Two critical PHP vulnerabilities, the widely used programming language underpinning millions of websites and web applications, have prompted urgent warnings from cybersecurity authorities worldwide.

Following reports on the 20th October that details of the vulnerabilities had leaked ahead of their scheduled disclosure, PHP developers released emergency security updates on 21 October. The UK’s National Cyber Security Centre (NCSC) urged organisations to identify affected systems and apply updates immediately, while Amazon’s threat intelligence team reported evidence of exploitation attempts dating back to 17 October.

With the vulnerabilities highlighting the potential consequences of security flaws in widely used web infrastructure, The IT Security Guru has gathered reactions from cybersecurity industry experts on the risks, implications and lessons for organisations.

Samuel Hassine, CEO and co-founder, Filigran:

“Taking a website offline for a day is a far cheaper decision than explaining a breach for a year. The agencies asking organisations to do exactly that are giving sound advice, and the speed of the coordinated response shows how much the discipline has matured. These flaws sat in code that dates back to 2004 and were found with AI. The same tools will help attackers move just as fast, and early attacks are already being reported. The job is simple to state and hard to do. Find every system running PHP, including the ones hidden inside third-party products. Update to a supported version or take it offline. Then check that nothing got in while the window was open. Patching is the easy part. Knowing what you run is the real test.” 

Sai Molige, senior manager of threat hunting at Forescout: 

“PHP2Shell has the potential to become a Log4Shell-scale event, but for a different reason. With Log4j, the main problem was finding a library you didn’t know you had. With PHP, much of the forgotten infrastructure will be found, but won’t have an upstream fix.

“The durable lesson from Log4j is that organisations should treat “How quickly can we identify where we run X” as a measurable capability separate from patching speed.

“Discovering vulnerable infrastructure, however, is only the first step. When older systems have no available fix or depend on a vendor update, organisations need to reduce exposure, restrict unnecessary connections, and isolate affected systems while planning remediation.

“AI is very good at performing variant analysis when it has a reference point, lowering the effort and expertise required. That could increase the volume of attempts we see with these critical vulnerabilities, even if many never turn into full exploits.

“Common places where forgotten PHP tends to live include:

• Vendor appliances whose admin UIs are PHP: NAS devices, some firewalls and VPN portals, printers, building-management panels, and OT/ICS HMIs with web front ends. Organisations cannot patch them directly and have to wait for vendors which introduces lag.
• Bundled runtimes. Control panels and commercial packages often ship their own PHP binary, invisible to the OS package manager.
• Containers pinned to old base images. The host is current; the image from 2021 isn’t.
• Marketing microsites, campaign pages, and acquired-company infrastructure, often on hosting accounts paid by credit card outside IT.
• Admin tools on dev or jump boxes: phpMyAdmin, Roundcube, Nextcloud.
• Origins behind a CDN or WAF that are still directly reachable, which quietly defeats your edge rules.

“Organisations concerned about exposure should prioritise identifying affected systems, reducing unnecessary external exposure, and follow vendor guidance for remediation or compensating controls. Teams should use a combination of external exposure scanning, host-level package managers, container or SBOM scans and network behavior to identify all implementations of PHP in their environment. Organisations who believe they are compromised should rotate secrets on exposed hosts, filter multipart at the edge, restrict agree from web workers, isolate EOL hosts. Look for classic web-shell patterns: php-fpm, httpd, or apache2 spawning sh, bash, curl, wget, or base64, new or modified .php files in web roots and outbound connections from web worker processes.”

Oliver Simonnet, Lead Cybersecurity Researcher at CultureAI:

“PHP2Shell is a clear example of how little time we now have as defenders to secure our environments in the age of AI. In a world where these types of vulnerability discoveries may become commonplace, and details being leaked before formal disclosure, exploits created exceptionally fast, and attackers exploiting the issue in the wild rapidly before fixes are even available. It’s almost impossible to justify a traditional maintenance window in this situation and what can you do if you know for a fact you’re vulnerable and you need to decide if you even can apply a temporary mitigation, or need take exposed systems offline. Its a nightmare scenario for security teams.

AI may play a part in making this worse as it helps attackers develop exploits faster, but its also what gives us the power to discover these issues so they can finally be fixed. So the challenge is now to arrive at a balance where we have the capability to not only identify exposed systems, but also develop effective mitigations and get them deployed before active exploitation can cause these types of disruptions.”

Charlotte Wilson, head of enterprise at Check Point:

“The scale of this is enormous. We’re talking about two serious security flaws in technology that underpins around three-quarters of the internet, potentially allowing criminals to access vulnerable systems remotely without even needing a password. We’ve become so dependent on digital services that we rarely stop to consider how much of our everyday lives relies on the same underlying technology. Governments, businesses, banks and public services are all connected through an increasingly complex web of systems, and when a weakness like this is discovered, huge numbers of organisations can find themselves exposed at once. It’s a bit like discovering that millions of buildings have been fitted with the same faulty lock. Suddenly, everyone is racing to change it before someone works out how to open the door.

We’ve already seen how disruption involving major technology providers can have consequences across the world, and there are growing questions about our reliance on a handful of companies to keep essential services running. Regulators are now looking much more closely at the role these providers play in our critical infrastructure. The timing is particularly concerning given the NCSC’s warnings that artificial intelligence will increase the frequency and intensity of cyberattacks. Criminals are becoming faster at identifying weaknesses and exploiting them, leaving organisations with less time to respond.

When governments are choosing to take their own websites offline rather than risk leaving them exposed, it gives you a pretty clear indication of how seriously this is being taken. The immediate priority is getting systems updated, but the bigger question is whether we’ve become too dependent on technology that can leave so many organisations vulnerable at exactly the same time.”

Ben Ronallo, director of cybersecurity operations at Black Duck:

“This is a genuine drop-everything moment for anyone running PHP. The flaws are in the PHP engine itself, so a perfectly secure application on top of a vulnerable runtime is still exposed. Updating WordPress or your framework won’t fix it. You have to update PHP itself and restart the services that run it. It’s understandable that people are confused about how this unfolded. Word of the vulnerabilities leaked on Y Combinator’s Hacker News forum two days before the planned disclosure, and PHP moved its security release up a day in response. The source of the leak hasn’t been identified, but there’s no evidence a threat group was involved, and no exploit code was released. A screenshot of the researchers’ exploit tool did circulate, which added to the alarm. In the end, the early reports were largely accurate. The main difference is severity: PHP officially rates both flaws 9.2 rather than the 10.0 some reports cited. That’s still critical, and it doesn’t change the advice. The organizations I’m most concerned about are the ones that don’t know where PHP is running in their environment. Older versions sitting in containers, appliances, or legacy sites won’t receive an official fix. Nobody wants to be building a software inventory in the middle of an emergency. You need that visibility before the next one hits.”

