OVHcloud announces new Premier 2027 hardware for Managed VMware vSphere

Posted in Commentary with tags on May 28, 2026 by itnerd

OVHcloud announces new Premier 2027 hardware for its Managed VMware vSphere solution. Available in the OVHcloud Private Cloud universe, Managed VMware vSphere is designed for enterprise grade environments to support the most critical use cases: cloud migration, disaster recovery, enterprise application hosting and application modernization. 

The Premier 2027 server range has been designed to provide new VMware environments and seamlessly scale out existing ones, with enhanced performance, scalability and flexibility.

With more compute resources, featuring up to 40% more CPU cores (compared to previous Premier generation) leveraging 5th generation Intel Xeon Scalable processors (code name Emerald Rapids) the Premier 2027 hardware comes with up to 1.5 TB of memory per host for memory intensive applications. To match these new hardware capabilities, the 2027 generation hardware is equipped with high performance NVMe drives and up to 50 Gbps private bandwidth included for improved data throughput. 

Offering better performance to address the most demanding workloads, the Premier 2027 hardware line comes with better granularity on cores and a range of choices to meet all use cases while benefiting from OVHcloud’s best performance/price ratio. 

Premier 2027 hardware is available now in France, including in Canada, the SecNumCloud 3.2 Region, and Europe. Deployment in the US is expected soon.

Resources 

UK Surveillance Levels Exposed

Posted in Commentary with tags on May 28, 2026 by itnerd

Britain has become one of the most watched nations on Earth. According to a 2021 British Security Industry Association report, approximately 21 million CCTV cameras now operate across the country,  yet what’s far less understood is the dramatic variation in who’s watching whom, and with what technology.

To find out, Comparitech filed Freedom of Information requests with all 380 UK councils and 48 police forces, mapping exactly which parts of the country are under the heaviest surveillance. The research doesn’t stop at camera counts as it reveals which councils and forces have quietly adopted facial recognition technology (FRT) and automatic number plate recognition (ANPR)  and benchmarks UK surveillance levels against major cities around the world.

Key findings include:

  • Britain is home to seven of the world’s 20 most surveilled places, putting UK towns and cities in the same league as authoritarian regimes
  • A single London police force operates 31,000+ cameras, a surveillance network bigger than some entire countries
  • One East London council alone has over 3,000 cameras making it the highest of any council in the UK
  • A Northern England council has quietly built the UK’s biggest facial recognition network with 120 cameras that can scan and identify faces in real time
  • One UK police force monitors residents at a rate of nearly 49 cameras per 1,000 people
  • Council camera coverage peaks in one UK country, reaching 3.6 cameras per 1,000 people

Additionally, Rebecca Moody, Head of Data Research at Comparitech has provided her insights on the findings:

“The report highlights a clear imbalance in the levels of surveillance across the UK. While some councils have opted for widespread camera systems, others have steered clear — and, as we found, this has little (if anything) to do with crime rates.

From a privacy perspective, what’s also concerning is the use of real-time systems, such as ANPR and facial recognition. While they’re in place for certain tasks, e.g. to monitor cars for traffic violations and to seek out persons of interest, they ultimately subject all citizens to mass surveillance. And, as we note, there’s also a worrying risk of “mission creep”, whereby these systems are promoted as helping X but, after a while, they’re also used to combat Y, and then Z, until, before we know it, their use is extensive and widespread. Essentially, once a system is installed under the guise of combating a certain crime, it can be easily rolled out into other areas. For example, ANPR was introduced as an anti-terrorism tool but has quickly become a key system to help with traffic enforcement.”

You can find more here: https://www.comparitech.com/news/watching-you-funded-by-you-number-of-cctv-cameras-by-uk-council-police-force/

Click Or Trick (CVE-2025-59199): Escaping the Sandbox with Windows URIs

Posted in Commentary with tags on May 28, 2026 by itnerd

SafeBreach Labs has uncovered a new one-click sandbox escape technique in Windows 11 that allows an attacker to achieve escalated code execution and arbitrary write from a low-integrity process with nothing more than a single user click.

