Daily Tech Digest by Kannan Subbiah: OSINT

Showing posts with label OSINT. Show all posts

Daily Tech Digest - January 12, 2026

Quote for the day:

"The people who 'don't have time' and the people who 'always find time' have the same amount of time." -- Unknown

7 challenges IT leaders will face in 2026

’s says that by the end of the decade organizations will see lawsuits, fines, and due to disruptions from inadequate AI controls. As a result, CIOs say, governance has become an urgent concern — not an afterthought. ... , CIO of digital identity and data protection services company , says he’s preparing for 2026 with a focus on cultural readiness, continuous learning, and preparing people and the tech stack for rapid AI-driven changes. “The CIO role has moved beyond managing applications and infrastructure,” Kaushal says. “It’s now about shaping the future. As AI reshapes enterprise ecosystems, accelerating adoption without alignment risks technical debt, skills gaps, and greater cyber vulnerabilities. Ultimately, the true measure of a modern CIO isn’t how quickly we deploy new applications or AI — it’s how effectively we prepare our people and businesses for what’s next.” ... When modernizing applications, argues that teams need to stay outcome-focused, phasing in improvements that directly support their goals. “This means application modernization and cloud cost-optimization initiatives are required to stay competitive and relevant,” he says. “The challenge is to modernize and become more agile without letting costs spiral. By empowering an organization to develop applications faster and more efficiently, we can accelerate modernization efforts, respond more quickly to the pace of tech change, and maintain control over cloud expenditures.”

Rethinking OT security for project heavy shipyards

In OT, availability always wins. If a security control interferes with operations, it will be bypassed or rejected, often for good reasons. That constraint forces a different mindset. The first mental shift is letting go of the idea that visibility requires changing the devices themselves. In many legacy environments, that simply isn’t an option. So you have to look elsewhere. In practice, meaningful visibility often starts at the network level, using passive observation rather than active interrogation. You learn what “normal” looks like by watching how systems communicate, not by poking them. ... In our environment, sustainable IT/OT integration means avoiding ad-hoc connectivity altogether. When we connect vessels, yards and on-shore systems, we do so through deliberately designed integration paths. One practical example of this approach is how we use our : secure remote access, segmentation and monitoring are treated as integral parts of the digital solution itself, not as optional add-ons introduced later. That allows us to enable innovation while retaining control as IT and OT continue to converge. ... In practice, least privilege means being disciplined about time and purpose. Access should expire by default. It should be linked to a specific task, not to a project or a person’s role in general. We have found that making access removal automatic is often more effective than adding extra approval steps at the front end. If access cannot be explained in one sentence, it probably shouldn’t exist.

Mastering the architecture of hybrid edge environments

A mature IT architecture is characterized by well-orchestrated workflows that enable compute at the edge as well as data exchanges between the edge and central IT. Throughout all processes, security must be maintained. ... Conceptually, creating an IT architecture that incorporates both central IT and the edge sounds easy -- but it isn't. What must be achieved architecturally is a synergistic blend of hardware, software, applications, security and communications that work seamlessly together, whether the technology is at the edge or in the data center. When multiple solutions and vendors are involved, the integration of these elements can be daunting -- but the way that IT can address architectural conflicts upfront is by predefining the interface protocols, devices, and the hardware and software stacks. ... The hybrid approach is a win-win for everyone. It gives users a sense of autonomy, and it saves IT from making frequent trips to remote sites. The key to it all is to clearly define the roles that IT and end users will play in edge support. In other words, what are end-user technical support people in charge of, and at what point does IT step in? ... Finally, a mature architecture must define disaster recovery. What happens if a remote edge site fails? A mature architecture must define where it fails over to, so the site can keep going even if its local systems are out. In these cases, data and systems must be replicated for redundancy in the cloud or in the corporate data center, so remote sites can fail over to these resources, with end-to-end security in place at all points.

The Push for Agentic AI Standards Is Well Underway

"Many existing trust frameworks were layered onto an internet never designed for machine-level delegation or accountability. As agents begin acting independently, those frameworks need to evolve rather than simply be imposed," said, who authored the book ": The Next Evolution of AI and the Future of Digital Interaction." The agentic AI standards debate ranges from adopting enforceable guardrails to ensuring interoperability. Hazari pointed out that innovation is already moving faster than formal standard-setting can go. Fragmentation is a natural phase that precedes consolidation and interoperability. ... The brings together early but influential agentic technologies from , and . These hyperscalers are rolling out controlled AI environments often described as "AI factories" designed to deliver AI compute at enterprise scale. Initial contributions to the foundation include Anthropic's Model Context Protocol, which focuses on standardizing how agents receive and structure context; goose, an open-source agentic framework contributed by ; and AGENTS.md from , which defines how agents describe capabilities, permissions and constraints. Rather than prescribing a single architecture, these projects aim to standardize interfaces and metadata areas where fragmentation is already creating friction. Hazari said initiatives like the Agentic AI Foundation can absorb patterns into shared frameworks as they emerge.

7 steps to move from IT support to IT strategist

The biggest obstacle holding IT professionals back is a passive mindset. Sitting back and waiting to be told what to do prevents IT teams from reaching the strategic partnership level they want, said ... , vice president of AI operations at , emphasized that strong IT leaders see their work as part of a bigger ecosystem, one that works best when people are open, share information, and collaborate. ... IT professionals need to show up as partners by truly understanding what’s going on in the business, rather than waiting for business stakeholders to come to them with problems to solve, ’s Johnson said. “When you’re engaging with your business partners, you’re bringing proactive ideas and solutions to the table,” he said. ... Rather than having an order-taking mindset, IT professionals should ask probing questions about what partners need and what’s driving that need, which shifts toward problem-solving and focuses on outcomes rather than just implementing solutions, said. ... “IT professionals should frame every initiative in terms of the business problem it solves, the risk it reduces, or the opportunity it unlocks,” he said. ... Johnson warns against constantly searching for home runs. “Those are harder to find and they’re harder to deliver on,” he said. “Within 30 to 60 days, IT pros can build understanding around metrics and target states, then look for opportunities to help, even if they start small.”

