Most mobile security conversations start with code: vulnerabilities, misconfigurations, tokens, and flaws. But few discussions focus on a critical dimension—location: not where an app is used, but where its data travels. In modern mobile architectures, dozens of services operate behind the scenes. SDKs phone home. APIs call upstream. CDNs redirect without warning. Within this chaos, a single, silent connection to a sanctioned region can escalate into a compliance crisis.

The National Institute of Standards and Technology (NIST) has unveiled a new metric that promises to revolutionize the way vulnerability management is prioritized. Likely Exploited Vulnerabilities (LEV) is a ranking designed to help organizations focus their efforts on the flaws that cybercriminals are actively using to perpetrate real-world attacks. Thousands of vulnerabilities are reported every year but only a small fraction is exploited in the wild.

In the ever-evolving world of retail, cyber threats are no longer a distant concern, they’re a daily reality. Over the past year, around 612,000 UK businesses reported experiencing a cyber breach or attack. Phishing remains the most common and disruptive method, targeting 85% of those affected. The retail sector, in particular, sits on a goldmine of customer data, credit card details, email addresses, and purchase histories, all of which are highly attractive to cybercriminals.

With the average phishing campaign now harvesting its first set of credentials in under 15 minutes , the efficacy of a detection strategy is measured in seconds, not hours.. Relying on scanning and takedown or traditional threat intelligence feeds – that inherently lag behind real-time user engagement – is no longer a viable defense against even unsophisticated credential theft and account takeover (ATO) scams.

If you are like me, a couple of years ago it was like I woke up to a new concept in the world of IT: the non-human identity. But, wait…this sounds very familiar. Haven’t we had service accounts and machines identities for performing automated tasks for many years now? In fact, I was on a development team that produced what is now known as RPA tools that helped automate repetitive IT tasks; an area highly used by many enterprises.