Tim Mackey, head of software supply chain risk strategy at Black Duck:

“Preventing leaks of any vulnerability data for a CVE prior to an embargo for the patch being published is precisely what coordinated vulnerability disclosure processes are designed to protect against. When a leak, or advance knowledge, of a vulnerability occurs the entire ecosystem surrounding the vulnerability is placed at risk. As details of the leak are published, security defenders are faced with the real risk that malicious actors could use the absence of an official patch to supply their own malicious patches. Defenders should pay extra attention to the origin of their patches and validate functional changes against official release notes. After all, a malicious patch could implant a backdoor for future use and a rush to patch might present the right opportunity for malicious actors.”

Jamie Akhtar, CEO and Co-founder of CyberSmart:

“The NCSC advises identifying PHP across your infrastructure, prioritising internet-facing systems, and not limiting the search to outdated versions. That includes appliances and services that bundle PHP, so keep monitoring for updates from third-party vendors.

Update to the latest version of PHP and apply the additional hardening steps from the PHP Team. If you cannot update, the PHP Team has provided temporary mitigations. If those cannot be applied, or would take too long, the NCSC suggests considering taking the system offline until it can be fully mitigated.”

The PHP2Shell vulnerabilities serve as a reminder of how quickly weaknesses in widely used software can become a global cybersecurity concern. As organisations work to secure affected systems, the incident reinforces the importance of timely patching, continuous monitoring and maintaining visibility across the software powering critical services.

Shane Barney, CISO at Keeper Security, said:

“The two critical flaws found in PHP, the programming language behind WordPress and countless online shops, have now led to government services in France, Denmark, Finland and the Netherlands going offline, alongside UK council sites, NHS Scotland and Wikipedia. Fixes arrived on Wednesday amid reports of millions of attempts to exploit the flaws, though it remains unclear whether any have succeeded. CERT-EU, the EU’s cybersecurity response team, had advised organisations that could not patch immediately to consider isolating their internet-facing applications.

The scale sets this apart from a routine patch cycle. PHP sits beneath sites run by multinationals, public bodies and one-person businesses alike, and most of the people running them are not security specialists. They rely on hosting providers, plugins and agencies to keep up, and many are learning about PHP for the first time this week.

The flaws sat in widely used code for years until AI tools surfaced them. OpenAI, whose model helped find them, expects similar findings to increase sharply in the coming months, as AI continues to lower the effort needed to turn a complex flaw into a working attack. Patching is only the first step, and any site exposed before it was fixed should review who has access to both the site, as well as internal systems within an organisation. Security teams should remove admin accounts that are no longer in use, implement the principle of least privilege to restrict access, replace passwords as a precaution and protect every login with multi-factor authentication.”

The post Critical PHP Vulnerabilities Spark Global Security Alert: Industry Experts React appeared first on IT Security Guru.

Organised by Eskenzi PR, the tenth annual awards ceremony took place at St Barts Pub in London, bringing together cybersecurity professionals, educators, industry leaders and advocates to recognise those whose work often goes unnoticed.

Unlike many industry awards, the Security Serious Unsung Heroes Awards are free to enter and attend. The initiative celebrates individuals and teams going above and beyond to protect businesses, communities and individuals, while also championing diversity, wellbeing, education and the next generation of cybersecurity talent.

This year’s event was sponsored by CultureAI, Filigran, OneAdvanced and The Zensory, with additional support from CyberASAP and Pulse Conferences. Media partners included Computer Weekly, Information Security Buzz and IT Security Guru.

Yvonne Eskenzi, Director of Eskenzi PR and Founder of the awards, said: “The Security Serious Unsung Heroes Awards are all about recognising the incredible people working tirelessly behind the scenes to keep our businesses, communities and country safe.

“Cybersecurity can often be a thankless profession, with the dedication and achievements of those working in the industry going largely unnoticed. These awards give us the opportunity to shine a spotlight on those individuals who consistently go above and beyond, while also celebrating the fresh perspectives and diverse talent shaping the future of the industry.

“It was fantastic to bring the cybersecurity community together once again to recognise these remarkable individuals. A huge congratulations to all our nominees and winners!”

Security Serious Unsung Heroes Awards 2026: The Winners

This year’s winners represented a broad cross-section of the cybersecurity industry, from frontline security professionals and ethical hackers to educators, content creators and community advocates.

The full list of winners is as follows:

• Cyber Correspondent: Phil Muncaster
• Godfather of Security: Andy James, Founder and CEO of Custodian360
• Godmother of Security: Dr. Emma Philpott, CEO of IASME
• Data Guardian: Peter Slevin, Cyber Engagement Senior Technical Lead at Bank of Ireland
• CISO Supremo: Andrea Litherland, CISO at Domestic & General
• Security Avengers: Revenge Porn Helpline
• Best Educator: Dr. Chidimma Opara, Senior Lecturer in AI at The Manchester Metropolitan University
• Best Ethical Hacker/Pen Tester: Dominic Mortimer, Head of Red Team at WorkNest Secure
• Channel Champion: Olly Carter, Senior Channel Sales Director, EMEA and APJ, at Forescout
• Senior Leader/Mentor: Meera Tamboli, DFIR Analyst at AVEVA
• Cybersecurity Wellbeing Advocate: Nikki Webb, Director at Custodian360
• Best Security Awareness Campaign: Cyber Local, a collaboration involving Cyber Innovations Ltd., Bournemouth University, Cybexer, Dorset Mind, Dorset Chamber and local authority stakeholders
• Diversity Champion: Segan Ebenezer Olaniyan, Information Security Analyst II at Kraken Technologies
• Apprentice/Rising Star: Jordan Daglish, Acumen Cyber
• Cyber Scribe: Dr. Runli Guo, Reducing Blast Radius LinkedIn newsletter
• Voice of Security: Cyber Agony Aunts podcast and Ant Davis, creator of The Awareness Angle
• Best Academic Entrepreneur: Dr. Peter Garraghan, CEO of Mindgard

Winners Highlight the Importance of Community and Collaboration

Among those recognised was Olly Carter of Forescout, who received the Channel Champion Award for his contribution to the cybersecurity channel ecosystem.

Carter said: “It’s a real honour to be recognised with the Channel Champion Award, but the truth is that nobody achieves anything in the channel alone! I’m incredibly fortunate to work alongside such a talented, passionate, and committed team at Forescout, and some truly fantastic partners.

“For me, the channel has always been about people, relationships, trust and working together to achieve something special.”

The Voice of Security Award was jointly awarded to the Cyber Agony Aunts podcast, hosted by Rebecca Taylor and Amelia Hewitt, and cybersecurity content creator Ant Davis.

Taylor and Hewitt said: “Cyber Agony Aunts comes from a very real place for us – it’s all about community, honesty and reminding people that behind the technology, cyber is ultimately about people.

“We’ve had some incredibly open conversations, plenty of laughs and a few tears along the way, so to see the podcast recognised like this is something we’re incredibly proud of. This award belongs just as much to our guests and the community as it does to us.”