Spec Driven Development: When Architecture Becomes Executable

The name Spec Driven Development may suggest a methodology, akin to Test Driven Development. However, this framing undersells its significance. SDD is more accurately understood as an architectural pattern, one that inverts the traditional source of truth by elevating executable specifications above code itself. SDD represents a fundamental shift in how software systems are architected, governed, and evolved. At a technical level, it introduces a declarative, contract-centric control plane that repositions the specification as the system's primary executable artifact. Implementation code, in contrast, becomes a secondary, generated representation of architectural intent. ... For decades, software architecture has operated under a largely unchallenged assumption that code is the ultimate authority. Architecture diagrams, design documents, interface contracts, and requirement specifications all existed to guide implementation. However, the running system always derived its truth from what was ultimately deployed. When mismatches occurred, the standard response was to "update the documentation" SDD inverts this relationship entirely. The specification becomes the authoritative definition of system reality, and implementations are continuously derived, validated, and, when necessary, regenerated to conform to that truth. This is not a philosophical distinction; it is a structural inversion of the governance of software systems.

Decoupling architectures: building resilience against cyber attacks

The recent incidents are tied together by a common approach to digital infrastructure: tightly coupled architectures. In these environments, critical applications such as , warehouse, logistics, retail, finance are interconnected so closely that if one fails, other critical systems are unable to function. A single weak point becomes the domino that topples the rest. This design may have made sense in a simpler, more predictable IT world. But in today’s highly interconnected landscape, with constantly evolving threats accelerated thanks to the AI revolution, this once-efficient design has turned into the perfect setup for system-wide issues. ... Instead of linking systems directly, a provides a shared backbone where each system publishes what happens. That means if one system is compromised or taken offline during an incident, the others can continue to function. Business operations don’t have to come to a standstill simply because a single component is isolated — and when the affected system is restored, it can replay the missed events and rejoin the flow seamlessly. Some architectures, like event-driven data streaming, can keep that data flowing in real time despite an attack. ... For CIOs and CISOs, this shift in mindset is critical. is no longer just about or detection tools. It’s about designing systems that can limit the blast radius when hit. absorbing and isolating the damage to ensure a quick recovery.

AI, geopolitics & supply chains reshape cyber risk

Organisations are scaling AI in core operations, customer engagement and decision-making. This expansion is exposing new attack surfaces, including data inputs, model training pipelines and integration points with legacy systems. It also coincides with uncertain regulatory expectations on issues such as transparency, auditability and the handling of personal and sensitive data in machine learning models. ... Map the above challenges alongside the geopolitical fragmentation the highlights, cyber risk is really being challenged in ways many traditional compliance frameworks were not designed for, via issues such as sovereignty, supply-chain and third-party exposure. In this environment, resilience absolutely depends on an organisation's ability to integrate cyber security, information security, privacy, and AI governance into a single risk picture, and to connect that with their technology decisions, regulatory obligations, business impact, and geopolitical context. ... Hardware, software and cloud services now rely on dispersed design, manufacturing and operational ecosystems. Attackers exploit this complexity. They target upstream providers, third-party tools and managed services. ... Regulatory fragmentation around AI is emerging alongside an increase in reported misuse. This includes deepfakes, automated disinformation, fraud, model theft and prompt injection attacks, as well as concerns over opaque automated decision-making.

Five key priorities for CEOs & Governance practitioners in 2026

As are embracing cutting edge technologies, without a skilled workforce to implement these technological solutions, the financial services industry will suffer a lot. According to IDC, IT skills shortage is expected to impact 9 out of 10 organizations by 2026 with a cost of $5.5 trillion in delays, issues, and revenue loss. Thus, CEOs and governance professionals should take up skills management as their top priority ... AI’s explainability and transparency are to be addressed on priority. Finally, AI is creating lots of environmental impacts contributing to greenhouse gas emissions due to its high energy and water consumption, which leads to the Environmental, social, governance (ESG) issues to be focused on by governance professionals. ... CEOs and governance professionals must take measures towards preemptive cybersecurity. They should realise that cybersecurity gives the foundation of trust for all the stakeholders of any enterprise and they cannot afford to compromise on it. ... Traditional strategic planning involved fixed, long-term goals, detailed forecasts, and periodic reviews. This is not suitable in the face of constant disruption. by contrast is having short planning cycles, incremental objectives, and adaptive learning. ... The future of information systems management lies in the seamless integration of cloud and edge computing – a distributed intelligent architecture where data is processed wherever it is more efficient to do so.

Dark Web Intelligence: How to Leverage OSINT for Proactive Threat Mitigation

Experts say monitoring the is an early warning system. Threat actors trade stolen data or exploits before they are detected in the broader world. Security pros even call dark web monitoring an ‘early warning radar’ that flags when sensitive data is leaked in underground forums. The difference is huge: Without these signals, breaches go undetected for months. In fact, one report found that the average breach goes undiscovered for about 194 days without proactive measures. ... Gathering intel from the dark web requires specialized tools and techniques. Analysts use a combination of and commercial intelligence platforms. Basic breach-checkers (public data-leak search engines) will flag obvious exposures, but comprehensive coverage requires purpose-built scanners that constantly crawl underground forums and encrypted chat networks. ... Organizations of all sizes have seen real benefits of dark web monitoring. For example, in 2020, identified a potential supply-chain breach when threat researchers discovered guest data being sold on some underground forums. Getting that early heads up allowed Marriott to get in and investigate and inform affected customers before the incident became public. Similarly, after 700 million got scraped in 2021, the first samples of the stolen data started popping up on dark web marketplaces and got caught by monitoring tools. Those alerts prompted LinkedIn users to reset their passwords and enabled the company to sort out its credential abuse defenses.

