Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The continuous changes in software development bring with them the necessity for the DCAS model – an amalgamation of development and operations processes – to quickly support the delivery of a top-quality product.

Can you believe it? The holiday season is finally here! For many of us, that means nostalgic traditions, quality time with family, and—let’s be honest—a significant amount of online shopping. The convenience of browsing for gifts from the comfort of our homes is undeniable, especially in our hybrid work environment. However, this surge in digital activity and scams also signals the busiest time of year for cybercriminals.

Artificial intelligence is no longer just an overused buzzword; it’s a fundamental shift in how businesses operate. The Architects of AI were just named as Time’s person of the year for 2025. From generative AI creating code to machine learning algorithms optimizing supply chains, the demand for AI is reshaping the technology landscape. But here’s the thing: all that computational power is useless if your data can’t move fast enough.

The image of the cyber attacker is changing. For years, the industry focused on email gateways and typo-squatted domains like citi-bank-security.com. But according to Tzoor Cohen, CTI Lead at Memcyco, the battleground has shifted. In 2026, the most dangerous social engineering tactics typically don’t start in an inbox. They start on social media, utilize legitimate infrastructure like Bitly, and exploit the user interface (UI) of mobile devices to hide malicious intent.

A critical code injection vulnerability has been identified in Apache Commons Text, a widely used Java library for text processing and interpolation. Tracked as CVE-2025-46295, the vulnerability carries a CVSS v3 score of 9.8 (Critical) and affects all versions of the library prior to 1.10.0. The vulnerability has an EPSS score of 0.253%, indicating a low short-term probability of exploitation.

Remember when open meant visible? When a bug in open-source code left breadcrumbs you could audit? When you could trace commits, contributors, timestamps, even heated 2:13 a.m. debates on tabs versus spaces? That kind of openness created confidence in the code and made it possible to hold contributors accountable when issues arose. Today, as AI changes how code is created and shared, those familiar markers of trust and transparency are becoming harder to find.