Nikki Webb, Director at Custodian360, was recognised as Cybersecurity Wellbeing Advocate for her work supporting people across the industry.

Webb said: “Our industry asks a lot of people, long hours, high pressure, and the weight of protecting others. Looking after the people behind the screens matters just as much as the technology itself, and I’m so proud to see that recognised.”

Recognising Education, Innovation and Awareness

The awards also highlighted the importance of making cybersecurity more accessible through education, awareness and research.

Dr. Chidimma Opara received the Best Educator Award for her contribution to inspiring the next generation of cybersecurity professionals.

Reflecting on her win, Opara said: “What makes this award so special is knowing that the work I love doing as an educator is making a meaningful difference in motivating the next generation of cybersecurity professionals.

“If my students leave my classroom feeling valued, believing in themselves a little more, and inspired to reach their potential, then I know I am doing something worthwhile.”

Meanwhile, Cyber Local received the Best Security Awareness Campaign Award, recognising a collaborative initiative involving academic institutions, local organisations and cybersecurity specialists.

Emily Rosenorn-Lanng, CEO and Co-Founder of Cyber Innovations Ltd., as well as pioneer of the Cyber Local project, said: “Ours has always been about helping people feel confident and supported when something goes wrong online, so to win Best Security Awareness Initiative, in a category full of such strong work, means a huge amount to me, to the Cyber Innovations team and to everyone who worked on it with us.”

The newly introduced Cyber Scribe category was awarded to Dr. Runli Guo for her LinkedIn newsletter, Reducing Blast Radius, which explores emerging cybersecurity challenges, particularly those associated with agentic AI.

Guo explained: “Agentic AI is quickly becoming the most discussed topic in cybersecurity, yet the associated threats and risks aren’t always fully understood. With the rapid rate of change in this space, CISOs and architects simply don’t have the time to read every update.”

She added that her work focuses on sharing practical insights and hands-on demonstrations to help security professionals understand and reduce the potential impact of emerging threats.

Dr. Peter Garraghan, CEO of AI security company Mindgard, was also recognised with the Best Academic Entrepreneur Award, highlighting the role of academic research and commercial innovation in addressing new cybersecurity challenges.

A Decade of Celebrating Cybersecurity’s Unsung Heroes

The ceremony was hosted by Yvonne Eskenzi and Clive Room, Director of Pulse Conferences, with winners selected by a judging panel comprising representatives from across the cybersecurity industry, academia and media.

This year’s judges included Alex Scroxton of Computer Weekly, Sam Soares of CultureAI, Joe Pettit of Bora, Emma Fadlon of CyberASAP, Beth Maundrill of Infosecurity Magazine, Stuart Coulson of HiddenText and Holly Foxcroft of OneAdvanced, alongside Eskenzi and Room.

The evening also raised £250 for NSPCC Childline through a charity raffle.

Now in its tenth year, the Security Serious Unsung Heroes Awards continues to recognise the individuals whose contributions extend beyond technical expertise, celebrating mentorship, collaboration, community engagement and the people helping to make cybersecurity a more inclusive and supportive profession.

Further information about the awards is available at www.securityserious.com.

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Forescout’s Vedere Labs has identified a previously undocumented malware delivery platform being used in ClickFix campaigns, alongside new delivery techniques associated with malware loaders linked to Vice Society ransomware activity.

The findings, published in two research blogs, examine what happens after victims fall for ClickFix lures. These attacks trick users into copying and running malicious commands, often under the pretence of fixing a technical problem or completing a verification step.

The investigations reveal how attackers deliver different malware families, conceal malicious files and establish access that could support further compromise.

ROMULUS serves multiple malware loaders

During an incident investigation, Forescout researchers discovered a server hosting a panel called ROMULUS. Further analysis identified six IP addresses exposing the same authentication interface and revealed a platform capable of delivering multiple malware loaders.

One of those addresses had previously been identified by Huntress in a campaign that abused ChatGPT’s Custom GPTs to direct victims towards pages hosting ClickFix lures. Forescout independently observed the same malware package being delivered from another ROMULUS server.

Researchers analysed two delivery routes. One used a trojanised installer containing legitimate Stardock software to load malicious code. The other delivered LegionLoader, a malware loader active since 2019, through a series of encrypted archives.

In the LegionLoader route, an archive smaller than 1 MB expanded into an executable exceeding 880 MB. Most of the executable’s size came from artificial padding, which can push files beyond security scanners’ upload limits or sandbox analysis thresholds.

A ROMULUS statistics page also displayed installation and execution counts, a timeline and a breakdown by country, potentially allowing operators to monitor campaign performance.

Forescout said the platform’s operators remain unknown. Researchers could not determine whether ROMULUS is a private tool, a commercial criminal service, an affiliate framework or software shared between operators.

Loader investigation reveals possible connection

The second blog examines Lorem Ipsum and Axolotl, two malware loaders whose relationship had not previously been documented in public research.

The investigation followed a September incident in which attackers used ClickFix to deploy Lorem Ipsum Loader and a Python tunnel client. Forescout contained the incident before ransomware was deployed, although researchers believe ransomware delivery was the attackers’ intended goal.

The tradecraft has previously been attributed to Vice Society, a cybercriminal group associated with several ransomware families, including Rhysida.

Researchers analysed five Lorem Ipsum samples from the incident and 39 Axolotl samples. They identified an additional Lorem Ipsum delivery method using MSI installers and multi-stage PowerShell, as well as three Axolotl variants using different host programs.

The analysis also found overlapping infrastructure and similarities in the loaders’ command-and-control communications. Although their code is distinct, Forescout said the findings suggest Lorem Ipsum may be a later iteration of Axolotl. Researchers could not establish that relationship conclusively.

Forescout recommends monitoring suspicious PowerShell activity, silent installer execution and unexpected DLL loading, alongside educating users about ClickFix and related lures that direct victims to Windows Terminal or PowerShell.

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Zero trust has become one of the most overused terms in security marketing, often applied to products that simply add another layer of network segmentation. This piece looks at what zero trust actually specifies according to its foundational standard, the implementation order that works in practice, and why identity is the dependency most organizations underestimate.

What Does Zero Trust Actually Specify, Beyond the Marketing Language?

Zero trust gets used loosely enough that it has largely lost precision as a term, applied to everything from a VPN replacement to a full architectural rebuild. That imprecision is a real problem for organizations trying to evaluate vendor claims, since two products both marketed as zero trust solutions can address entirely different parts of the actual model.

Organizations working through this evaluation often look at established regional providers as part of their planning. Among them, cybersecurity solutions in Dubai offer a starting point for comparing how different providers translate the zero trust framework into an actual implementation roadmap, which varies considerably depending on an organization’s existing infrastructure.

At its core, the specification requires continuous verification of every access request, whether it originates inside or outside the traditional network perimeter, and it removes the assumption that anything on the internal network is inherently trustworthy simply by virtue of its location.

