Daily Tech Digest by Kannan Subbiah: Daily Tech Digest

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Seeing AI Agents Is Not Enough. Security Teams Must Enforce What They Can Do

As organizations increasingly adopt artificial intelligence to handle everyday tasks, finding out where these AI programs operate is only the first step. The article points out that simply tracking these programs provides a false sense of safety. Unlike regular software or human workers with predictable routines, AI programs often adapt their actions based on goals, making standard access controls inadequate. Because they can reason and take action independently across various systems, the real security challenge lies in strictly enforcing what they are allowed to do. To achieve this, security teams must understand the core intent behind each program. This means correlating who owns the program, what it is designed to achieve, and what tools it needs to access. Rather than waiting for something to go wrong and cleaning up the mess, organizations should set clear rules that govern AI behavior before actions occur. For example, a customer support tool might need to read histories but should never be allowed to export bulk data. Ultimately, managing these tools safely requires a unified approach that spans the entire organization. Success comes not just from knowing an AI tool exists, but from confidently controlling its boundaries, actions, and overall purpose.

The air gap is a myth and other OT security truths

In a recent interview, Benjamin Bachmann, Director of Group Information Security at Bilfinger, addresses key realities of securing industrial operations and dispels common misconceptions about operational technology security. He explains that attackers targeting industrial environments are generally not looking to steal data or trade secrets. Instead, they want to disrupt operations and gain control over physical processes. He also notes that the idea of a completely isolated network, or air gap, is largely a myth in today's connected plants. To handle security incidents effectively without compromising safety or uptime, Bachmann emphasizes the need for engineering and security teams to establish containment protocols long before an emergency occurs. He points out that while older industrial equipment lacks modern security features, its highly predictable network traffic makes it easier to spot unauthorized activity through careful monitoring and network segmentation. Regarding ransomware, Bachmann observes that attackers often price their demands based on the cost of operational downtime. Therefore, the most effective defense involves rapid recovery plans and the ability to maintain partial operations safely, which removes the attacker's leverage. Finally, he challenges the common belief that human error is the weakest link in security, arguing instead that fragile system architectures are the actual root problem.

Why enterprises should care about Nokia’s AI-RAN platform

Nokia recently announced an artificial intelligence driven platform designed to fundamentally change how mobile network infrastructure operates. Traditionally, mobile networks rely on rigid, specialized hardware that limits adaptability and requires frequent physical upgrades. The new approach separates the network software from the physical hardware, running operations on flexible graphics processing units instead. This shift effectively turns the radio network into a programmable computer. The immediate benefit for network operators is significant performance improvements. By using complex algorithms, the platform can double the usable capacity of existing wireless spectrum bands by the year 2028, avoiding the need for expensive new spectrum licenses. Furthermore, it easily adapts to changing data traffic patterns caused by modern applications. However, the most critical shift is in potential business models. Because the platform operates like a standard computing environment, it supports a new application layer where developers can create practical tools. This allows operators to generate revenue beyond basic internet connectivity. Practical applications include turning cell towers into sensor networks for environmental monitoring, providing accurate tracking for warehouse robots, and offering dedicated computing power for local data processing. Ultimately, this software driven strategy allows network providers to continuously update features and increase efficiency without relying on constant hardware replacements.

AI adoption in OT security outpaces governance controls

According to a recent industry survey, industrial organizations are rapidly adopting artificial intelligence for operational technology (OT) cybersecurity, yet formal governance and safety controls are lagging significantly behind. While nearly ninety percent of surveyed organizations are evaluating or using AI to monitor networks, detect threats, and support security operations, only about fifteen percent have implemented an enforced AI policy tailored to industrial environments. The technology is primarily deployed in advisory roles for monitoring and analysis rather than direct industrial control. However, errors in AI classification or alerting could still negatively affect equipment availability and safety. Implementation challenges are primarily rooted in poor data quality, lack of proper labeling, and the difficulty of integrating modern AI tools with legacy operational systems. Furthermore, respondents expressed concerns about the physical risks of AI system failures or cyberattacks manipulating AI outputs, as adversaries increasingly use similar technology to enhance their attacks. Most organizations currently rely on informal human oversight rather than documented protocols. Experts suggest that to maintain operational control, companies should ensure their use of AI does not exceed the authority supported by their current security controls, evidence, and operating models. Robust governance and formal consequence mapping are essential for safe integration.

CIOs beware: DNS KSK rollover could kick off wave of mysterious outages

A seemingly routine security update to the internet’s domain name system could trigger unexpected network outages for organizations between October 2026 and January 2027. The event, known as a Key Signing Key rollover, updates the cryptographic key that verifies network responses. While the central update itself is simple, many organizations possess vast networks of unmapped connections hidden within older applications, custom scripts, external services, and forgotten software containers. Because these hidden areas operate outside normal oversight, they may fail to process the new key correctly. When these older configurations fail, the resulting disruptions rarely announce themselves as a domain name problem. Instead, they often look like random application timeouts, broken logins, or unreachable partner networks. This misdirection can force support teams to spend hours troubleshooting the wrong issues before realizing the core problem stems from a missed network update. Although widespread failure of primary systems is unlikely, even isolated disruptions in specific departments or manufacturing lines can cause severe operational delays. Experts advise technology leaders to treat this upcoming change with calm focus. Rather than viewing it as a simple infrastructure chore, organizations can use this event as a practical opportunity to improve their internal visibility and strengthen overall system resilience.