Daily Tech Digest - December 23, 2025

Quote for the day:

"What seems to us as bitter trials are often blessings in disguise." -- Oscar Wilde

The CIO Playbook: Reimagining Transformation in a Shifting Economy

The CIO has travelled from managing mainframes to managing meaning and purpose-driven transformation. And as AI becomes the nervous system of the enterprise, technology’s centre of gravity has shifted decisively to the boardroom. The basement may be gone, but its persona remains — a reminder that every evolution begins with resistance and is ultimately tamed by the quiet persistence of those who keep the systems running and the vision alive. Those who embraced progressive technology and blended business with innovation became leaders; the rest faded into also-rans. At the end of the day, the concern isn’t technology — it’s transformation capacity and the enterprise’s appetite to take risks, embrace change, and stay relevant. Organisations that lack this mindset will fail to evolve from traditional enterprises into intelligent, interactive digital ecosystems built for the AI age. The question remains: how do you paint the plane while flying it — and keep repainting it as customer needs, markets, and technologies shift mid-air? In this GenAI-driven era, the enterprise must think like software: in continuous integration, continuous delivery, and continuous learning. This isn’t about upgrading systems; it’s about rewiring strategy, culture, and leadership to respond in real time. We are at a defining inflection point. The time is now to connect the dots — to build an experience delivery matrix that not only works for your organisation but evolves with your customer.

Flexibility or Captivity? The Data Storage Decision Shaping Your AI Future

Enterprises today must walk a tightrope: on one side, harness the performance, trust, and synergies of long-standing storage vendor relationships; on the other, avoid entanglements that limit their ability to extract maximum value from their data, especially as AI makes rapid reuse of massive unstructured data sets a strategic necessity. ... Financial barriers also play a role. Opaque or punitive egress fees charged by many cloud providers can make it prohibitively expensive to move large volumes of data out of their environments. At the same time, workflows that depend on a vendor’s APIs, caching mechanisms, or specific interfaces can make even technically feasible migrations risky and disruptive. ... Budget and performance pressures add another layer of urgency. You can save tremendously by offloading cold data to lower-cost storage tiers. Yet if retrieving that data requires rehydration, metadata reconciliation, or funneling requests through proprietary gateways, the savings are quickly offset. Finally, the rapid evolution of technology means enterprises need flexibility to adopt new tools and services. Being locked into a single vendor makes it harder to pivot as the landscape changes. ... Longstanding vendor relationships often provide stability, support, and volume pricing discounts. Abandoning these partnerships entirely in the pursuit of perfect flexibility could undermine those benefits. The more pragmatic approach is to partner deeply while insisting on open standards and negotiating agreements that preserve data mobility.

Agentic AI already hinting at cybersecurity’s pending identity crisis

First, many of these efforts are effectively shadow IT, where a line of business (LOB) executive has authorized the proof of concept to see what these agents can do. In these cases, IT or cyber teams haven’t likely been involved, and so security hasn’t been a top priority for the POC. Second, many executives — including third-party business partners handling supply chain, distribution, or manufacturing — have historically cut corners for POCs because they are traditionally confined to sandboxes isolated from the enterprise’s live environments. But agentic systems don’t work that way. To test their capabilities, they typically need to be released into the general environment. The proper way to proceed is for every agent in your environment — whether IT authorized, LOB launched, or that of a third party — to be tracked and controlled by PKI identities from agentic authentication vendors. ... “Traditional authentication frameworks assume static identities and predictable request patterns. Autonomous agents create a new category of risk because they initiate actions independently, escalate behavior based on memory, and form new communication pathways on their own. The threat surface becomes dynamic, not static,” Khan says. “When agents update their own internal state, learn from prior interactions, or modify their role within a workflow, their identity from a security perspective changes over time. Most organizations are not prepared for agents whose capabilities and behavior evolve after authentication.”

Expanding Zero Trust to Critical Infrastructure: Meeting Evolving Threats and NERC CIP

StandardsPrevious compliance requirements have emphasized a perimeter defense model, leaving blind spots for any threats that happen to breach the perimeter. Zero Trust initiatives solve this by making accesses inside the perimeter visible and subjecting them to strong, identity-based policies. This proactive, Zero Trust-driven model naturally fulfills CIP-015-1 requirements, reducing or eliminating false positives compared to threat detection methods. In fact, an organization with a mature Zero Trust posture should be able to operate normally, even if the network is compromised. This resilience is possible when critical assets—such as controls in electrical substations or business software in the data center—are properly shielded from the shared network. Zero Trust enforces access based on verified identity, role, and context. Every connection is authenticated, authorized, encrypted, and logged. ... In short, Zero Trust’s identity-centric enforcement ensures that unauthorized network activity is detected and blocked. Even if a hacker has network access, they won’t be able to leverage that access to exfiltrate data or attack other hosts. A Zero Trust-protected organization can operate normally, even if the network is compromised. ... Zero Trust doesn’t replace your perimeter but instead reinforces it. Rather than replacing existing network firewalls, a Zero Trust can overlay existing security architectures, providing a comprehensive layer of defense through identity-based control and traffic visibility.

