Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Phone scams have been around for decades, but the last few years have brought a sharp shift in how convincing they've become. Voice phishing, often called vishing, used to rely on generic scripts and a scammer's ability to sound believable. Today, the same technology that powers helpful tools like AI phone calling is also being studied and used to fight back against these scams.

Every large company works with dozens, sometimes hundreds, of outside vendors. From software providers to marketing agencies to hardware suppliers, enterprises depend on a wide network of partners to keep operations running smoothly. But before any vendor gets a seat at the table, they go through a process that can feel like a job interview crossed with a background check. This process is called vendor vetting, and it exists to protect the enterprise from risk, wasted money, and reputational damage.

Most brand impersonation starts in public. A lookalike support handle appears, replies to real customers under your official account, and links to a credential-harvesting page. By the time it reaches a takedown vendor's weekly report, the damage window has been open for hours.

AI video gets much harder the moment you ask it to tell a story. A single beautiful shot can hide a lot of weaknesses. Narrative work exposes them: the character has to remain recognizable, actions need to happen in the right order, camera changes have to make sense, and the next clip should feel as if it belongs to the same world. That is why we are not ranking these tools by the prettiest demo. We care about how useful they are for building scenes, maintaining visual direction, working from references and turning multiple clips into something that feels intentional.

Session replay has quietly become default infrastructure. Product teams want to see where users stall, support wants to stop asking "can you send a screenshot," and engineering wants a reproduction path for the bug that only happens on one customer's machine. The business case writes itself. The security review, in most organisations, never really happened. So when the question finally comes up - where does this stop being lawful? - most teams go looking for the answer in the wrong place.

A storage expansion often looks simple on a spreadsheet. The organisation needs more capacity, so the infrastructure team adds drives, another enclosure or another rack and moves on. The difficulty is that each expansion carries more with it than raw terabytes. More hardware can mean more power, more cooling, more cabling, more floor space and more equipment to manage later. That is why "more storage" and "storage that scales well" are not the same thing.

Selecting a hypervisor in the UAE is no longer just a technical infrastructure decision. For many enterprises, it now affects licensing predictability, data management, operational resilience, security, and access to regional support. As organizations continue their digital transformation initiatives, infrastructure teams are also reassessing long-standing virtualization platforms. Changes in VMware licensing and ownership have encouraged many enterprises to explore VMware Alternatives and plan potential VMware Migration strategies.

Shadow agents are quickly becoming one of the hardest visibility problems in enterprise security.

The most difficult AI incidents do not necessarily begin with an obviously malicious prompt. An employee can ask an approved agent to summarize customer data. The agent retrieves the correct records, invokes an approved tool, generates the requested output, and then sends it somewhere it should never have gone. Every individual action may look legitimate in isolation. The incident only becomes visible when security can reconstruct the entire sequence and understand what the user intended, what the agent inferred, which systems it touched, and where the execution path diverged.

It's no secret that AI has a significant presence in our daily lives these days. Many people hail it as a great way to save time and help them with basic tasks each day. The problem is, AI has become a part of nearly every single app, product, and device. AI has overreached the limits that the companies selling it promised. It's time for everyone to take action to ensure that AI products and companies are kept under control before they become problematic.