The metrics organizations should track to measure their cyber resilience

As cyber disruptions become an unavoidable reality, organizations must shift from merely aspiring to cyber resilience to making it a measurable operational capability. Relying on traditional technical metrics, like counting patched vulnerabilities or software alerts, is no longer sufficient. These measurements do not reflect a company's ability to maintain its operations during a crisis. Instead, leaders should measure resilience by its actual business impact. The first step is identifying the minimum viable business, which includes the critical services and functions that must remain active or be restored immediately to fulfill the organization's core mission. From there, time becomes the most valuable metric. Organizations should track how quickly they can detect, contain, and recover from an incident to minimize both the depth and duration of the disruption. Furthermore, standard questionnaires and self-assessments are inadequate for testing true readiness. Practical, realistic exercises, such as tabletop simulations and recovery drills, are necessary to uncover gaps in decision-making and communication under stress. Because businesses operate within interconnected ecosystems, resilience must also extend to suppliers and third-party partners. Ultimately, these practical metrics serve as a vital leadership tool, guiding investment decisions and proving that a company can confidently withstand and operate through significant cyber events.

The Compliance Timelines Are Converging: Every Road Now Leads to a Cryptographic Bill of Materials

Over the next few years, multiple security regulations and government standards are converging, bringing strict new deadlines for organizations to track and manage their encryption methods. Past transitions to newer security standards were difficult because companies simply did not know where their outdated encryption was hidden. Now, with the looming threat of advanced computers capable of breaking current encryption, the stakes are even higher, especially since adversaries can steal sensitive encrypted data today and unlock it later. Many organizations mistakenly rely on basic certificate scanners, but these tools fail to detect encryption deeply embedded in software applications, operating systems, and databases. To properly secure their networks and meet these overlapping rules, companies must build a complete map of their encryption assets and understand how they interact. This comprehensive record is known as a Cryptographic Bill of Materials. By adopting this approach, teams can identify vulnerabilities, map relationships between systems, and prioritize updates without guesswork. The most effective strategy is to start by taking a realistic inventory of all current encryption practices across the entire organization. Doing so allows leaders to confidently prepare for future requirements, adapt to new standards, and maintain continuous oversight of their digital security. It is a vital step.

Recovery Readiness Is the New Measure of Cybersecurity Success

For decades, the primary goal of cybersecurity was preventing attacks by building strong defenses like firewalls and detection systems. While prevention remains a highly foundational element, the rapidly evolving threat landscape, driven by sophisticated ransomware, nation-state actors, and artificial intelligence, means that simply keeping attackers out is no longer a realistic finish line. Today, stakeholders recognize that even the most secure organizations can suffer breaches. As a result, the standard for cybersecurity success has firmly shifted from strict prevention toward operational recoverability. Instead of just tracking technical vulnerabilities, leaders, customers, and boards are now asking how quickly and confidently a business can actually restore its critical services after a cyber incident. Preserving trust and reputation now depends on resilient recovery processes rather than simply avoiding compromise. However, true recovery readiness cannot be assumed from written plans or annual exercises alone; it requires continuous validation as cloud infrastructure, hidden business dependencies, and technologies evolve. Moving forward, companies must treat operational recoverability as a vital business metric. By understanding their recovery posture, organizations can prioritize investments based on actual business impact, reduce uncertainty during a crisis, and ensure they survive and thrive even after a serious cyberattack occurs.

Why MDR Is Essential for Big Data Security

Managed Detection and Response is becoming increasingly vital as organizations generate massive amounts of data and face more sophisticated threats. In our highly connected world, the convergence of traditional corporate networks and operational technology creates significant vulnerabilities. Industrial systems, which were once completely isolated, now frequently connect to cloud platforms and corporate systems, greatly expanding the potential attack surface. Consequently, security teams must sift through enormous volumes of business data to identify subtle anomalies and hidden threats before they cause widespread damage. A robust Managed Detection and Response strategy provides continuous monitoring and specialized expertise, which is especially critical for operational technology environments like manufacturing, energy, and utilities. Unlike standard information technology environments, these physical systems prioritize safety and continuous operation above all else, meaning security measures cannot simply shut down critical processes when a threat is suspected. Top providers address this challenge by delivering specialized detection and response tailored to the unique constraints of industrial control systems. They bridge the gap between information technology and operational technology, helping leaders reduce physical risks, adhere to critical infrastructure regulations, and protect essential services. By partnering with an experienced provider, companies gain the necessary visibility and rapid response capabilities to secure their complex data environments with assurance and operational continuity.

Europe's Multilingual Reality Exposes AI Security Gaps

While large language models can process text in dozens of languages, their included safety guardrails are overwhelmingly optimized for English. This English focus creates significant security vulnerabilities for organizations operating in multilingual environments, particularly across Europe. Although a model might fluently answer prompts in languages like German, Spanish, or Swahili, its ability to detect and block malicious actions, such as prompt injections and jailbreaks, often drops significantly compared to English. Attackers exploit this gap by translating harmful commands into lesser used languages to bypass security filters. Research shows that some models are vastly more likely to provide actionable responses to unsafe prompts when queried in these regional languages. Relying on translation security layers, where inputs are translated to English before being checked, can alter the true intent of a prompt, sometimes masking malicious commands within benign contexts. To address these serious vulnerabilities, experts recommend moving beyond basic translation filters. Organizations should instead adopt native language guardrails that evaluate the original input, conduct rigorous security testing that includes mixed language scenarios and diverse cultural contexts, and deploy active runtime firewalls. As the modern regulatory landscape, including new artificial intelligence legislation in Europe, demands better risk management, ensuring consistent safety across all supported languages is becoming a critical operational necessity.

Daily Tech Digest by Kannan Subbiah

Daily Tech Digest - July 25, 2026