Top 5 enterprise tech priorities for 2026

The first is that the top priority, cited by 211 of the enterprises, is to “deploy the hardware, software, data, and network tools needed to optimize AI project value.” ... “You can’t totally immunize yourself against a massive cloud or Internet problem,” say planners. Most cloud outages, they note, resolve in a maximum of a few hours, so you can let some applications ride things out. When you know the “what,” you can look at the “how.” Is multi-cloud the best approach, or can you build out some capacity in the data center? ... “We have too many things to buy and to manage,” one planner said. “Too many sources, too many technologies.” Nobody thinks they can do some massive fork-lift restructuring (there’s no budget), but they do believe that current projects can be aligned to a long-term simplification strategy. This, interestingly, is seen by over a hundred of the group as reducing the number of vendors. They think that “lock-in” is a small price to pay for greater efficiency and reduction in operations complexity, integration, and fault isolation. ... The biggest problem, these enterprises say, is that governance has tended to be applied to projects at the planning level, meaning that absent major projects, governance tended to limp along based on aging reviews. Enterprises note that, like AI, orderly expansions in how applications and data are used can introduce governance issues, just like changes in laws and regulations.

Why flaky tests are increasing, and what you can do about it

One of the most persistent challenges is the lack of visibility into where flakiness originates. As build complexity rises, false positives or flaky tests often rise in tandem. In many organizations, CI remains a black box stitched together from multiple tools as artifact size increases. Failures may stem from unstable test code, misconfigured runners, dependency conflicts or resource contention, yet teams often lack the observability needed to pinpoint causes with confidence. Without clear visibility, debugging becomes guesswork and recurring failures become accepted as part of the process rather than issues to be resolved. The encouraging news is that high-performing teams are addressing this pattern directly. ... Better tooling alone will not solve the problem. organizations need to adopt a mindset that treats CI like production infrastructure. That means defining performance and reliability targets for test suites, setting alerts when flakiness rises above a threshold and reviewing pipeline health alongside feature metrics. It also means creating clear ownership over CI configuration and test stability so that flaky behaviour is not allowed to accumulate unchecked. ... Flaky tests may feel like a quality issue, but they are also a performance problem and a cultural one. They shape how developers perceive the reliability of their tools. They influence how quickly teams can ship. Most importantly, they determine whether CI/CD remains a source of confidence or becomes a source of drag.

Stop letting ‘urgent’ derail delivery. Manage interruptions proactively

As engineers and managers, we all have been interrupted by those unplanned, time-sensitive requests (or tasks) that arrive outside normal planning cadences. An “urgent” Slack, a last-minute requirement or an exec ask is enough to nuke your standard agile rituals. Apart from randomizing your sprint, it causes thrash for existing projects and leads to developer burnout. ... Existing team-level mechanisms like mid-sprint checkpoints provide teams the opportunity to “course correct”; however, many external randomizations arrive with an immediacy. ... Even well-triaged items can spiral into open-ended investigations and implementations that the team cannot afford. How do we manage that? Time-box it. Just a simple “we’ll execute for two days, then regroup” goes a long way in avoiding rabbit-holes. The randomization is for the team to manage, not for an individual. Teams should plan for handoffs as a normal part of supporting randomizations. Handoffs prevent bottlenecks, reduce burnout and keep the rest of the team moving. ... In cases where there are disagreements on priority, teams should not delay asking for leadership help. ... Without making it a heavy lift, teams should capture and periodically review health metrics. For our team, % unplanned work, interrupts per sprint, mean time to triage and periodic sentiment survey helped a lot. Teams should review these within their existing mechanisms (ex., sprint retrospectives) for trend analysis and adjustments.

How does Agentic AI enhance operational security

With Agentic AI, the deployment of automated security protocols becomes more contextual and responsive to immediate threats. The implementation of Agentic AI in cybersecurity environments involves continuous monitoring and assessment, ensuring that NHIs and their secrets remain fortified against evolving threats. ... Various industries have begun to recognize the strategic importance of integrating Agentic AI and NHI management into their security frameworks. Financial services, healthcare, travel, DevOps, and Security Operations Centers (SOC) have benefited from these technologies, especially those heavily reliant on cloud environments. In financial services, for instance, securing hybrid cloud environments is paramount to protecting sensitive client data. Healthcare institutions, with their vast troves of personal health information, have seen significant improvements in data protection through the use of these advanced cybersecurity measures. ... Agentic AI is reshaping how decisions are made in cybersecurity by offering algorithmic insights that enhance human judgment. Incorporating Agentic AI into cybersecurity operations provides the data-driven insights necessary for informed decision-making. Agentic AI’s capacity to process vast amounts of data at lightning speed means it can discern subtle signs of an impending threat long before a human analyst might notice. By providing detailed reports and forecasts, it offers decision-makers a 360-degree view of their security.

AI-fuelled cyber onslaught to hit critical systems by 2026

"Historically, operational technology cyber security incidents were the domain of nation states, or sometimes the act of a disgruntled insider. But recently, we've seen year-on-year rises in operational technology ransomware from criminal groups as well and with hacktivists: All major threat actor categories have bridged the IT-OT gap. With that comes a shift from highly targeted, strategic campaigns to the types of opportunistic attacks CISA describes. These are the predators targeting the slowest gazelles, so to speak," said Dankaart. ... Australian policymakers are expected to revise cybersecurity legislation and regulations for critical sectors. Morris added that organisations are looking at overseas case studies to reduce fraud and infrastructure-level attacks. ... "The scam ecosystem will continue to be exposed globally, raising new awareness of the many aspects of these crimes, including payment processors, geographic distribution of call centres and connected financial crimes. ... "The solution will be to find the 'Goldilocks Spot' of high automation and human accountability, where AI aggregates related tasks, alerts and presents them as a single decision point for a human to make. Humans then make one accountable, auditable policy decision rather than hundreds to thousands of potentially inconsistent individual choices; maintaining human oversight while still leveraging AI's capacity for comprehensive, consistent work."