The research shows how multiple legitimate Windows features can be chained together to achieve arbitrary write outside the sandbox, including COM objects, toast notifications, Snipping Tool URI handlers, Microsoft Teams, and Chromium’s remote debugging functionality. The attack requires only a single user click on a spoofed notification and does not rely on dropping traditional malware or third-party tools.

The SafeBreach Labs team is available to discuss:

  • How undocumented COM AppID flags allowed low-integrity processes to launch medium-integrity server processes.
  • The abuse of Windows notifications and URI handlers to execute attacker-controlled actions outside the sandbox boundary.
  • How Microsoft Teams and Chromium debugging functionality were leveraged to achieve arbitrary write using only native Windows applications.
  • Why chaining together legitimate operating system components creates dangerous attack paths that are difficult for defenders to detect.

Click Or Trick (CVE-2025-59199): Escaping the Sandbox with Windows URIs: https://www.safebreach.com/blog/click-or-trick-cve-2025-59199-escaping-the-sandbox-with-windows-uris/

Guest Post: Claude Coding Addiction And Why It Can Lead to Startup Burnout

Posted in Commentary on May 28, 2026 by itnerd

By Mohamed Yousuf, CEO – Smart Workforce AI

You can’t live with them, and you can’t live without them. That’s the conundrum many startup founders face when it comes to technical experts like an experienced CTO or principal engineer. The skills those experts bring can get the startup on track much faster, but the salaries they demand can cause an unmanageable financial drain.

Claude Code seems to provide a solution to the conundrum. It provides founders with technical expertise at a fraction of the cost of an engineer, but bringing Claude Code into the environment also introduces risks that can sink a startup.

How Claude Code can get founders off track

Claude Code is the kind of thing founders used to dream about as they attempted to bootstrap their way to viability. Budgets were extremely tight, but founders knew they needed to hire an expert in areas like sales, marketing, or software development to move the dream forward. Finding a way to get that work done well and on the cheap was a game-changer.

By giving startups the ability to run multiple agents on multiple fronts, Claude Code unlocks a lot of doors. One agent can work on research, another on software development, and another on DevOps; the list can go on and on.

But there is a problem with unleashing Claude Code in this way. While the platform offers a lot of value for a low cost, what you get is never perfect. Unlike the human expert with the capability to run things for you, Claude Code needs your constant attention. Rather than delegating and moving on, you find yourself going back and forth with the agents endlessly. 

For those with founder perfectionism, tapping into Claude Code can easily lead to burnout.

I experienced this firsthand. As I spent more time with Claude Code, I spent more time doing a lot of things on my own rather than delegating them to my team. I found myself wasting time on projects someone else could handle and shifting my focus away from bigger, more important things.

How founders can keep Claude Code from becoming a distraction

The key to using Claude Code optimally is knowing when to stop. Generally, that means leveraging its capabilities to get your startup off the launch pad. Once the business starts to produce, it’s time to shift AI to a different role.

Claude Code works well in the early phases of the startup process because cash flow is a challenge. Whereas in the past, founders might have turned to offshore outsourcing to make staff affordable — or give away equity in the company — now they can work with AI to build their dream business. But using AI agents as your staff is not a long-term solution.

I highly recommend that you reduce your reliance on Claude Code once you start to make revenue. There may be a time in the future, as AI becomes more intelligent and better able to understand your vision, when you can continue scaling with a full AI team. At this time, however, AI should be seen as a tech amplifier, not a human replacement.

Once a startup begins generating revenue, scale back on Claude Code and start using AI alongside subject matter experts. This will allow you to catapult your business forward with a leaner workforce.

How founders can keep Claude Code from becoming a liability

When I first started using Claude Code, it dramatically increased my efficiency and productivity. It unlocked a lot of tasks I had been dependent on others for and gave me the ability to do things the way I wanted, when I wanted. Suddenly, I could draft email copy, update marketing websites, code any software project that came to mind, and run my own sales outreach campaigns by just connecting Claude to my Google Workspace.

In reality, however, I hadn’t gained access to a coding expert. I could do more with Claude Code than I could on my own, but I was still only working with a junior developer who lacked the experience to consider the overall context and process. Having that type of “person” on your staff might work for an early-phase startup, but you don’t want to rely on that type of resource long-term.

