Unpatched software: The silent gateway to cyber attacks and how AI-driven solutions can close the gap


Modern enterprises are under fire from all angles. Attackers have become increasingly sophisticated and persistent in how they target enterprise data and systems. But as the threat landscape has evolved and become more complex, one tried and true method for malicious attackers stands out as a weak point for nearly every enterprise attack surface: outdated software. As much as patch management has advanced in recent years, the fact remains that most organizations struggle to deploy patches consistently and effectively, and that leaves systems exposed to cyber attacks.
Cybercriminals have become quite adept at exploiting unpatched software, using it as an easy entry point into enterprise networks. Malicious actors have developed an incredibly sophisticated understanding of where enterprise weak points are. In fact, most criminal operators have a deeper understanding of enterprise attack surfaces than the security teams tasked with defending them. Enterprise networks often consist of hundreds of thousands of IT assets, and every single unpatched instance represents an opportunity for attackers to compromise data and operations.
Crossing the divide: How IT and OT can work together to secure the future


In cybersecurity, the divide between IT (Information Technology) and OT (Operational Technology) remains a problem that practitioners, vendors, and consultants must navigate daily. The differences between these two mindsets -- one rooted in the world of delivering data and maintaining software, the other firmly planted in the realm of continuous uptime of industrial systems -- can lead to conflicting priorities and misunderstandings. Even as the industry strives to align these domains, this divergence is still evident, as I was reminded just this week.
During my usual morning LinkedIn browsing, I stumbled upon a post featuring the “Top 50 People in ICS/OT Cyber Security You Need to Follow”. At first glance, I panicked. My immediate assumption was that the list featured individuals responsible for securing operational environments -- the unsung heroes safeguarding critical infrastructure around the globe.
IT industry today faces same issues that aggravated 1990s manufacturing: How can we take a cue from history?


Until the late 1990s, manufacturing reigned as the lifeblood of the global economy -- leading in productivity, employment, growth, and investments across all points of the world. However, once we neared the close of the 20th century, manufacturing found its Achilles heel in the compounded complexity accrued from outdated processes, an over-reliance on human labor that simply couldn’t meet its extreme needs, supply chain disruptions, and rising costs.
I fear that today, the information technology industry finds itself at all-too-familiar cross-roads. Why is this?
Celebrating Data Privacy Day: Ensuring ethical agentic AI in our daily interactions


Both AI agents and agentic AI are becoming increasingly powerful and prevalent. With AI agents, we can automate simple tasks and save time in our everyday lives. With agentic AI, businesses can automate complex enterprise processes. Widespread AI use is an inevitability, and the question going forward is not if we’ll use the technology but how well.
In a world where AI takes on more responsibility, we need to know how to measure its effectiveness. Metrics like the number of human hours saved or the costs reduced are, of course, important. But we also need to consider things like how ethically and securely our AI solutions operate. This is true when adopting third-party solutions and when training AI in house.
Trump is back -- here’s what it means for IoT


On January 20, Donald Trump was inaugurated to the highest office in the United States of America. If his last four-year term contains hints about his next four-year term, the tech sector can expect more protectionist policies reflected in tariffs, trade wars, and production.
For connected devices in the Internet of Things, this means flow-on effects in manufacturing supply chains and potentially stricter cybersecurity oversight. Let’s explore.
Hyper-personalization is here -- but are organizations ready?


The rising demand for relevant, convenient and personalized customer experiences across all sectors has put modern organizations under pressure to adapt. McKinsey reports that almost three quarters of buyers now expect personalized interactions. The choice is clear: either embrace personalization, with individual offers or tailored updates based on previous habits, or risk falling behind competitors with a standardized approach.
Many organizations already do this well. From personalized Netflix movie recommendations to tailored Google adverts built on previous searches, organizations are able to delight customers with tailored services.
Data privacy in 2025: The resurgence of biometric security, a fleeting forecast for federal data privacy regulations, and the return of the wild west of AI


The transition from 2024 to 2025 brings a lot of uncertainty, speculation, and hopefully some optimism for the world of data privacy.
As technology continued to innovate, securing data grew more complex and consumers grew more concerned over how their information was being used. Regulatory changes are coming soon, with several states providing their own data privacy standards in anticipation of a shifting focus within the U.S. federal government, creating an important inflection point to set the tone for the future of data privacy and security.
The UK's cybersecurity landscape: Key trends and challenges for 2025


Almost every single organization, large or small, is acutely aware of the need to implement robust security measures. However, this is easier said than done. As the threat landscape continues to evolve, only heightened by tools such as AI, it can be difficult to stay ahead and ensure appropriate security measures are in place. There are a lot of security tools out there, and many organizations have tried to implement security measures and are now overwhelmed with an influx of information trying to figure out how best to manage it.
However, though it may not be the easiest task, it’s certainly one worth doing right. So, as we move into 2025, what are the main trends that organizations need to be aware of and how can they use this knowledge to stay protected?
2025: The year of evolution in identity security