Rising Tides: When Cybersecurity Becomes Personal – Inside the Work of an OSINT Investigator

The upside of all the technology and access we have is also what creates so much risk in the multitude of dangerous situations that Miller has seen and helped people out of in the most efficient and least disruptive ways possible. But, we as a cyber community have to help, but building ethics and integrity into our products so they can be used less maliciously in human cases; not simply data cases. ... When everything complicated is failing, go back to basics, and teach them over and over again, until the audience moves forward. I’ve spent a decade doing this and still share the same basic principles and safety measures. Technology changes, so do people, but sometimes the things they need the most are to to be seen, heard and understood. This job is a lot of emotional support and working through the things where the client gets hung up making a decision, or moving forward. ... The amount of energy and time devoted to cases has to have a balance. I say no to more cases than I say yes, simply because I don’t have the resources or time to do them. ... As the world changes, you have to adapt and shift your tactics, delivery, and capabilities to help more people. While people like to tussle over politics, I remind them, everything is political. It’s no different in community care, mutual aid, or non-profit work. If systems cannot or won’t support communities, you have a responsibility to help build parallel systems of care that can. This means not leaving anyone behind, not sacrificing one group over another.

Daily Tech Digest - August 22, 2025

Quote for the day:

“Become the kind of leader that people would follow voluntarily, even if you had no title or position.” -- Brian Tracy

Leveraging DevOps to accelerate the delivery of intelligent and autonomous care solutions

Fast iteration and continuous delivery have become standard in industries like e-commerce and finance. Healthcare operates under different rules. Here, the consequences of technical missteps can directly affect care outcomes or compromise sensitive patient information. Even a small configuration error can delay a diagnosis or impact patient safety. That reality shifts how DevOps is applied. The focus is on building systems that behave consistently, meet compliance standards automatically, and support reliable care delivery at every step. ... In many healthcare environments, developers are held back by slow setup processes and multi-step approvals that make it harder to contribute code efficiently or with confidence. This often leads to slower cycles and fragmented focus. Modern DevOps platforms help by introducing prebuilt, compliant workflow templates, secure self-service provisioning for environments, and real-time, AI-supported code review tools. In one case, development teams streamlined dozens of custom scripts into a reusable pipeline that provisioned compliant environments automatically. The result was a noticeable reduction in setup time and greater consistency across projects. Building on this foundation, DevOps also play a vital role in development and deployment of the Machine Learning Models.

Tackling the DevSecOps Gap in Software Understanding

The big idea in DevSecOps has always been this: shift security left, embed it early and often, and make it everyone’s responsibility. This makes DevSecOps the perfect context for addressing the software understanding gap. Why? Because the best time to capture visibility into your software’s inner workings isn’t after it’s shipped—it’s while it’s being built. ... Software Bill of Materials (SBOMs) are getting a lot of attention—and rightly so. They provide a machine-readable inventory of every component in a piece of software, down to the library level. SBOMs are a baseline requirement for software visibility, but they’re not the whole story. What we need is end-to-end traceability—from code to artifact to runtime. That includes:Component provenance: Where did this library come from, and who maintains it? Build pipelines: What tools and environments were used to compile the software? Deployment metadata: When and where was this version deployed, and under what conditions? ... Too often, the conversation around software security gets stuck on source code access. But as anyone in DevSecOps knows, access to source code alone doesn’t solve the visibility problem. You need insight into artifacts, pipelines, environment variables, configurations, and more. We’re talking about a whole-of-lifecycle approach—not a repo review.

Navigating the Legal Landscape of Generative AI: Risks for Tech Entrepreneurs

The legal framework governing generative AI is still evolving. As the technology continues to advance, the legal requirements will also change. Although the law is still playing catch-up with the technology, several jurisdictions have already implemented regulations specifically targeting AI, and others are considering similar laws. Businesses should stay informed about emerging regulations and adapt their practices accordingly. ... Several jurisdictions have already enacted laws that specifically govern the development and use of AI, and others are considering such legislation. These laws impose additional obligations on developers and users of generative AI, including with respect to permitted uses, transparency, impact assessments and prohibiting discrimination. ... In addition to AI-specific laws, traditional data privacy and security laws – including the EU General Data Protection Regulation (GDPR) and U.S. federal and state privacy laws – still govern the use of personal data in connection with generative AI. For example, under GDPR the use of personal data requires a lawful basis, such as consent or legitimate interest. In addition, many other data protection laws require companies to disclose how they use and disclose personal data, secure the data, conduct data protection impact assessments and facilitate individual rights, including the right to have certain data erased.

Five ways OSINT helps financial institutions to fight money laundering

By drawing from public data sources available online, such as corporate registries and property ownership records, OSINT tools can provide investigators with a map of intricate corporate and criminal networks, helping them unmask UBOs. This means investigators can work more efficiently to uncover connections between people and companies that they otherwise might not have spotted. ... External intelligence can help analysts to monitor developments, so that newer forms of money laundering create fewer compliance headaches for firms. Some of the latest trends include money muling, where criminals harness channels like social media to recruit individuals to launder money through their bank accounts, and trade-based laundering, which allows bad actors to move funds across borders by exploiting international complexity. OSINT helps identify these emerging patterns, enabling earlier intervention and minimizing enforcement risks. ... When it comes to completing suspicious activity reports (SARs), many financial institutions rely on internal data, spending millions on transaction monitoring, for instance. While these investments are unquestionably necessary, external intelligence like OSINT is often neglected – despite it often being key to identifying bad actors and gaining a full picture of financial crime risk.