That table names the components. The harder part, and the part most vendor pitches skip, is the order in which an organization actually implements them.

What Implementation Order Actually Works, and What Stalls?

Organizations that attempt zero trust as a single, comprehensive rollout tend to stall, since the scope quickly exceeds what any team can execute without disrupting normal operations. Organizations that succeed tend to sequence the work, starting with identity infrastructure before touching network segmentation.

That sequencing is not arbitrary. Identity is the hard dependency underneath every other component of the model. Microsegmentation without solid identity verification just creates smaller trusted zones rather than removing the underlying trust assumption. Continuous monitoring without reliable identity data produces noise rather than usable signal. Getting identity right first is what makes everything built on top of it actually function as intended.

IT Security Guru’s coverage of automated tools in SaaS penetration testing touches a related sequencing question from a different angle: the growing reliance on automation to keep pace with continuous verification demands, which is exactly the kind of tooling that becomes necessary once an organization’s zero trust model matures past the identity foundation stage.

Organizations that skip the identity-first ordering often end up with what looks like a zero trust deployment on paper but functions as a rebranded VLAN structure underneath, technically segmented but still relying on implicit trust once a user or device gets past the initial checkpoint.

Where Does the NIST Standard Actually Draw the Line?

Rather than relying on vendor definitions, it helps to work from the actual specification. NIST Special Publication 800-207 lays out the zero trust architecture in detail, defining the core logical components and the tenets that distinguish a genuine implementation from marketing language attached to conventional network security.

The standard makes it clear that zero trust is a set of principles guiding architecture decisions, not a single product or technology you can buy and deploy wholesale. That framing alone rules out a large share of what gets marketed under the term, since a genuine implementation touches identity management, policy enforcement, and monitoring together rather than any one of them in isolation.

How Can an Organization Tell Real Progress From a Rebranded VLAN?

A few honest checks separate genuine progress toward zero trust from a relabeled version of existing network security. Evaluate access decisions per request based on current context, not grant broad access once a user authenticates at the start of a session. Policy enforcement should apply consistently, whether a request originates inside or outside the traditional network boundary. Monitoring should also detect anomalous access patterns after the fact, not just block unauthorized access at the point of entry.

An organization that cannot clearly explain how it makes access decisions on a per-request basis is likely still operating on the old trust model, whatever the marketing materials on its security stack claim.

FAQ

What is zero trust, in the simplest accurate terms?

It is a security model that requires continuous verification of every access request, regardless of whether it originates inside or outside the traditional network perimeter, removing the assumption that internal network location implies trustworthiness.

Why does identity have to come before network segmentation in implementation?

Identity verification is the dependency the rest of the model relies on. Segmentation and monitoring without reliable identity data produce smaller trusted zones or noisy alerts, rather than genuinely removing implicit trust.

How can an organization tell if its zero trust deployment is genuine?

Access decisions should be evaluated per request based on current context, not granted broadly after initial login, and policy enforcement should apply consistently regardless of where a request originates.

Is zero trust a product an organization can simply buy?

No. NIST’s foundational specification describes it as a set of architectural principles, not a single purchasable technology. A genuine implementation brings together identity, policy enforcement, and monitoring rather than relying on any one component alone.

The post Zero Trust in Practice: Moving Beyond the Buzzword appeared first on IT Security Guru.

Over the past few years, AI has gone from something understood and used by a select few to a cornerstone of almost every organisation. As businesses race to adopt new models, tools and autonomous agents, security and governance are struggling to keep up.

Recent incidents involving AI agents behaving in unexpected ways have offered an early glimpse of what could happen as these systems are given greater autonomy. Closer to home, organisations face a more immediate problem: employees are adopting AI tools faster than many security teams can identify, assess or control them, a point CultureAI’s Founder and CEO, James Moore, made in a recent interview with the Guru.

That raises two questions: who is responsible for AI security and governance, and do organisations really know the full extent of their AI risk?

The IT Security Guru spoke to Oliver Simonnet, Lead Cybersecurity Researcher at CultureAI, about models escaping their sandbox, shadow AI, why people overshare with LLMs, who should be holding the industry accountable, and what organisations should put in place before the next wave of adoption.

Q: How are the advances in AI changing the cyber threat landscape for attackers and defenders?

There’s nothing particularly novel happening in the AI space outside of the recent cases of models escaping their sandbox and being used to attack other organisations. Even then, it’s mostly an acceleration of what already existed.

For attackers, there’s the more typical stuff: AI lowering the bar to entry for cybercriminals and helping them become more efficient as the models become more capable. Cybercriminals are using the more traditional LLMs to speed up malware development, and to build AI capability into malware for command and control or for modifying code.

On the defence side, it’s a double-edged sword. We’ve got people rushing to adopt AI to solve problems and to aid investigations. But each time we adopt another AI technology, or embed something in an organisation, we’re also opening up all of that risk of the unknown. No one really knows how any of this works, typically, unless people want to do the due diligence and the research. You can do that, but at the speed people are adopting things, you adopt it, you deploy it, and then you hope for the best.

You adopt it, you deploy it, and then you hope for the best.

So, it’s hard for defenders to adopt and leverage these technologies without putting themselves at too much risk, or causing too many complications.

That said, AI is being incorporated into everything now, and it very clearly helps with speeding up incident response and investigations, fixing bugs in code, removing vulnerabilities and getting AI to assess things automatically.

It’s a very different world to the one we were in a couple of years ago.

Q: Why do people feel so comfortable putting sensitive information into an LLM, as opposed to a search engine?

The difference is that a traditional search engine like Google, at least before Google Search was also AI-driven, doesn’t rely on a large amount of information. The typical way we learned to use search engines was concisely, if anything. Single words at best. You put in exactly what you want, the minimum amount of typing, and ideally you get the result you’re after.

Whereas the way AI has evolved in the LLM space, it thrives, and is most efficient, when it’s given the most information it can possibly get.

So it encourages a feedback loop. Users give it as much information as they can because they know that gets them the best answer, and if the answer is not as good, they’ll probably give it even more. The less information you give it, the less reliable the outcome is ultimately going to be.

That creates a practice of, one, giving it a lot of information. And two, I think the conversational nature of it, from a psychological perspective, creates a level of trust or familiarity with the technology that lowers people’s guard considerably. It gets you chatting away, forgetting what the implications are of what’s actually going on.

You’re just more willing to have a full-blown conversation about your personal issues on your business ChatGPT account, without thinking about the fact that you’re putting all of that into third-party infrastructure, and doing it through your business account.

Then what happens one day if that information is accessed and compromised? It’s a lot worse. You probably don’t want your Google searches compromised, I’m sure, but you definitely don’t want your ChatGPT logs compromised.

Q: Employees are being encouraged to innovate and experiment with AI. How can organisations enable that without simply blocking everything?

Having visibility of what AI is being used, and how it’s being used, is key. Without that information, organisations can’t see what’s going on, know whether they’re at risk, or understand whether the tools people are using are any good.

