Ransomware Defence Begins with Fundamentals Not AI

 

The era of rapid technological advancements has made it clear that artificial intelligence isn't only influencing cybersecurity, it is fundamentally redefining its boundaries and capabilities as well. The transformation was evident at the RSA Conference in San Francisco in the year 2025, as more than 40,000 cybersecurity professionals gathered to discuss the path forward for the industry.

It was essential to emphasise that the rapid integration of agentic AI into cyber operations is one of the most significant topics discussed, highlighting both the disruptive potential and strategic complexities it introduces simultaneously. AI technologies continue to empower both defenders and adversaries alike, and organizations are taking a measured approach, recognising the immense potential of AI-driven solutions while remaining vigilant against the increasingly sophisticated attacks from adversaries. 

As the rise of artificial intelligence (AI) and its application in criminal activities dominates headlines more often than not, the narrative is far from a one-sided one, as there are several factors playing a role. However, the rise of AI reflects a broader industry shift toward balancing innovation with resilience in the face of rapidly shifting threats. 

Several cybercriminals are indeed using artificial intelligence (AI) and large language models (LLMs) to make ransomware campaigns more sophisticated and more convincing, crafting more convincing phishing emails, bypassing traditional security measures, and improving the precision with which victims are selected. In addition to increasing the stealth and efficiency of attackers, the stakes for organisational cybersecurity have increased as a result of these tools. 

Although AI is considered a weapon for adversaries, it is proving to be an essential ally in the defence against ransomware when integrated into security systems. By integrating AI into security systems, organisations are able to detect threats more quickly and accurately, which leads to quicker detection and response to ransomware attacks. 

Furthermore, AI helps enhance the containment and recovery efforts of incidents, leading to faster containment and a reduction in potential damage. Furthermore, AI helps to mitigate and recover from incidents more effectively. With AI coupled with real-time threat intelligence, security teams are able to adapt to evolving attack techniques, providing them with the agility to close the gap between offence and defence, making the cyber environment in which people live more and more automated.

In the wake of a series of high-profile ransomware attacks - most notably, those targeted at prominent brands like M&S - concerns have been raised that artificial intelligence may be contributing to a spike in cybercrime that has never been seen before. In spite of the fact that artificial intelligence is undeniably changing the threat landscape by streamlining phishing campaigns and automating attack workflows, its impact on ransomware operations has often been exaggerated. 

In practice, AI isn't really a revolutionary force at all, but rather a tool to accelerate tactics cybercriminals have relied on for years to come. Most ransomware groups continue to rely on proven, straightforward methods that offer speed, scalability, and consistent financial returns for their attacks. As far as successful ransomware campaigns are concerned, scammy emails, credential theft, and insider exploitation have continued to be the cornerstones of these campaigns, offering reliable results without requiring the use of advanced artificial intelligence. 

As security leaders are looking for effective ways to address these threats, they are focusing on getting a realistic perspective on how artificial intelligence is used within ransomware ecosystems. It has become increasingly evident that breach and attack simulation tools are critical assets for organisations as they enable them to identify vulnerabilities and close security gaps in advance of attackers exploiting them. 

There is a sense of balance in this approach, which emphasises the importance of bolstering foundational security controls while keeping pace with the incremental evolution of adversarial capabilities. Nevertheless, generative artificial intelligence is continuing to evolve in profound and often paradoxical ways as it continues to mature. In one way, it empowers defenders by automating routine security operations, detecting hidden patterns in complex data sets, and detecting vulnerabilities that might otherwise go undetected by the average defender. 

It also provides cybercriminals with the power to craft more sophisticated, targeted, scalable attacks, blurring the line between innovation and exploitation, providing them with powerful tools to craft more sophisticated, targeted, and scalable attacks. According to recent studies, over 80% of cyber incidents are caused by human error, which is why organisations need to harness artificial intelligence to strengthen their security posture to prevent future cyber attacks. 

AI is an excellent tool for cybersecurity leaders as it streamlines threat detection, reduces human oversight, and enables real-time response in real-time. There is, however, a danger that the same technologies may be adapted by adversaries to enhance phishing tactics, automate malware deployment, and orchestrate advanced intrusion strategies. The dual use of artificial intelligence has raised widespread concerns among executives due to its dual purpose. 

According to a recent survey, 84% of CEOs have expressed concern about generative AI being the source of widespread or catastrophic cyberattacks. Consequently, organisations are beginning to make a significant investment in AI-based cybersecurity, with projections showing a 43% increase in AI security budgets by 2025 as a result of this increase. 

In an increasingly complex digital environment, it is becoming increasingly recognised that even though generative AI introduces new vulnerabilities, it also holds the key to strengthening cyber resilience. This surge is indicative of a growing recognition of the need for generative AI. As artificial intelligence is increasing the speed and sophistication with which cyberattacks are taking place, it has never been more important than now to adhere to foundational cybersecurity practices. 

While artificial intelligence has unquestionably enhanced the tactics available to cybercriminals, allowing them to conduct more targeted phishing attempts, exploit vulnerabilities more quickly, and create more evasive malware, many of the core techniques have not changed. In other words, even though they have many similarities, the differences lie more in how they are executed, rather than in what they do. 