Limiting your reliance on Claude Code limits your liability. Ultimately, you need to adopt a human-in-the-loop approach that can certify that its output will integrate, scale, and stand up to real-world challenges.

Claude Code is addictive because it gets things done quickly, which is not common for startups in their early phases. But founders must remember that startup success isn’t about getting things done. Rather, it’s about building value. Claude Code can help with that, but ultimately it needs to become a tool for those pursuing long-term business success and not just quick coding.

– Mohamed Yousuf is the CEO and founder of Smart Workforce AI, a workforce intelligence platform focused on transforming how shift-based industries operate in an AI-driven world. His background is rooted in building and scaling technology-driven systems that address structural inefficiencies in workforce planning, scheduling, and labor utilization across sectors, including healthcare, hospitality, retail, and manufacturing. Through Smart Workforce AI, Mohamed focuses on moving organizations away from rigid, approval-heavy scheduling models and toward intelligent, adaptive systems that balance operational needs with greater employee autonomy.

Megalodon supply chain attack infects more than 5,500 GitHub repositories

Posted in Commentary with tags on May 27, 2026 by itnerd

Security researchers at Safedep disclosed a large-scale software supply chain attack dubbed “Megalodon” that compromised 5,561 public GitHub repositories in roughly six hours through malicious automated commits.

The attack injected rogue GitHub Actions workflows designed to steal CI/CD secrets, CI environment variables, AWS credentials, GCP access tokens, Azure credentials, SSH private keys, Docker and Kubernetes configurations, API keys, database connection strings, GitHub Actions tokens, GitLab CI/CD tokens, and dozens of other types of secrets when affected workflows executed.

Researchers said the campaign pushed 5,718 malicious commits that appeared to come from trusted automated tooling, allowing attackers to silently poison repositories without directly modifying application code. 

The attack has been linked to the broader TeamPCP supply chain campaign, which has recently targeted npm packages, developer tools, and CI/CD ecosystems through credential theft and release pipeline compromise. Researchers said organizations with affected repositories should review workflow histories, rotate exposed secrets, and inspect cloud and CI/CD environments for signs of unauthorized access.

Jacob Krell, Senior Director: Secure AI Solutions & Cybersecurity, Suzu Labs:

   “Megalodon is a persistence operation. The dormant backdoors injected into thousands of repositories produce no visible CI activity until the attacker triggers them remotely through the GitHub API. Credential rotation alone does not resolve the compromise when the harvesting mechanism is still embedded in the workflow. Every rotation hands the attacker a fresh set.

   “This follows a pattern we have tracked since March 2026. Credentials stolen in one attack fuel the next. TeamPCP compromised a vulnerability scanner to reach LiteLLM on PyPI, and the campaign has since expanded to TanStack and GitHub itself. Megalodon extends that playbook to thousands of repositories simultaneously, converting build pipelines into credential harvesting infrastructure.

   “TeamPCP publicly released the Shai-Hulud worm source code six days before Megalodon struck over 5,500 repositories. The tooling to compromise build pipelines at scale is now commodity infrastructure. Zero trust has been applied to users and networks for years. Build pipelines and CI/CD workflows deserve the same scrutiny. Any organization that treats its build infrastructure as implicitly trusted is operating on assumptions that threat actors have already invalidated.”


Damon Small, Board of Directors, 
Xcape, Inc.:

   “The Megalodon campaign demonstrates that software supply chain attacks are evolving from hand-crafted package manipulation into industrial-scale, automated pipeline poisoning. By executing thousands of automated commits within a single afternoon, the threat actors exploited widespread architectural flaws in modern development pipelines, specifically the lack of strict branch protection rules and unhardened GitHub Actions environments. For enterprise security leaders, the primary risk is not application tampering, but the massive, silent harvest of highly privileged infrastructure keys and OpenID Connect tokens that connect development systems directly to production cloud assets.

   “Security executives must treat this incident as a critical mandate to move past basic dependency tracking; they must immediately enforce strict, global branch protection rules that require signed commits, universally implement the principle of least privilege across all continuous integration workflows, and mandate an immediate, automated rotation of all enterprise secrets to neutralize any latent credentials that may have already been swept up in this automated net.