Without visibility, they can’t quantify the risk either. Someone could ask you what risks you think you have in your business from AI adoption, but if you’ve got nothing to go by outside of “well, people are using it and everyone seems happy”, you’re going to say the risk is basically nothing, because everything seems fine.

In reality, if you have the visibility and you can see that people are sending your confidential information out left, right and centre, or disclosing private medical information into third-party applications and breaking regulations in the process, then your perceived risk is going to skyrocket, and you’re going to be worried about a fine.

Someone could ask you what risks you have from AI adoption, but if you’ve got nothing to go by, you’re going to say the risk is basically nothing, because everything seems fine.

So, adopting tools that give you visibility of general AI use matters, as does anything people can do to contain agents or deploy things locally.

Organisations also need to show some restraint when they adopt things, and not get caught up in the excitement. Take a beat, establish your controls and processes first, and then you’ve got something in place rather than immediately exposing yourself to a higher amount of risk.

Q: Who should ultimately be responsible for ensuring organisations are prepared for these risks: businesses, regulators or governments?

AI is a global problem, which makes governance particularly complicated.

The issue with established frameworks, compliance regimes and standards is that organisations can decide to adopt them or not at their own risk, depending on things like their own exposure and how public they are. Frameworks establish a baseline, but they aren’t a legal requirement.

Some industries rely heavily on mandates. Financial organisations know that during due diligence, potential partners will check for certain certifications and baseline standards before working with them. If you decide you want to be a payment processor, even if you’re just an individual, you need to make sure you’re following all the right approaches. Global standards like PCI DSS exist to protect payment card data and govern how cardholder information is handled, and if you don’t adhere to them as a financial organisation, you can be heavily fined.

I feel like there should be something like that for AI. We need one of the central bodies, whether that’s a government or an individual trade body, making firmer decisions on AI security and holding the wider industry accountable.

Whether it ends up with government depends on how the industry responds. If nobody takes the voluntary route, that’s the point at which the government should probably step in and legislate on what the outcomes are if you’re negligent in this space.

It’s slightly too early to say where that lands. I think there’s still enough time for industry regulation and standards to keep up. In the meantime, though, organisations are responsible for making sure they do everything right.

Q: Looking towards 2027 and beyond, what do you expect the next stage of AI to look like?

It’s a horrible question, to be honest, because it’s difficult to predict. If you’d asked me two years ago, I wouldn’t even have thought agents would be a thing, and now they’re basically dominating.

Right now, we’re at the early stage of them. Or maybe, in AI terms, we’re already in the late stage of them. Either way, it wasn’t something I foresaw happening so quickly.

Agentic technology will probably develop significantly further and be used a lot more. At the minute it’s still tied to certain things, whether that’s individual ecosystem services or people building agents into specific areas like development. But more general agents that are just off doing their own thing seem plausible.

Artificial general intelligence, the end goal everyone’s after, still feels like a potential fairy tale. But with the speed everything is going, I wouldn’t be surprised if it happened within the next few years. At that point, who knows. That would be a whole different universe we’re living in.

It’s going to be crazy, potentially. You could take it in any fantasy direction and it seems relatively plausible, so I’m trying to keep it as grounded as I can.

Final thoughts

Simonnet’s argument starts with a sequencing problem. Organisations are adopting AI faster than they can see it, and an organisation that cannot see what its people are using has no way to judge whether its risk is negligible or severe. It will usually assume the former, because nothing appears to be going wrong.

The behaviour underneath it is not carelessness either. LLMs work better the more they are told, and they are conversational by design, so oversharing is a product of how the technology is built rather than a failure of employee discipline. That makes it a problem to be managed with visibility and controls, rather than one to be solved with a policy reminder.

On who fixes it, he is more patient than some. Industry standards still have time to catch up, and if they don’t, legislation on negligence follows. Either way, the responsibility in the meantime sits with organisations themselves, which brings the question back to whether they can see enough of their own AI usage to act on it.

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Security researchers have uncovered a now-fixed vulnerability in agentic AI platform Manus that could have allowed attackers to hijack an AI agent through a single malicious email and potentially access a user’s connected accounts.

Researchers at Salt Labs, the research arm of Salt Security, found that Manus could interpret malicious instructions embedded within an incoming email and execute them when asked by a user to check their messages.

Manus is a general-purpose agentic AI platform capable of independently carrying out multi-step tasks including research, data analysis, content creation and software development. The platform can also connect to third-party services such as email, cloud storage and code repositories.

According to Salt Labs, this connectivity created an opportunity for an indirect prompt injection attack, in which malicious instructions contained within external content are interpreted by an AI system as commands.

During testing, researchers initially sent an email containing a direct malicious command. Manus detected and flagged the instruction, suggesting its existing guardrails were capable of recognising the attack.

However, researchers were subsequently able to disguise the command using an obscure JavaScript obfuscation technique. Manus decoded and executed the hidden code and, while the platform produced a security warning, Salt Labs said the warning appeared only after the code had already executed.

The researchers were then able to establish a reverse shell within the environment and locate credentials and tokens associated with third-party services connected to the test account.

According to Salt Labs, a successful real-world exploitation of the vulnerability could therefore have potentially enabled an attacker to reach services including a victim’s email, cloud storage and code repositories.

Significantly, the attack chain did not require the victim to click a malicious link, download a file or hand over their password. Researchers said it required just two events: a malicious email arriving in the victim’s inbox and the user subsequently asking Manus to check their messages.

The vulnerability was responsibly disclosed and has since been resolved, meaning the attack described by Salt Labs is no longer exploitable.

However, the researchers argue the findings demonstrate a wider security challenge facing agentic AI systems: detecting malicious activity may not be enough if an autonomous agent has already performed the action before a human can intervene.

As organisations increasingly give AI agents access to business applications, APIs and sensitive data, Salt Labs said security controls will need to extend beyond inspecting prompts and model behaviour to governing what agents are permitted to do across connected systems.

“The agentic domain is relatively new, and the industry is still learning how to use it correctly, and so are attackers,” said Yaniv Balmas, Head of Research at Salt Security.

“Guardrails are an important part of any agentic system that handles untrusted input, but they are often simply not enough. Anyone designing an agentic system should build robust, layered defenses rather than trusting guardrails to provide all the protection, exactly as we learned to do with traditional services.”

Balmas added that as adoption of agentic AI grows, he expects attacks targeting these systems to become an increasingly common threat vector.

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AI adoption is moving faster than most organisations can govern it. It is a familiar line by now, repeated often enough to sound routine, and that is part of the problem: it is still true, and still understated. As James Moore, CEO of AI security and governance platform CultureAI, told the IT Security Guru, this is a security challenge and a business risk, and one leaders can no longer afford to ignore.

