Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

As enterprise data moves across applications, databases, and analytics pipelines, uncontrolled proliferation of PII increases compliance risk and a potential breach. IT leaders and product managers are often struggling to find the best way to protect data. Protecto Vault helps organizations contain this risk by centralizing PII governance and offering two powerful architectural models to minimize data exposure – the Tokenization Model and the Centralized Profile Model.

Sha1-Hulud has burrowed back into our lives, spreading rapidly and causing more destruction than ever. Named after the famous worm from the Dune franchise, this attack is also impacting global organizations. Since its first widescale spread on September 16, 2025, this worm has demonstrated its ability to propagate rapidly with high impact using the following techniques: This variant includes some new behavior, including.

The Ivy League is the promised land for thousands of high school students, but it has also become a target for cyberattackers. Three of the most prestigious universities in the United States suffered sophisticated cyberattacks in fall 2025. Harvard University, Princeton University and the University of Pennsylvania have all disclosed data breaches that compromised sensitive information about alumni, donors, students and faculty members.

You may not often think about how far computer security has come over the last 30 years; the evolution is remarkable. Early attacks, such as viruses, passed around on floppy disks, worms spreading for notoriety, and hacktivism done for a cause felt more punk rock than organized crime. Today, according to Canalys, ransomware is the top concern for small businesses. But will it stay that way?

Picture this: an organization rolls out a small policy update on a Friday evening, expecting to fix a few login issues. By Monday morning, half the users can’t access their accounts, help desk tickets are flooding in, and the IT team is scrambling to trace what went wrong. That’s how quickly a single misconfiguration in Active Directory can snowball into a full-blown business disruption.

In today’s digital landscape, the volume and complexity of cyber threats are staggering. Security teams are constantly drowning in a tsunami of data—raw threat feeds, security alerts, and endless reports. Consequently, this data overload leads to alert fatigue, making it nearly impossible to distinguish a critical, targeted attack from simple digital background noise. Furthermore, if you’re relying on manual processes and disparate tools, you’re always playing catch-up.

Security leaders are asking a new question with greater urgency: How exposed are we? In an era where every application, identity, and integration expands the attack surface, answering that question with clarity is no longer optional. The traditional model of vulnerability management cannot keep up. Findings come in faster than they can be addressed. Visibility is fragmented. Risk prioritization is often based on severity scores rather than business impact.

German cybersecurity teams are making meaningful progress in exposure management, but critical gaps remain that limit their ability to reduce business risk. That’s one of the key takeaways from Bitsight’s State of Cyber Risk and Exposure 2025 report, which surveyed 1,000 cyber risk professionals globally, including 150 based in Germany.

This is the second in our Retail Resilience series. Check out the first article, Cyber Risk in UK Retail: A Golden Quarter Under Threat Threat actors have retail firmly in their sights. High profile breaches across giants, from Cartier, Co-op and Adidas to Marks & Spencer, underscore just how much is at stake. With sprawling customer data, complex supply chains and relentless digital transformation, the sector is a prime target for sophisticated threat groups.

‍ AI has moved from experimentation to everyday infrastructure, shaping decisions and workflows across nearly every industry. However, in the rush to harness its speed and efficiency, many enterprises adopted GenAI and other AI systems faster than they built the structures necessary to govern them. The result is an all-too-familiar pattern of powerful technology being deployed widely before its risks are fully understood, let alone managed. ‍