Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Top tips is a weekly column where we highlight what’s trending in the tech world and list ways to explore these trends. This week, we’re looking at how you can reduce the amount of data you share online and minimize your digital footprint. How would you like it if someone followed you throughout the day, noting every single action you perform, every place you visit, and every interaction you have? Think about it; isn’t this exactly what happens when you use the internet?

Let’s start with the fundamentals: What is Address Resolution Protocol (ARP)? ARP is a vital networking protocol that ensures effective communication between devices on a local-area network (LAN). Its primary function is to map IP addresses to MAC addresses, allowing devices to recognize and communicate with each other within the network. ARP bridges the gap between the logical layer (IP addresses) and the physical layer (MAC addresses).

Cyber risk is the potentially negative impact to an organization when information systems fail or are damaged, disrupted or destroyed by unauthorized use or by cyberattack. In the world of risk management, risk is commonly defined as threat times vulnerability times consequence. The objective of risk management is to mitigate vulnerabilities to threats and the potential consequences, thereby reducing risk to an acceptable level.

AI training data has become a major concern as DeepSeek reached the top spot on the App Store, sparking debates about data privacy and national security. In a timely CNBC interview amid the DeepSeek controversy, Feroot Security CEO Ivan Tsarynny highlighted the critical intersection of data collection, AI development, and security risks. He emphasized how the data collected through apps plays a crucial role in AI advancements, raising further concerns about digital privacy.

A third-party data breach is a security incident where an organization's sensitive data is compromised or stolen due to a vulnerability or cyber attack on one of its third party vendors. This type of breach happens outside the primary organization's own IT infrastructure but still impacts them, as the third-party vendor, contractor, or service provider has access to their data.

It’s every security manager's worst nightmare. A member of the IT department reaches to alert that malicious software has been detected on an internal network, and the hacker potentially has access to layers of sensitive data.

Smartphones, smart homes, and virtual assistants like Alexa and Siri have seamlessly integrated into our daily lives. Yet, many of us rarely stop to think about the technology behind them. We enjoy the convenience these devices offer, but behind the scenes, artificial intelligence (AI) is reshaping the way we live, work, and interact with the world.

As enterprises continue to adopt hybrid and multi-cloud environments, the complexity of managing network security has increased significantly. Attack Surface Management (ASM) has emerged as a critical capability for identifying, monitoring, and mitigating risks across these dynamic environments. Forward Networks’ innovative digital twin technology delivers a compelling solution that addresses the challenges of effective ASM practices.

In 2024 threat actors were trying to abuse GitHub even more severely than before. There were detected thousands of “ghost accounts” spreading malware. Hackers were also trying to succeed in their malware campaigns using not only repositories but also comments. Moreover, multiple organizations that store their source code on GitHub have experienced data leakage and data breaches. Among those companies are The New York Times, Mercedes Benz, Ultralitics, etc.

DeepSeek’s latest large language models (LLMs), DeepSeek-V3 and DeepSeek-R1, have captured global attention for their advanced capabilities, cost-efficient development, and open-source accessibility. These innovations have the potential to be transformative, empowering organizations to seamlessly integrate LLM-based solutions into their products. However, the open-source release of such powerful models also raises critical concerns about potential misuse, which must be carefully addressed.