Employees are using a growing number of known and unknown AI tools, and sensitive business data is finding its way into third-party platforms and new integrations. Security teams are finding it harder to know exactly where organisational data ends up. Meanwhile, many businesses are still relying on basic policies or bolt-on security tools to manage an increasingly complex problem.

Moore is focused on the bigger question: do organisations have enough visibility and control to use AI safely?

The IT Security Guru spoke with Moore about how the industry should define AI security and governance in the first place, why companies cannot be trusted to self-regulate, who should own AI governance internally, the danger of treating AI security as a box-ticking exercise, and why the industry may end up learning this lesson the hard way.

Q: How should businesses think about AI security and governance?

I still don’t think that we, as an industry, have fully defined AI security and governance yet, if I’m being really honest. But there are a few aspects business leaders need to think about.

You have the discovery piece. Before you do any security or governance, you have to be able to discover what is out there and what’s actually being used. The big AI security and governance companies discover a small amount of the foundational AI apps an organisation might be using, but they’re missing a huge portion of the AI footprint that’s out there. Discovery is genuinely foundational, to detect the many shadow and embedded AI in use.

Then it’s understanding, which is the context piece. Not only what’s being used, but how it’s being used, and why. Why are employees putting what they’re putting into these tools?

Then you’ve got control. Control for me is more on the security side: how do you stop people doing risky stuff inside the apps they’re using? How do you stop them using it badly while still enabling them?

And then governance sits above all of that, which is how do you prove all of the above? How do you prove you’ve got a list of the apps people are using? How do you prove you know what they’re putting into those apps? How do you prove you’ve got that security control in place?

There’s no way you can do governance without those three layers underneath it: discovery, understanding and control. Governance is the extra bit on top that proves you’re doing the right stuff.

Q: Do you think regulation needs to play a bigger role?

I strongly believe companies shouldn’t be allowed to self-regulate on AI. We need government regulation that says organisations have to have controls in place, because the majority of companies out there either have no controls or minimal controls. They’re flying completely blind.

The majority of companies out there either have no controls or minimal controls. They’re flying completely blind.

I also don’t think the general public know how far and wide their own data is going. In our own research we’ve seen sales and support people at fairly large consumer businesses putting personal customer details into ChatGPT, usually on their own personal accounts, to build emails, build websites, all kinds of crazy stuff. The consumer has no idea their data is going into those apps.

Every single time we put our platform inside a client or a prospect, the organisation sees something unexpected, and in some cases frankly quite horrendous.

Q: What are your strongest opinions on where the AI industry is heading?

I predict we’re going to end up with a bunch of platforms, the big ones, that bolt on AI security. People will buy it because it’s an easy add-on. They’ll bolt on the bare minimum to get people to buy an AI security module, so organisations can tick a box. That’s what’s been happening with cybersecurity in general: bare minimum spending, just to tick a box and say yes, we’ve got it covered.

What you’ll end up with is the organisations that are using these big platforms will not be doing AI security properly, but doing it well enough to pretend that they are.

And that will go one of two ways. Either it works, and everyone carries on for years, nice and happy. Or something goes wrong at one of these companies, whether that’s a breach or data being used in ways it never should have been, at which point everybody’s going to go, “err, we might need to do this properly.”

Q: What are the biggest AI risks businesses are facing today?

Over the past year the risk has shifted a little from people using AI on the web to using it on the desktop. With desktop usage comes more integrations, so people are connecting their desktop AI to more data sources and more third-party tools. Data is moving around more, and there’s more chance of it getting lost or misused.

There’s a lot of talk about agentic, but we’re still not seeing much of it actually happen in practice. It’s quite rare to see real agentic use inside an organisation. Most organisations are still pretty immature with this stuff, even though they might say otherwise.

But are the fundamental challenges much different to 12 months ago? Not really. It’s still about controlling what AI is being used, what data is going into it, and where that data ends up. That ultimately is the challenge.

Q: Where does CultureAI fit into that future?

Most organisations will soon have a mix of humans and agents in their org charts, with a very large number of agents doing quite a large number of jobs. So over time our focus will split between protecting human use of AI and protecting agentic AI.

Beyond that, we will be focusing on more visibility into the AI tools people are actually using, working on better classification of the data going into them, and continuing to build strong guardrails and controls around both.

Final thoughts

Moore’s argument comes back to sequence. Discovery, understanding and control have to exist before governance means anything, and in his eyes, most organisations are still missing the first step.

A module that ticks the box may satisfy an auditor for a while, but it will not tell a board which AI tools employees are actually using, what data is going into them, or where that data ends up. Those, as Moore notes, are much the same questions the industry was asking twelve months ago, only now with desktop integrations widening the surface and agents arriving behind them.

Whether organisations get ahead of that deliberately, or only after something goes badly wrong, remains an open question. On his evidence, most are still flying blind enough that they would struggle to know either way.

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Artificial intelligence is changing vulnerability discovery. At OpenSSL, we are seeing that change first-hand. A year ago, our security address received around nine separate reports and enquiries a month. It now receives around 70. AI tools can examine source code and identify potential security issues at a scale that would previously have required significant human effort.

In many ways, that’s positive. Finding vulnerabilities is an essential part of making software more secure. But there is another side to this that deserves much more attention. Every vulnerability report has to go somewhere.

Someone needs to assess whether the issue is genuine. If it is, engineers need to understand its severity, develop a fix, test that fix and manage disclosure appropriately. AI can increase the speed at which potential problems are discovered. It does not automatically increase the number of experienced engineers available to deal with them. That imbalance could become a serious issue for open-source security.

Finding a vulnerability is only the beginning

There is an understandable tendency to treat vulnerability discovery as the success story. An AI system finds something humans missed. That makes a compelling headline. But identifying a potential weakness and resolving it are very different tasks.

A report might represent a serious vulnerability. It might be something already understood. It might be technically correct but have limited real-world security impact. It might simply be wrong. Working out which of those is true requires expertise. Then, if there is a genuine vulnerability, somebody has to fix it.

Over the past 12 months we received a little over 400 vulnerability reports. 43 resulted in a published CVE. Roughly one in ten. The other nine still had to be read, understood, reproduced where we could, and answered. A report that turns out not to be a vulnerability consumes much the same expert attention as one that is — sometimes more, because establishing that something cannot be exploited is often harder than confirming that it can.

For a commercial software company with large security teams, increasing the number of reports may be manageable. For an open-source project with limited resources, a sudden increase can create a very different problem. The technology for finding possible vulnerabilities is becoming cheaper and more accessible. However, the expertise required to investigate them is not.

Businesses depend on projects they may barely know exist

This connects to a much older problem with open-source. Most technology companies know they use open-source software. What is less clear is whether they understand exactly which projects their products and services depend upon. That distinction matters.

Open-source components can sit deep inside software stacks. They work quietly, so organisations may have little reason to think about the people maintaining them. Then something goes wrong.

Heartbleed was an important moment for OpenSSL because it exposed the gap between the importance of open-source infrastructure and the resources available to support it. The industry responded. Investment increased and organisations began paying much more attention to the sustainability of critical open-source projects.