As such, rigorously and consistently applied traditional cybersecurity strategies remain critical bulwarks against even the threats that are enhanced by artificial intelligence. In addition to these foundational defences, multi-factor authentication (MFA), which is widely used, provides a vital safeguard against credential theft, particularly in light of the increasing use of artificial intelligence-generated phishing emails that mimic legitimate communication with astonishing accuracy - a powerful security measure that is critical today. 

As important as it is to maintain regular data backups, maintaining a secure backup mechanism also provides an effective fallback mechanism for ransomware, which is now capable of dynamically altering payloads to avoid detection. The most important element is to make sure that all systems and software are updated, as this prevents AI-enabled tools from exploiting known vulnerabilities. 

A Zero Trust architecture is becoming increasingly relevant as attackers with artificial intelligence move faster and stealthier than ever before. By assuming no implicit trust within the network and restricting lateral movement, this model greatly reduces the blast radius of any potential breach of the network and reduces the likelihood of the attack succeeding. 

A major upgrade is also required for email filtering systems, with AI-based tools that are better equipped to detect subtle nuances in phishing campaigns that have been successfully evading legacy solutions. It is also becoming more and more important for organisations to emphasise security awareness training to prevent breaches, as human error is still one of the leading causes. There is no better line of defence for a company than having employees trained to spot deceptive artificial intelligence-crafted deception.

Furthermore, the use of artificial intelligence-based anomaly detection systems is becoming increasingly important for detecting unusual behaviours that indicate a breach of security. In order to limit exposure and contain threats, segmentation, strict access control policies, and real-time monitoring are all complementary tools. However, it is important to note that even as AI has created new complexities in the threat landscape, it has not rendered traditional defences obsolete. 

Rather, these tried and true cybersecurity measures, augmented by intelligent automation and threat intelligence, are the cornerstones of resilient cybersecurity, not the opposite. Defending against adversaries powered by artificial intelligence requires not just speed but also strategic foresight and disciplined execution of proven strategies. 

As AI-powered cyberattacks become a bigger and more prevalent subject of discussion, organisations themselves are at risk from an unchecked and ungoverned use of artificial intelligence tools, a risk that is often overlooked. While much of the attention has been focused on how threat actors are capable of weaponising artificial intelligence, the internal vulnerabilities that arise from the unscheduled adoption of generative AI present a significant and present threat to the organisation. 

In what is referred to as "Shadow AI," employees are using tools like ChatGPT without formal authorisation or oversight, which circumvents established security protocols and could potentially expose sensitive corporate data. According to a recent study, nearly 40% of IT professionals admit that they have used generative AI tools without proper authorisation. 

Besides compromising governance efforts, such practices obscure visibility of data processing and handling, complicate incident response, and increase the organisation's vulnerability to attacks. The use of artificial intelligence by organisations is unregulated, coupled with inadequate data governance and poorly configured artificial intelligence services, resulting in a number of operational and security issues. 

The risks posed by internal AI tools must be mitigated by organisations treating them as if they were any enterprise technologies. Among the measures that must be taken to mitigate these risks is to establish robust governance frameworks, ensure the transparency of data flows, conduct regular audits, and provide cybersecurity training that addresses the dangers of shadow artificial intelligence, as well as ensure that leaders remain mindful of current threats to their organisations. 

Although artificial intelligence generates headlines, the most successful attacks continue to rely on the proven techniques - phishing, credential theft, and ransomware. The emphasis placed on the potential threats that could be driven by AI can distract attention from critical, foundational defences. In this context, complacency and misplaced priorities are the greatest risks, and not AI itself. 

 It remains true that maintaining a disciplined cyber hygiene, simulating attacks, and strengthening security fundamentals remain the most effective ways to combat ransomware in the long run. There is no doubt that artificial intelligence is not just a single threat or solution for cybersecurity, but rather a powerful force capable of strengthening as well as destabilising digital defences in an environment that is rapidly evolving. 

As organisations navigate this shifting landscape, it is imperative to have clarity, discipline, and strategic depth as they attempt to navigate this new terrain. Despite the fact that artificial intelligence may dominate headlines and influence funding decisions, it does not negate the importance of basic cybersecurity practices. 

What is needed is a recalibration of priorities as people move forward. Security leaders must build resilience against emerging technologies, rather than chasing the allure of emerging technologies alone. They need to adopt a realistic and layered approach to security, one that embraces AI as a tool while never losing sight of what consistently works. 

To achieve this goal, advanced automation, analytics, and tried-and-true defences must be integrated, governance around AI usage must be enforced, and access to data flows and user behaviour must remain tightly controlled. In addition, organisations need to realise that technological tools are only as powerful as the frameworks and people that support them. 

Threats are becoming increasingly automated, making it even more important to have human oversight. Training, informed leadership, and an environment that fosters a culture of accountability are not optional; they are imperative. In order for artificial intelligence to be effective, it must be part of a larger, more comprehensive security strategy that is based on visibility, transparency, and proactive risk management. 

As the battle against ransomware and AI-enhanced cyber threats continues, the key to success will not be whose tools have the greatest sophistication, but whose application of these tools will be consistent, purposeful, and foresightful. AI isn't a threat, but it's an opportunity to master it, regulate it internally, and never let innovation overshadow the fundamentals that keep security sustainable in the first place. Today's defenders have a winning formula: strong fundamentals, smart integration, and unwavering vigilance are the keys to their success.