Critical Takeaways

  •    “Pipelines are the new perimeter: Attackers have realized it is far more efficient to poison the automated workflow files that hold the keys to your cloud kingdoms than it is to search for vulnerabilities in your application source code.
  •    “The illusion of trusted identities: Relying on automated commit messages or friendly bot personas to bypass pull request reviews creates a massive security blind spot that automated scripts can exploit across thousands of repositories simultaneously.
  •    “Ephemeral tokens require hardening: Unchecked GITHUB_TOKEN permissions within actions files can allow automated scripts to read repository contents and exfiltrate environment variables, requiring a hard enforcement of read-only defaults across the organization.

   “When an automated campaign can backdoor over five thousand repositories in less time than it takes to complete an executive status meeting, your manual pull request review policy is no longer a defense mechanism, it is a historical artifact.

   “Moving forward, security leaders must assume that every continuous integration environment is a hostile network, shifting their defense strategy from preventing commits to strictly limiting the blast radius of runtime tokens.”

Ryan McCurdy, VP of Marketing, Liquibase:

   “Megalodon is a reminder that the attack surface is no longer just the code. It is the automation trusted to move code into live environments. Once a compromised workflow can reach secrets, cloud credentials, and database connection strings, the pipeline stops being plumbing and starts acting like a privileged identity. That is the shift enterprise security models still have not caught up to.”

Time to shift your strategy. Because the attack surface has become broader. And you’re very much the target.

FBI again warns of Kali365 phishing service targeting Microsoft 365 accounts

Posted in Commentary with tags on May 27, 2026 by itnerd

The FBI is still warning about the Kali365 phishing-as-a-service platform (PhaaS) that is used to hijack Microsoft 365 accounts by abusing OAuth device code authentication to steal session tokens and bypass MFA. If you haven’t read the warning from the FBI, it should be required reading.

Commenting on this news is Dan Moore, Sr. Director, CIAM Strategy & Identity Standards at FusionAuth:

“Device code phishing works because the user does everything right. They visit a real Microsoft page, complete a real login and MFA challenge, and enter the code. By doing so, the user hands an attacker real long-lived tokens for accessing real applications. The default Microsoft refresh token is good for 90 days. Worse, it renews itself every time it’s used.

The login and MFA are completed by a legitimate user on the attacker’s behalf. An easy fix: disallow superfluous OAuth grants. The device code grant exists for legitimate reasons; I wouldn’t want to type a password into my printer or smart TV when I could use my phone. But almost all enterprise users don’t need it (yes, yes, carve out exceptions for engineering teams who actually use CLI tools). Leaving it accessible is a configuration choice and attackers are actively exploiting it.

If your organization can’t block the device code grant entirely, at minimum you need short refresh token lifetimes and aggressive revocation. A captured refresh token gives persistent access until it’s expired or revoked. How long that window stays open is up to you.”

It’s time to refresh how one manages devices. Otherwise the possibility of getting pwned is very high.

Open-source DockSec uses AI to cut through vulnerability noise in Docker images

Posted in Commentary with tags on May 27, 2026 by itnerd

DockSec is making waves for applying AI to one of container security’s most persistent problems — the gap between what scanners find and what security teams can actually act on. But the deeper story is what happens when AI becomes the layer deciding which vulnerabilities matter, and most organizations have no visibility into how those decisions are being made.

Gidi Cohen, CEO & Co-founder, Bonfy.AI had this to say:

“The DockSec project highlights something the security industry has been reluctant to admit: detection has never been the hard part. Finding problems — whether CVEs in a container image or sensitive data in an AI workflow — is a solved problem. 

What remains unsolved is what happens next.

Patel’s frustration is familiar to anyone building serious security programs today. You scan, you find hundreds of signals, and then the real work begins: figuring out which of those findings actually matter, in this context, for this system, right now. Without that, findings pile up and nothing gets fixed.

The gap between detection and action is not a tooling gap. It is an accuracy and context gap. A finding without context is just noise. And noise, as every security team knows, is the enemy of enforcement.