The hard problem in data centres isn’t cooling or power – it’s people

Traditional infrastructure jobs no longer have the allure they once did, with Silicon Valley and startups capturing the imagination of young talent. Let’s be honest – it just isn’t seen as ‘sexy’ anymore. But while people dream about coding the next app, they forget someone has to build and maintain the physical networks that power everything. And that ‘someone’ is disappearing fast. Another factor is that the data centre sector hasn’t done a great job of telling its story. We’re seen as opaque, technical and behind closed doors. Most students don’t even know what a data centre is, and until something breaks it doesn’t even register. That’s got to change. We need to reframe the narrative. Working in data centres isn’t about grey boxes and cabling. It’s about solving real-world problems that affect billions of people around the world, every single second of every day. ... Fixing the skills gap isn’t just about hiring more people. It’s about keeping the knowledge we already have in the industry and finding ways to pass it on. Right now, we’re on the verge of losing decades of expertise. Many of the engineers, designers and project leads who built today’s data centre infrastructure are approaching retirement. While projects operate at a huge scale and could appear exciting to new engineers, we also have inherent challenges that come with relatively new sectors.

Multi-party computation is trending for digital ID privacy: Partisia explains why

The main idea is achieving fully decentralized data, even biometric information, giving individuals even more privacy. “We take their identity structure and we actually run the matching of the identity inside MPC,” he says. This means that neither Partisia nor the company that runs the structure has the full biometric information. They can match it without ever decrypting it, Bundgaard explains. Partisia says it’s getting close to this goal in its Japan experiment. The company has also been working on a similar goal of linking digital credentials to biometrics with U.S.-based Trust Stamp. But it is also developing other identity-related uses, such as proving age or other information. ... Multiparty computation protocols are closing that gap: Since all data is encrypted, no one learns anything they did not already know. Beyond protecting data, another advantage is that it still allows data analysts to run computations on encrypted data, according to Partisia. There may be another important role for this cryptographic technique when it comes to privacy. Blockchain and multiparty computation could potentially help lessen friction between European privacy standards, such as eIDAS and GDPR, and those of other countries. “I have one standard in Japan and I travel to Europe and there is a different standard,” says Bundgaard.

MIT report misunderstood: Shadow AI economy booms while headlines cry failure

While headlines trumpet that “95% of generative AI pilots at companies are failing,” the report actually reveals something far more remarkable: the fastest and most successful enterprise technology adoption in corporate history is happening right under executives’ noses. ... The MIT researchers discovered what they call a “shadow AI economy” where workers use personal ChatGPT accounts, Claude subscriptions and other consumer tools to handle significant portions of their jobs. These employees aren’t just experimenting — they’re using AI “multiples times a day every day of their weekly workload,” the study found. ... Far from showing AI failure, the shadow economy reveals massive productivity gains that don’t appear in corporate metrics. Workers have solved integration challenges that stymie official initiatives, proving AI works when implemented correctly. “This shadow economy demonstrates that individuals can successfully cross the GenAI Divide when given access to flexible, responsive tools,” the report explains. Some companies have started paying attention: “Forward-thinking organizations are beginning to bridge this gap by learning from shadow usage and analyzing which personal tools deliver value before procuring enterprise alternatives.” The productivity gains are real and measurable, just hidden from traditional corporate accounting.

The Price of Intelligence

Indirect prompt injection represents another significant vulnerability in LLMs. This phenomenon occurs when an LLM follows instructions embedded within the data rather than the user’s input. The implications of this vulnerability are far-reaching, potentially compromising data security, privacy, and the integrity of LLM-powered systems. At its core, indirect prompt injection exploits the LLM’s inability to consistently differentiate between content it should process passively (that is, data) and instructions it should follow. While LLMs have some inherent understanding of content boundaries based on their training, they are far from perfect. ... Jailbreaks represent another significant vulnerability in LLMs. This technique involves crafting user-controlled prompts that manipulate an LLM into violating its established guidelines, ethical constraints, or trained alignments. The implications of successful jailbreaks can potentially undermine the safety, reliability, and ethical use of AI systems. Intuitively, jailbreaks aim to narrow the gap between what the model is constrained to generate, because of factors such as alignment, and the full breadth of what it is technically able to produce. At their core, jailbreaks exploit the flexibility and contextual understanding capabilities of LLMs. While these models are typically designed with safeguards and ethical guidelines, their ability to adapt to various contexts and instructions can be turned against them.

The Strategic Transformation: When Bottom-Up Meets Top-Down Innovation

The most innovative organizations aren’t always purely top-down or bottom-up—they carefully orchestrate combinations of both. Strategic leadership provides direction and resources, while grassroots innovation offers practical insights and the capability to adapt rapidly. Chynoweth noted how strategic portfolio management helps companies “keep their investments in tech aligned to make sure they’re making the right investments.” The key is creating systems that can channel bottom-up innovations while ensuring they support the organization’s strategic objectives. Organizations that succeed in managing both top-down and bottom-up innovation typically have several characteristics. They establish clear strategic priorities from leadership while creating space for experimentation and adaptation. They implement systems for capturing and evaluating innovations regardless of their origin. And they create mechanisms for scaling successful pilots while maintaining strategic alignment. The future belongs to enterprises that can master this balance. Pure top-down enterprises will likely continue to struggle with implementation realities and changing market conditions. In contrast, pure bottom-up organizations would continue to lack the scale and coordination needed for significant impact.

Digital-first doesn’t mean disconnected for this CEO and founder

“Digital-first doesn’t mean disconnected – it means being intentional,” she said. For leaders it creates a culture where the people involved feel supported, wherever they’re working, she thinks. She adds that while many organisations found themselves in a situation where the pandemic forced them to establish a remote-first system, very few actually fully invested in making it work well. “High performance and innovation don’t happen in isolation,” said Feeney. “They happen when people feel connected, supported and inspired.” Sentiments which she explained are no longer nice to have, but are becoming a part of modern organisational infrastructure. One in which people are empowered to do their best work on their own terms. ... “One of the biggest challenges I have faced as a founder was learning to slow down, especially when eager to introduce innovation. Early on, I was keen to implement automation and technology, but I quickly realised that without reliable data and processes, these tools could not reach their full potential.” What she learned was, to do things correctly, you have to stop, review your foundations and processes and when you encounter an obstacle, deal with it, because though the stopping and starting might initially be frustrating, you can’t overestimate the importance of clean data, the right systems and personnel alignment with new tech.