My concern is that some of those lessons are beginning to fade, and AI could make the consequences of that particularly visible.

AI changes the economics of vulnerability discovery

There is an asymmetry developing. The cost of searching code for potential security weaknesses is falling. The volume of reports can therefore rise significantly. But the other side of the process remains stubbornly human. Experienced engineers still need to understand the code. They need to judge whether the finding matters and decide how it should be fixed without creating another problem somewhere else.

Those people are a scarce resource. This means the question organisations should be asking about AI and cybersecurity isn’t only: “What can AI find?” It should also be: “Who is going to deal with everything it finds?”

For open-source projects, that leads directly to questions about sustainable funding. If businesses depend on a project as part of their critical infrastructure, supporting the health of that project should be viewed as part of resilience, not philanthropy.

Regulation only gets us part of the way

Governments are understandably looking at how regulation can improve cyber resilience. That matters, but regulation cannot maintain software. Europe provides some interesting examples of a different approach. OpenSSL Foundation has received support from Germany’s Sovereign Tech Agency, which invests directly in open digital infrastructure.

That recognises something important: if technology is critical to the functioning of the digital economy, somebody needs to invest in the people maintaining it. I’d like to see more of that conversation in the UK. Cyber resilience isn’t only about telling organisations what standards they should meet. We also need to consider the health of the technology underneath the services we’re trying to protect.

Organisations need to know what they depend on

There is something businesses can do immediately. Understand your open-source dependencies. If a critical vulnerability appeared tomorrow in a project your organisation relies on, could you identify where that software was being used?

Would you know which products and services were affected? Would you know who maintains the project? And would you have any relationship with the community responsible for fixing it? If the answer is no that is a resilience gap.

Organisations don’t necessarily need to contribute code themselves. There are other ways to support projects, including funding, engineering resources and participation in the communities maintaining the technology they depend upon. The important shift is recognising open source as infrastructure rather than free software that simply appears.

We need to talk about the people behind the code

AI will continue getting better at analysing software. That’s exciting, and it has the potential to make technology significantly more secure. But more findings do not automatically produce more security. The benefit comes when we have the expertise and resources to act on what those tools discover. That makes this a human question as much as a technology question.

How do we sustain the communities maintaining critical open-source infrastructure? How should businesses support the projects they depend on? What happens when vulnerability discovery accelerates faster than our ability to respond?

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Cybercrime no longer divides neatly between lone hackers, organised gangs and state-backed operations. These groups exchange tactics and tools, while stolen data gives them an asset that can be sold, used for fraud, held to ransom or weaponised for political damage. 

Geoff White is an award-winning investigative journalist whose reporting has taken him inside global hacking networks, cryptocurrency thefts and modern money-laundering operations.  

A former Technology Correspondent for Channel 4 News, he has also reported for the BBC and The Sunday Times. Geoff co-created and presented the BBC World Service podcast The Lazarus Heist and has written three books on cybercrime and organised crime. Champions Speakers 

In this exclusive interview for the IT Security Guru conducted by the Cyber Security Speakers Agency, Geoff explains how cybercrime became a mature global industry, why segmentation remains critical against ransomware and how criminals are using AI in practice. He also examines why stolen data has become one of their most useful assets. 

What drove the convergence of lone hackers, organised crime gangs and state actors into today’s global cybercrime ecosystem? 

Geoff White: “Hacking has always been a thing with computers. From the earliest days, there were people who hacked, which originally didn’t necessarily mean criminal behaviour. 

“Hacking something together is an engineering term. If all you’ve got is some gaffer tape and string, you make the engine work. That was the principle behind hacking in the early days. 

“The apple in the Garden of Eden was money. As soon as websites such as eBay and Amazon started getting set up, credit cards began flooding onto the web. That’s where organised crime gangs started to become interested in the technology. 

“What’s happened since has been an evolution. You started to see organised crime gangs become interested in cyber and hacking. Governments also became interested because getting hold of secrets and manipulating other nations is very useful. 

“You also had lone hackers, what they call hacktivists, the classic kid in a hoodie in a bedroom somewhere. 

“Over time, these movements have moved together and learned from each other. Governments realised that the tactics used by bedroom hackers and activists could be used effectively to push other nations around. 

“Organised crime gangs have sometimes obtained incredibly powerful cyber tools from government hackers. 

“We’re starting to see all these different types of groups coming together. If you want to know why cyber has risen up the agenda, that’s the real explanation.” 

Ransomware now operates like a mature industry. Why do major organisations remain vulnerable, and what defence matters most once attackers get inside?

Geoff White: “The thing to realise about ransomware is that this is a very mature industry, and it is an industry. There are hundreds of people working in it. 

“It’s been through its start-up phase, seed-funding phase and venture-capital phase. It is now a fully fledged industry. 

“At the last count, I found 62 different groups on the dark web who were all carrying out ransomware attacks. They’re extremely strategic. 

“They will say: “Today, we are going to target the transport sector.” They will find companies in that sector and work out which ones are vulnerable, which are most valuable and which are juicy targets. 

“The next day, they might decide to target pharmaceuticals. They are very strategic in how they work and will target those organisations until they find a way in. 

“Unfortunately, the likelihood is that a ransomware gang will get inside your organisation. The only thing you can do to prevent the damage becoming much worse is segmentation. 

“Make sure that if attackers get into one part of your organisation, they can’t access everything. If they break into one department, they shouldn’t be able to move into other departments. 

“Segmentation, breaking things apart and introducing barriers for attackers, is your best defence.” 

How are cybercriminals using AI in practice, and is the threat currently outpacing cyber defence? 

Geoff White: “Like all industries, the cybercrime industry is looking very hard at artificial intelligence. Our working practices are gradually being revolutionised by AI, and the cybercrime space is no exception. 

“However, there’s some good news. 

“If you look at how cybercriminals are using AI in practice, rather than theoreticals, hypotheticals or unverified services being offered on the dark web, it’s the same stuff we’re using it for. 

“They’re using it to improve their emails, audit their code and conduct reconnaissance on targets they might want to hit. That’s not reinventing the wheel. 

“I would contrast that with what’s happening on the defensive side of cyber. AI has always been used in cyber defence. We used to call it machine learning. 

“The cyber-defence industry is using AI at scale and pace. I think we’re in a good place. 

“If we can double down on those AI wins in cyber defence now, we can hopefully stave off the day when cybercriminals start using AI at scale as well.” 

What makes stolen data more useful to cybercriminals and nation states than assets such as cash or cryptocurrency? 

Geoff White: “Cybercriminals have realised that the one thing organisations possess that is easy to obtain and use is data. 

“I can get hold of credit cards as a crook, but then I’ve got to wash the credit card money. I can steal Bitcoin, but then I’ve got to put the Bitcoin somewhere. 

