the security approach that enterprises usually follow and why it is dated.

In late July, we published new research on the risks of unmanaged AI, revealing four major security challenges companies face when AI slips under the radar.

The number of connected devices worldwide is projected to surpass 29 billion by 2030. From healthcare IoT and industrial OT to smart vehicles and critical infrastructure, these devices are now central to operations and innovation. The rapid evolution of IoT technology and its widespread adoption across industries have introduced new opportunities, but also new risks.