The year 2025 will not be a revolutionary one, it will be evolutionary, with developments coming into effect that were necessitated by events and happenings in 2024, and solutions to address these events reaching maturity levels that allow an appropriate, comprehensive response. With threats like ransomware certain to continue, identity resilience is going to become more important in the year ahead and, as such, identity will become the critical component of security.
This shift in emphasis started to take place in 2024, but there will be a greater focus on it among business leaders in the year ahead as they start to understand that identity is one of the biggest threats to any organization as it is a key vector for attackers.
Active metadata: The key to unlocking data's full potential


Data-driven organizations are increasingly struggling with the limitations of passive metadata practices. These traditional approaches quickly become outdated, leading to inaccurate insights and poor decision-making. Passive metadata often remains siloed, making it challenging to integrate and understand relationships between datasets. As a result, organizations face significant hurdles in achieving data agility -- the ability to adapt how information is interpreted and rapidly acted upon.
Active metadata management solves these challenges by providing a dynamic, intelligent layer that enables businesses to improve their decision-making processes and maintain a competitive edge in an increasingly data-centric environment.
Companies have to address the risks posed by GenAI


Even though it’s only been two years since the public demo of ChatGPT launched, popularizing the technology for the masses, generative AI technology has already had a profound and transformative effect on the world. In the years since the platform’s launch, critics have regularly pointed out the risks of generative AI and called for increased regulation to mitigate them. Once these risks are addressed, companies will be more free to use AI in ways that help their bottom line and the world as a whole.
We must remember that artificial intelligence is a powerful tool, and as the adage goes, “With great power comes great responsibility.” Although we have seen AI make a positive impact on society in several ways -- from boosting productivity in industrial settings to contributing to life-saving discoveries in the medical field -- we have also seen wrongdoers abuse the technology to cause harm.
2025 predictions -- Navigating through the challenges and opportunities ahead


As we head further into 2025, the global economic landscape remains a mix of challenges and potential shifts that will shape markets and industries worldwide. From high interest rates to the evolving impact of AI, there are several key factors that will define the year ahead. While there will be friction in some areas, persistence, agility and out-of-the-box thinking will ensure a competitive edge.
The economic slowdown in the European Union (EU) and the UK will likely persist into 2025, with high interest rates continuing to weigh on consumer spending and business investment. Central banks’ inflation-control measures are dampening growth, making a swift recovery unlikely. Governments will be under pressure to boost the economy through fiscal policies, increasing social program spending and infrastructure investments. The success of these efforts will depend on how quickly businesses adjust to a more cost-conscious climate and how consumers respond to rising financial pressures. The balancing act between controlling inflation and sustaining growth will be the key to success in 2025.
Harnessing AI to drive team efficiency and optimize project management


As organizations strive for greater project management efficiency, AI can be a powerful tool to identify inefficiencies, anticipate risks, and improve decision-making. From content creation to data summarization, generative AI (GenAI) transforms how teams work by quickly creating valuable outputs with less effort. For example, a daily sprint report that might take a team member up to an hour to compile can be generated in seconds by AI that is trained to summarize data from multiple sources.
Over time, small efficiencies like these are multiplied, leading to extensive time savings across teams and organizations. By handling repetitive tasks, GenAI models give teams more time to focus on collaboration, strategic thinking, and creative problem-solving.
In large companies, particularly those with high staff turnover or matrixed, cross-functional teams, new team members often face a steep learning curve when adapting to the team’s specific tools and processes. By functioning as a copilot, an ever-present, always-patient expert on all things project management, GenAI can provide answers from both static documentation and real-time data. When getting up to speed in a new role, a manager could ask a GenAI copilot what is happening across a team that could, over time, negatively impact the projects they are working on. The feedback given can help address these issues, reduce the manager’s learning curve, and provide on-the-job training that delivers immediate, actionable insights.
How to unlock innovation safely in the AI revolution


Organizations are caught up in a whirlwind of AI adoption, whilst struggling to ensure their security standards can match up. And as the rush to integrate AI into business processes continues into 2025, the time to safeguard its deployment is now.
To-date much of the security discussion around AI has focused on protecting against AI-powered threats. However, an overlooked aspect of AI security lies in the internal workings of AI systems, notably the hidden layers in machine learning models. Understanding the evolving threats to these internal structures is crucial to ensuring the safety and integrity of organizations seeking a security foothold in the current storm of AI adoption.
How can organizations mitigate the security risks caused by human error?


There’s a great quote which goes along the lines of “To err is human, but to really foul things up requires a computer”. When applied to cyber security this can fit very well, as human error is a major contributing factor towards data breaches. People are inherently prone to making mistakes, and when working with complex technology the risks are massively amplified. It’s hardly surprising, therefore, that almost three-quarters (74 percent) of CISOs view human error as the most significant cyber security vulnerability, according to a recent study.
Examining the issues relating to cloud security more specifically reveals a wide variety of people-problems. From technology misconfiguration and phishing to multi-factor authentication (MFA) errors, social engineering, and alert fatigue, exploiting our shared propensity for making mistakes has become a focal point for threat actors.
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