“If I steal data, I’ve got an instant win. I can go on the dark web and sell it. If it’s customer data, I can contact people and send them phishing emails. 

“I can also contact the organisation and say: “I’ve got a bunch of your data. Pay me and I won’t leak it.” 

“There are many different ways data can be used. This isn’t limited to criminals. Nation states have become involved as well. 

“We’ve seen massive data leaks and government hackers breaking into organisations. One famous example was the Democratic Party during the 2016 US presidential election. Incredibly sensitive data was stolen and then weaponised to cause damage. 

“Data has become the new currency for cybercrime gangs in the same way it became the new currency for organisations.” 

 When audiences hear the stories behind your investigations, what do you want them to understand about cybercrime and how to confront it? 

Geoff White: “When I give talks, I’m lucky as a journalist because I have these amazing stories. 

“Regardless of how technical this becomes or how much financial crime might appear to concern spreadsheets, it’s always about people. 

“There’s always a set of characters behind it who are interesting, sometimes crazy and sometimes extremely quirky. 

“I look at the people and their motivations. Then we examine how they work and the lessons organisations need to learn to fight them. 

“I hope people leave my talks with a thumping good story and some valuable, applicable lessons that they can start putting in place to stop the bad guys winning.” 

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The 25th July 2026 marks one year since the Online Safety Act’s landmark child safety duties came into force, making it a natural moment to assess what’s changed, what’s worked and what challenges remain. Although the Act itself received Royal Assent in October 2023, its requirements were introduced in phases, with 25th July 2025 being the date many of the most visible obligations on platforms took effect.

The child safety duties require platforms likely to be accessed by children to introduce stronger protections, including effective age assurance, child risk assessments and measures to reduce exposure to harmful content. 

One year on, has the Online Safety Act fundamentally changed the internet for UK users, or has it simply shifted the challenges elsewhere? We spoke to cybersecurity experts for a short series of reports to find out more.  

Today, we’re examining the unintended consequences of the Act… 

Professor George Loukas, Head of Centre for Sustainable Cyber Security, University of Greenwich, said: “Ofcom has moved from consultation to enforcement. Naturally, the larger adult sector platforms have been the most visible early targets, and there have been lots of discussions on whether that led to a shift to more VPN usage as well as to non-compliant adult websites. These were all predictable though.”

Uptick in VPN Usage 

For many, the enforcement date signalled a natural (if not predictable) shift towards VPN usage to get around age verification tests. The evidence backs up this hypothesis: Proton VPN’s 2025 end of year report revealed that one of the biggest spikes in VPN sign-ups globally was seen in the UK from the 25th July. 

Konstantin Levinzon, co-founder of Planet VPN, noted that the real issue is people seeking out ‘free’ or not reputable VPNs, posing a significant security risk: “The biggest unintended consequence has been pushing people towards less secure tools, not more careful online behaviour. Age verification requirements have driven a significant increase in VPN adoption, but many users don’t seek out reputable providers – they simply download the first free VPN they find. Those services are often the ones leaking DNS requests, harvesting telemetry or relying on weak security practices, creating a worse privacy outcome than the legislation was designed to prevent.”

Sanjeev Malhotra, chief information security officer at TSG, emphasised the security risk: “People engaging with unvetted VPNs are potentially opening themselves up to serious risks, including malware infections, phishing attempts and personal data harvesting. At the end of the day, it’s still going through a server somewhere, and most people don’t stop to think about who’s operating it, where that data is going or what safeguards are actually in place. In some cases, people may be trading one privacy concern for another without realising it.”

A Lack of Measurable Outcomes? 

But is the ban on children accessing adult sites actually working? Some experts argue that there’s no hard evidence to back it up.

Elle Todd, Partner and Co-chair of the Entertainment & Media Industry Group at Reed Smith LLP, said:  “Ofcom’s recent age assurance report found that the proportion of children encountering harmful content online has not substantially improved despite widespread implementation efforts. The uncomfortable truth is that, based on this report, significant investment in compliance and technologies has not yet translated into measurable improvements in safety outcomes.”

Brian Higgins, Security Specialist at Comparitech, noted that, despite some non-compliance fines being handed out, there are still notable enforcement gaps: “Stats from Ofcom summarising their activities during the first twelve months of the Online Safety Act include the launch of 30 investigations, and fines for statutory violations in the region of £4 million GBP. Unfortunately they have also identified ‘enforcement gaps’ where AI and algorithmic content are concerned.”

“This item, in particular, could be a precursor to more widespread enforcement action in the future but a brief investigation into the facts reveals that their twelve-month fine collection figure only stands at £55,000. Couple that with their fairly embarrassing skirmish with the American platform 4chan, where their interjurisdictional service of a £520,000 financial penalty notice was rather infamous met with a picture of a hamster and a heavy dose of internet ridicule and it becomes rather obvious that they aren’t performing particularly well.”

Examining Data Storage and Verification System Security

Boris Cipot, principal security engineer, Black Duck, argues that we should be looking beyond whether checks are working and to whether the software behind the systems doing those checks is actually secure: “For many organisations, the focus has been on whether age checks are working. But an equally important question is whether the software behind those systems is secure and properly maintained. If a vulnerability, misconfiguration or compromised third-party component allows age checks to be bypassed, then this is not just a cybersecurity problem anymore but can quickly become a regulatory one as well.”

Sarah Bone, Co-Founder of YEO Messaging, notes the growing number of specialist identity providers: “The biggest unintended consequence has been a shift in where trust actually sits. Before the Online Safety Act, platforms largely carried the responsibility for verifying users themselves. Now we’ve got a growing ecosystem of specialist identity providers, each holding highly sensitive personal information. That’s strengthened online safety, but it’s also concentrated trust into fewer organisations, which makes them increasingly attractive targets for attackers.”

So what should age verification providers be doing?

Martin Wegrostek, Cyber Security Portfolio Manager at cybersecurity specialist OryxAlign, said: “Businesses should work on the assumption that breaches are a matter of when, not if. The question is whether providers have built their services with security and privacy by design. That means collecting the minimum amount of information needed to verify age, encrypting data both in transit and at rest, enforcing strong access controls, continuously monitoring for suspicious activity and having a well-rehearsed incident response plan. Organisations relying on third-party age-assurance services should also carry out regular security assessments and review the resilience of their supply chain, rather than assuming a compliant provider is automatically a secure one.”

On Trust and Risk

The conversation should also focus on human risk, said Tim Ward, CEO and co-founder, Redflags: “Content moderators, trust and safety teams, and customer support staff at in-scope platforms are, for the first time, routinely processing government ID documents, facial scans, and other highly sensitive data belonging to minors as part of their everyday work. That’s a substantial new category of human risk, from simple mishandling to targeted social engineering aimed at staff with access to this data, and it’s had almost no public discussion compared to the technical side of compliance.”

“Organisations that have spent the past year focused on the verification system itself should be asking whether the humans downstream of it have had the same level of scrutiny and support,” Ward noted. 

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