This is the broader challenge facing data security across every domain, not just containers. Whether the system is inspecting a Docker image, a document leaving a corporate environment, or data flowing through an AI agent, the core problem is the same: detection is easy, but accurate, contextual enforcement is hard.

For years, the industry accepted this gap as a given — something to manage, not solve. AI is now removing that option. In automated, agent-driven workflows, there is no human in the loop to catch what the system gets wrong. If enforcement is not accurate enough to act on without review, it does not happen at all.

What DockSec gets right — and what every security tool should aspire to — is closing the distance between finding and fixing. Surfacing a signal is the beginning of the work, not the end. The goal is a decision the system can act on with confidence.

That principle applies well beyond containers. It is the standard data security needs to hold itself to across every surface where AI is now making decisions.”

It’s become one of those cases where security has to be top of mind and whether AI is involved or not. Sigh.

U.S. employers are falling behind their own workforce on AI 

Posted in Commentary with tags on May 27, 2026 by itnerd

Nexthink has issued new analysis showing that employer support for AI is lagging real-world U.S. workforce adoption. Drawing on data from Gallup, the Federal Reserve Bank of New York, JFF, and Forrester – combined with Nexthink usage data from millions of endpoints – the findings show AI adoption has become a game of chance, with employees left to navigate tools without support or guidance.

According to Gallup, 28% of U.S. employees now use AI at work at least a few times a week. Yet research from the Federal Reserve Bank of New York shows just 15.9% of workers say their employer currently offers any AI training – a gap that makes clear employer support is failing to keep pace with AI usage. Nearly six in ten workers who consider AI training important are not being offered it, with the New York Fed finding demand for training (38%) more than double the share of employers providing it.

Despite this, JFF research shows 56% of workers have not been consulted by employers on how AI tools are used in their work. And when they seek guidance, workers turn to social media (31%), news articles (27%), or friends and family (21%) rather than employers (9%).

The scale of unsupported AI use is already visible. Nexthink data, drawn from 4.9 million sessions per day across 3.4 million employees, shows GenAI users engaging with these tools an average of 10 times a day and spending three hours and 14 minutes per week doing so. With adoption at this level occurring without formal guidance, the window for employers to get ahead of adoption is narrowing fast.

The challenge will only become more pronounced as AI becomes a larger part of everyday work. Forrester projects that AI will augment 20% of jobs over the next five years, raising the stakes for employers to understand not only whether AI tools are being used, but whether employees have the support, training and digital experience to use them effectively.

Detectify launches MCP Server to secure the autonomous coding loop

Posted in Commentary with tags on May 27, 2026 by itnerd

Detectify has announced the launch of the Detectify MCP (Model Context Protocol) Server, a new integration layer that brings Detectify’s security testing engines directly into AI-driven development workflows, helping coding agents find and validate exploitable vulnerabilities and interpret attack surface data with unprecedented precision.

As organizations increasingly rely on AI agents to write, refactor, and modernize code, software production is accelerating faster than many security teams can realistically review or govern. Whether through official engineering initiatives or shadow AI adoption by developers eager to speed up work, AI-assisted development can help eliminate some common coding mistakes. It is also dramatically increasing the volume of software, services, APIs, and infrastructure organizations must continuously track and secure. The result is a growing visibility and governance challenge, compounded by shadow IT and shadow AI adoption, where organizations may write cleaner code while simultaneously losing track of what they are deploying and exposing.

The Detectify MCP Server is designed to close that gap by giving AI agents a standardized way to augment development and security workflows with AI-assisted access to Detectify findings and capabilities, allowing them to access and act on real-time security findings as part of autonomous development workflows. Rather than relying on periodic reviews or delayed security handoffs, organizations can embed continuous validation more directly into the software delivery process as code, infrastructure, and services evolve.

Key MCP Server capabilities include:

  • “Find & Fix” Automation: Instead of security findings landing in a static backlog, they can now be handed directly to AI agents as structured remediation tasks. Agents can generate a patch, trigger a Detectify validation scan to confirm the vulnerability is resolved, and present a verified fix for human review.
  • Conversational Command: Query scan results, monitor asset status, and surface high-severity findings through natural-language interactions connected to the Detectify MCP Server.
  • Frictionless Setup: A lightweight configuration allows organizations to connect their preferred AI tools to the remotely hosted Detectify MCP server for simplified deployment and connectivity.