Daily Tech Digest - May 08, 2025

Quote for the day:

Don't fear failure. Fear being in the exact same place next year as you are today. - Unknown

Security Tools Alone Don't Protect You — Control Effectiveness Does

Buying more tools has long been considered the key to cybersecurity performance. Yet the facts tell a different story. According to the Gartner report, "misconfiguration of technical security controls is a leading cause for the continued success of attacks." Many organizations have impressive inventories of firewalls, endpoint solutions, identity tools, SIEMs, and other controls. Yet breaches continue because these tools are often misconfigured, poorly integrated, or disconnected from actual business risks. ... Moving toward true control effectiveness takes more than just a few technical tweaks. It requires a real shift - in mindset, in day-to-day practice, and in how teams across the organization work together. Success depends on stronger partnerships between security teams, asset owners, IT operations, and business leaders. Asset owners, in particular, bring critical knowledge to the table - how their systems are built, where the sensitive data lives, and which processes are too important to fail. Supporting this collaboration also means rethinking how we train teams. ... Making security controls truly effective demands a broader shift in how organizations think and work. Security optimization must be embedded into how systems are designed, operated, and maintained - not treated as a separate function.

APIs: From Tools to Business Growth Engines

Apart from earning revenue, APIs also offer other benefits, including providing value to customers, partners and internal stakeholders through seamless integration and improving response time. By integrating third-party services seamlessly, APIs allow businesses to offer feature-rich, convenient and highly personalized experiences. This helps improve the "stickiness" of the customer and reduces churn. ... As businesses adopt cloud solutions, develop mobile applications and transition to microservice architectures, APIs have become a critical foundation of technological innovation. But their widespread use presents significant security risks. Poorly secured APIs can be prone to becoming cyberattack entry points, potentially exposing sensitive data, granting unauthorized access or even leading to extensive network compromises. ... Managing the API life cycle using specialized tools and frameworks is also essential. This ensures a structured approach in the seven stages of API life cycle: design, development, testing, deployment, API performance monitoring, maintenance and retirement. This approach maximizes their value while minimizing risks. "APIs should be scalable and versioned to prevent breaking changes, with clear documentation for adoption. Performance should be optimized through rate limiting, caching and load balancing ..." Musser said.

How to Slash Cloud Waste Without Annoying Developers

Waste in cloud spending is not necessarily due to negligence or a lack of resources; it’s often due to poor visibility and understanding of how to optimize costs and resource allocations. Ironically, Kubernetes and GitOps were designed to enable DevOps practices by providing building blocks to facilitate collaboration between operations teams and developers ... ScaleOps’ platform serves as an example of an option that abstracts and automates the process. It’s positioned not as a platform for analysis and visibility but for resource automation. ScaleOps automates decision-making by eliminating the need for manual analysis and intervention, helping resource management become a continuous optimization of the infrastructure map. Scaling decisions, such as determining how to vertically scale, horizontally scale, and schedule pods onto the cluster to maximize performance and cost savings, are then made in real time. This capability forms the core of the ScaleOps platform. Savings and scaling efficiency are achieved through real-time usage data and predictive algorithms that determine the correct amount of resources needed at the pod level at the right time. The platform is “fully context-aware,” automatically identifying whether a workload involves a MySQL database, a stateless HTTP server, or a critical Kafka broker, and incorporating this information into scaling decisions, Baron said.

How to Prevent Your Security Tools from Turning into Exploits

Attackers don't need complex strategies when some security tools provide unrestricted access due to sloppy setups. Without proper input validation, APIs are at risk of being exploited, turning a vital defense mechanism into an attack vector. Bad actors can manipulate such APIs to execute malicious commands, seizing control over the tool and potentially spreading their reach across your infrastructure. Endpoint detection tools that log sensitive credentials in plain text worsen the problem by exposing pathways for privilege escalation and further compromise. ... If monitoring tools and critical production servers share the same network segment, a single compromised tool can give attackers free rein to move laterally and access sensitive systems. Isolating security tools into dedicated network zones is a best practice to prevent this, as proper segmentation reduces the scope of a breach and limits the attacker's ability to move laterally. Sandboxing adds another layer of security, too. ... Collaboration is key for zero trust to succeed. Security cannot be siloed within IT; developers, operations, and security teams must work together from the start. Automated security checks within CI/CD pipelines can catch vulnerabilities before deployment, such as when verbose logging is accidentally enabled on a production server.

Fortifying Your Defenses: Ransomware Protection Strategies in the Age of Black Basta

What sets Black Basta apart is its disciplined methodology. Initial access is typically gained through phishing campaigns, vulnerable public-facing applications, compromised credentials or malicious software packages. Once inside, the group moves laterally through the network, escalates privileges, exfiltrates data and deploys ransomware at the most damaging points. Bottom line: Groups like Black Basta aren’t using zero-day exploits. They’re taking advantage of known gaps defenders too often leave open. ... Start with multi-factor authentication across remote access points and cloud applications. Audit user privileges regularly and apply the principle of least privilege. Consider passwordless authentication to eliminate commonly abused credentials. ... Unpatched internet-facing systems are among the most frequent entry points. Prioritize known exploited vulnerabilities, automate updates when possible and scan frequently. ... Secure VPNs with MFA. Where feasible, move to stronger architectures like virtual desktop infrastructure or zero trust network access, which assumes compromise is always a possibility. ... Phishing is still a top tactic. Go beyond spam filters. Use behavioral analysis tools and conduct regular training to help users spot suspicious emails. External email banners can provide a simple warning signal.

