Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Your AI Agents Are Already Acting. The Question Is Whether You Can See What They're Doing.

In conversations with CISOs about their agentic environments, the question I ask first is not whether they have agents deployed. Most do. It is not whether those agents are creating value. Most are. The question I ask is whether they have mapped their Agentic Security Graph. Almost none of them have. And that gap, between the agentic infrastructure that exists inside their organizations and the visibility they have into it, is where the most serious AI security risk in the enterprise lives right now.

Extending Security to MCP Servers: Closing a Critical Gap

The Model Context Protocol (MCP) is a de facto standard for providing structured access to privileged systems for AI agents and external integrations. It acts as a USB-C port for AI, enabling faster innovation by allowing organizations to expose tools, resources, and workflows without the time-consuming work of building APIs. Adoption has surged in recent months, and categories like payments, project management, and developer platforms are already beginning to reap the benefits.

Security Features in Delivery Software

Delivery management software handles more than routes and driver schedules. It also processes customer names, addresses, phone numbers, delivery notes, payment references, proof-of-delivery records, driver locations, and operational data. That makes it a security-sensitive system. If the platform is poorly configured, attackers may access customer information, disrupt dispatch, manipulate delivery records, or expose driver activity.

The Security Trifecta: Operationalizing API Protection with AWS, Wallarm, and Coralogix

In the modern digital world, API’s are no longer just “connectors” – they are the real security product. Whether you are a Fintech processing payments, a SaaS platform managing multi-tenant data, or an E-Commerce giant handling the bulk of sales, your API’s are the foundation of your customer registration, checkout experiences, and partner ecosystems. However, that transition has made API’s the fastest-growing attack surface in history.

Kling Video 2.6 API: How to Build Automated Visual Simulation Workflows

The landscape of generative media has shifted from simple prompt-based experimentation to sophisticated, integrated production pipelines. With the release of Kling 2.6, the focus has moved toward "Native Audio-Visual Generation"-a breakthrough that allows developers to synchronize high-fidelity visuals with context-aware sound in a single automated step. For platforms focusing on digital senses and technical security, the Kling Video 2.6 API offers a robust framework for building simulations that were previously too resource-intensive to automate.

6 Lessons Security Leaders Must Learn About AI and APIs

Most organizations treating AI security as a model problem are defending the wrong layer. Security teams filter prompts, patch jailbreaks, and tune model behavior, which is all necessary work, while the actual attack surface sits largely unexamined underneath. That surface is the API layer: the endpoints AI systems use to retrieve data, call tools, and take action on behalf of users. This isn't a theoretical gap.