Traditional application security workflows were built around slower development cycles, where human review and periodic testing could reasonably keep pace with software delivery. In modern AI-assisted environments, those assumptions are increasingly breaking down as code, infrastructure, and services evolve continuously.

The launch reflects a broader shift in AppSec toward continuous, real-time security validation. While LLMs excel at reasoning, frontier models operate at a speed and cost-profile that makes large-scale security testing impossible. Detectify solves this by monitoring millions of changing domains using compiled, deterministic code, while the MCP Server combines that scale with agentic workflows to help security operate at the same velocity as engineering.

As AI-assisted development continues to accelerate engineering velocity, organizations face increasing pressure to move beyond one-time security reviews and maintain continuous visibility into what exists across their attack surface.

The Detectify MCP Server will be available soon as part of Detectify’s continued investment in AI-native application security. For more information, visit Detectify.com.

AI Adoption Creates Critical Cloud Security Gaps for Enterprises

Posted in Commentary with tags on May 27, 2026 by itnerd

Check Point has released its 2026 Cloud Security Report: Enter the AI Era, revealing a growing disconnect between rapid AI adoption and security readiness.

The report reveals a critical shift from the cloud “blind spots” of 2025 to a deeper challenge in 2026: organizations are no longer just struggling with visibility, but with governance, control, and real-time enforcement. AI is changing how users behave, how applications communicate, and where threats enter the environment. This year, 77% of organizations have updated their security strategy for cloud in response to AI, yet only 26% report having the architecture to enforce it. This reveals a 51-point gap between intent and capability.

Meanwhile, attackers are weaponizing AI tools to accelerate phishing, generate malware, and launch adversarial attacks faster than traditional security models can respond. The impact is already measurable: 78% of organizations reported confirmed or suspected AI-related security incidents over the past year.

Key findings for cloud-native environments include:

  • Infrastructure Misalignment: 52% of AI workloads span hybrid environments, yet 64% say their architecture needs redesign
  • Perimeter Gaps: 76% rate datacenter security as critical for AI, but only 35% say it can support current needs
  • Performance Challenges: Only 24% can fully inspect AI traffic without impacting performance; 71% report increased WAF false positives
  • Operational Complexity: 88% say AI has increased security complexity; 67% report fragmented policies
  • Limited Visibility: 54% of organizations have experienced an AI-related security incident, while another 24% cannot confirm due to lack of visibility. This means more than three-quarters have either been hit or cannot determine whether they have
  • Identity Risks: 48% cite non-human identities (AI agents, APIs) as a top concern
  • Inconsistent access model: Organizations have yet to converge on a single access model. 24% say they have no AI-specific access controls, and only 16% enforce controls consistently across the environment

Closing the AI Security Gap

To address these challenges, the report emphasizes the need for a unified, prevention-first architecture across cloud, datacenter, SaaS, and endpoints.

Check Point’s Hybrid Mesh Network Security approach delivers:

  1. Unified Management: 86% of leaders rate unified security management across cloud, datacenter, and edge as critical for AI workloads. A hybrid mesh architecture keeps policies and protections consistent everywhere, no matter where data or workloads run
  2. Prevention-First Security: Real-time blocking of ransomware, zero-day threats, and data leaks using AI-driven insights, validated by a 99.8% security effectiveness score in the 2026 Miercom report
  3. Secure Connectivity and Threat Prevention: Identity-based protection ensures every user, device, and application is verified and protected in real time, with consistent security across all access points and without impacting performance
  4. AI Defense Plane: A unified control plane governing how AI is connected, deployed, and operated, with runtime protection across employee AI use, applications, and agentic systems
  5. Agentic Network Security Orchestration: The 51-point enforcement gap is more than a visibility problem; it’s also an operational one. Check Point’s newly launched Agentic Network Security Orchestration Platform shifts security teams to the level of business intent, letting AI agents autonomously handle policy creation, Zero Trust tightening, and compliance across hybrid environments

Download the full 2026 Cloud Security Report: Enter the AI Era here, or read the accompanying blog post.