AI Emotional Dependency and the Quiet Erosion of Democratic Life

Byung-Chul Han’s The Expulsion of the Other is particularly instructive here. He argues that neoliberal societies are increasingly allergic to otherness: what is strange, challenging, or unfamiliar. Emotionally responsive AI companions embody this tendency. They reflect a sanitized version of the self, avoiding friction and reinforcing existing preferences. The user is never contradicted, never confronted. Over time, this may diminish one’s capacity for engaging with real difference; precisely the kind of engagement required for democracy to flourish. In addition, Han’s Psychopolitics offers a crucial lens through which to understand this transformation. He argues that power in the digital age no longer represses individuals but instead exploits their freedom, leading people to voluntarily submit to control through mechanisms of self-optimization, emotional exposure, and constant engagement. ... As behavioral psychologist BJ Fogg has shown, digital systems are designed to shape behavior. When these persuasive technologies take the form of emotionally intelligent agents, they begin to shape how we feel, what we believe, and whom we turn to for support. The result is a reconfiguration of subjectivity: users become emotionally aligned with machines, while withdrawing from the messy, imperfect human community.

From prompts to production: AI will soon write most code, reshape developer roles

While that timeline might sound bold, it points to a real shift in how software is built, with trends like vibe coding already taking off. Diego Lo Giudice, a vice president analyst at Forrester Research, said even senior developers are starting to leverage vibe as an additional tool. But he believes vibe coding and other AI-assisted development methods are currently aimed at “low hanging fruit” that frees up devs and engineers for more important and creative tasks. ... Augmented coding tools can help brainstorm, prototype, build full features, and check code for errors or security holes using natural language processing — whether through real-time suggestions, interactive code editing, or full-stack guidance. The tools streamline coding, making them ideal for solo developers, fast prototyping, or collaborative workflows, according to Gartner. GenAI tools include prompt-to-application tools such as StackBlitz Bolt.new, Github Spark, and Lovable, as well as AI-augmented testing tools such as BlinqIO, Diffblue, IDERA, QualityKiosk Technologies and Qyrus. ... Developers find genAI tools most useful for tasks like boilerplate generation, code understanding, testing, documentation, and refactoring. But they also create risks around code quality, IP, bias, and the effort needed to guide and verify outputs, Gartner said in a report last month.

Navigating the Warehouse Technology Matrix: Integration Strategies and Automation Flexibility in the IIoT Era

Warehouses have evolved from cost centers to strategic differentiators that directly impact customer satisfaction and competitive advantages. This transformation has been driven by e-commerce growth, heightened consumer expectations, labor challenges, and rapid technological advancement. For many organizations, the resulting technology ecosystem resembles a patchwork of systems struggling to communicate effectively, creating what analysts term “analysis paralysis” where leaders become overwhelmed by options. ... Among warehouse complexity dimensions, MHE automation plays a pivotal role—and it is easy to determine where you are on the Maturity Model. Organizations at Level 5 in automation automatically reach Level 5 overall complexity due to the integration, orchestration and investment needed to take advantage of MHE operational efficiencies. ... Providing unified control for diverse automation equipment, optimizing tasks and simplifying integration. Put simply, this is a software layer that coordinates multiple “agents” in real time, ensuring they work together without clashing. By dynamically assigning and reassigning tasks based on current workloads and priorities, these platforms reduce downtime, enhance productivity, and streamline communication between otherwise siloed systems.

How AI-Powered OSINT is Revolutionizing Threat Detection and Intelligence Gathering

Police and intelligence officers have traditionally relied on tips, informants, and classified sources. In contrast, OSINT draws from the vast “digital public square,” including social media networks, public records, and forums. For example, even casual social media posts can signal planned riots or extremist recruitment efforts. India’s diverse linguistic and cultural landscape also means that important signals may appear in dozens of regional languages and scripts – a scale that outstrips human monitoring. OSINT platforms address this by incorporating multilingual analysis, automatically translating and interpreting content from Hindi, Tamil, Telugu, and more. In practice, an AI-driven system can flag a Tamil-language tweet with extremist rhetoric just as easily as an English Facebook post. ... Artificial intelligence is what turns raw OSINT data into strategic intelligence. Machine learning and natural language processing (NLP) allow systems to filter noise, detect patterns and make predictions. For instance, sentiment analysis algorithms can gauge public mood or support for extremist ideologies in real time. By tracking language trends and emotional tone across social media, AI can alert analysts to rising anger or unrest. In one recent case study, an AI-powered OSINT tool identified over 1,300 social media accounts spreading incendiary propaganda during Delhi protests.

How to Determine Whether a Cloud Service Delivers Real Value

The cost of cloud services varies widely, but so does the functionality they offer. This means an expensive service may be well worth the price — if the capabilities it offers deliver a great deal of value. On the other hand, some cloud services simply cost a lot without providing much in the way of value. For IT organizations, then, a primary challenge in selecting cloud services is figuring out how much value they generate relative to their cost. This is rarely straightforward because what is valuable to one team might be of little use to another. ... No one can predict how cloud service providers may change their pricing or features in the future, of course. But you can make reasonable predictions. For instance, there's an argument to be made (and I will make it) that as generative AI cloud services mature and AI adoption rates increase, cloud service providers will raise fees for AI services. Currently, most generative AI services appear to be operating at a steep financial loss — which is unsurprising because all of the GPUs powering AI services don't just pay for themselves. If cloud providers want to make money on genAI, they'll probably need to raise their rates sooner or later, potentially reducing the value that businesses leverage from generative AI.