Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The Internet of Things (IoT) ecosystem is expanding rapidly, connecting billions of devices across industries. While this connectivity drives efficiency and innovation, it also introduces massive cyber risks. The IoT ecosystem is an interconnected environment of devices, systems, and technologies, making security especially complex. Attackers are increasingly using automation and artificial intelligence (AI) to launch sophisticated attacks at scale.

Mobile app security can’t afford surface-level assessments. To truly verify how apps handle compromise, security teams must venture deeper, and in the iOS world, that means jailbreaking. Jailbreaking an iOS device grants pentesters the access required to uncover weaknesses otherwise invisible under Apple's sandboxing model. By removing Apple’s built-in restrictions, testers gain deeper access to system files, APIs, and hidden behaviors that standard tools can’t expose.

AI has redrawn the cyber battlefield. Adversaries are already automating every phase of the kill chain to strike faster, scale wider, and overwhelm defenders. Manual workflows and conversational assistants help teams move faster, but still bind them to human speed. Agentic AI changes the equation. It enables security teams to deputize trusted, mission-ready agents that reason, decide, and act on their behalf — at the speed of AI. The promise of agentic AI is clear.

Security leaders are well acquainted with Shadow IT; the unsanctioned apps, services, and even devices employees adopt to bypass bureaucracy and accelerate productivity. Think rogue cloud storage, messaging platforms, or unapproved SaaS tools. These all often slip past governance until they trigger a breach, compliance issue, or operational failure. Now, a more complex threat is emerging - Shadow AI.

AI is now part of customer service, product design, operations, and decision making. That reach brings real benefits, and it also surfaces personal and sensitive data in new places. It raises the question: How do we ship useful AI while protecting people and meeting laws? This guide helps you understand AI and data privacy as one practice through core principles, common pitfalls, practical controls, and a step by step plan to build privacy into your AI stack from the start.

API security breaches have reached a crisis point, with 57% of organizations experiencing API-related breaches in the past two years. Only 13% of organizations can prevent more than 50% of API attacks, while 84% of security professionals experienced an API security incident in the past year. The average cost to remediate API incidents was $591,404 in the United States, increasing to $832,801 in the financial services sector.

How AI can transform even Microsoft's own documentation to meet its style standards.