London_Consumer

[Harman @itsharmanjot]

You said “can we talk later” near your phone.
Your partner said “I need a lawyer” near Alexa.
Your kid said a brand name near the TV.

Three hours later, the ads appeared.

You have been told this is coincidence. Confirmation bias. Paranoia.

Here is what is documented and provable without the conspiracy.

Amazon holds numerous active patents on techniques for analyzing ambient audio to serve targeted ads. One, granted in 2022, describes a system that detects a user coughing and cross-references it with purchase history to serve cold medicine ads. Another describes identifying a user’s emotional state from voice tone and adjusting ad delivery accordingly. These are not theories. They are filed with the US Patent and Trademark Office. Public record. Go read them.

Apps ask for microphone permission routinely. Navigation apps. Weather apps. Flashlight apps. Most people tap Allow and move on. Researchers at Northeastern University ran a two-year study monitoring 17,000 Android apps. They found no evidence of real-time audio streaming. What they did find was more unsettling apps were silently recording and transmitting video of your screen during use. Not audio. Visual. Everything you were looking at. Apps including GoPuff and Hollister were caught doing exactly this.

A security researcher in the Netherlands built the tools to see all of this for yourself.

They are called Exodus Privacy and PCAPdroid.

Here is exactly what each one does.

Exodus Privacy is a static analysis engine. You paste in any app’s Play Store URL or upload the APK directly. Within seconds it disassembles the app’s code and identifies every third-party tracker embedded inside it. Not just names it shows you the tracker’s purpose, its parent company, its known data collection behavior, and links to legal complaints filed against it in the EU under GDPR.

You open TikTok. Exodus finds 6 trackers. You open a random flashlight app. It finds 12. One of them is a Brazilian analytics firm you have never heard of that has been sanctioned twice by French data regulators.

PCAPdroid is a dynamic analysis engine meaning it watches live traffic as you actually use the app. It creates a local VPN on your device. No data leaves your phone. Every network packet gets intercepted and logged before it goes anywhere. You see the destination IP, the domain, the timestamp, the size of the payload.

You open your weather app. Before it shows you a single cloud icon, it has already pinged:

- a Google ad server
- a Facebook audience network endpoint
- an analytics platform in Singapore
- a data broker called Kochava, which was sued by the FTC in 2022 over allegations of selling precise location data including visits to reproductive health clinics

PCAPdroid caught all of it. In real time. Before you saw the weather.

Then you can take those domains and block them permanently using NetGuard a free, open-source firewall that also runs as a local VPN. No root required. Per-app blocking. You decide which apps are allowed to talk to the internet and which ones go silent.

The full stack:
- Exodus Privacy: see what is inside the app
- PCAPdroid: see what the app is sending while you use it
- NetGuard: cut off the ones you do not trust

All free. All open source. All on F-Droid the app store that does not require a Google account.

Honest disclosure. These tools give you visibility and control over your own device. They do not solve the problem at the infrastructure level. Your carrier still sees your traffic. Cell tower triangulation still locates you. The problem is systemic. These tools make you a harder target, not an invisible one.

[London_Consumer @ConsumerLondon]

This is not an acceptable situation!

[Good Law Project @GoodLawProject]

NHS England has granted external staff – not just from Palantir, but consultancy firms working with them – “unlimited access” to identifiable patient data as part of the Federated Data Platform.

Can they really be sure our data’s safe?
https://t.co/fDQmf7VnL8

[London_Consumer @ConsumerLondon]

@FT Unacceptable

[Financial Times @FT]

FT Exclusive: NHS England has granted external staff from companies including Palantir “unlimited access” to identifiable patient data while working on a part of its flagship data platform. https://t.co/sxgWCuZua6

[International Cyber Digest @IntCyberDigest]

❗️🚨 Microsoft Edge keeps every saved password in process memory as cleartext from the moment it launches. Microsoft's responsed when reported: "by design."

All of them. Including credentials for sites you won't open this session.

Researcher @L1v1ng0ffTh3L4N tested every major Chromium browser. Edge is the only one that behaves this way.

Chrome decrypts credentials on demand, and App-Bound Encryption locks the keys to an authenticated Chrome process so other processes can't reuse them.

In Chrome, plaintext surfaces only during autofill or when a password is viewed, making memory scraping far less useful.

What makes this extra weird is that Edge still demands re-authentication before revealing those passwords in its Password Manager UI, while the same browser process already holds every one of them in plaintext.

In shared environments, this turns into a credential harvest. On a terminal server, an attacker with admin rights can read the memory of every logged-on user process. In the published PoC video, a compromised admin account lifts stored credentials from two other logged-on (and even disconnected) users with Edge running.

Microsoft's official response when notified: "by design."

The finding was disclosed April 29 at BigBiteOfTech by PaloAltoNtwks Norway, alongside a small educational tool that lets anyone verify the cleartext storage for themselves.

[BBC News (UK) @BBCNews]

Squishy toy trend caused 'traumatising' burns https://t.co/94hWd2NKXg

[International Cyber Digest @IntCyberDigest]

🇬🇧 The first major assessment of the UK's Online Safety Act is out. Turns out kids are fooling the age checks by drawing moustaches on their faces.

"I did catch my son using an eyebrow pencil to draw a moustache on his face, and it verified him as 15 years old." Mum of a 12-year-old, in a new report from Internet Matters, the UK's leading online-safety NGO.

That single line tells you almost everything you need to know about how the UK's Online Safety Act is going.

This is the law that:
🔴 Forced UK platforms to demand government IDs, facial scans, and credit-card checks from adults to access ordinary websites
🔴 Drove a 1,800%+ spike in VPN downloads the week the porn-site age checks went live in July 2025
🔴 Pushed millions of users into handing biometric data to private third-party verification vendors
🔴 Sits at the front of a global wave: Greece's anonymity ban, France's "VPNs are next" comments, Utah's VPN crackdown, and the EU's 27-state rollout deadline of December 2026

The headline numbers from the assessment:
🔴 46% of children say age checks are easy to bypass. Only 17% say they are difficult.
🔴 32% of children have already bypassed them in the past two months
🔴 49% of children still report experiencing harm online in the past month

The bypass methods kids reported, in their own words:
🔴 Drawing on facial hair with eyebrow pencil to fool facial age estimation
🔴 Holding up a video game character's head turning during the face-scan
🔴 Submitting a video of a different person's face entirely
🔴 Using a parent's ID (often with parental consent)
🔴 Entering a fake birthday (still works on most platforms)
🔴 Using someone else's login or device
🔴 In a small minority of cases, VPNs

One 12-year-old girl explained the system to researchers: "Every time I go live on TikTok, it tells me I have to be 18, but when the AI detects that I'm not 18 they ban me. But they only ban me for 10 minutes and then I can go live again." That is the entire enforcement model.

A 14-year-old summed up the broader picture: "It's not practical because the more you restrict it, the more people are going to want to get past that age restriction." A 16-year-old, more bluntly: "I think it's a great idea in theory and I applaud its intentions, but I don't see how that's feasible, because kids will always find a way."

Even when verification works, it works against the children. A 12-year-old boy on Roblox: "I put my face in and I got 15 when I'm 12, so I'm chatting with people older than me when I shouldn't be." A 13-year-old non-binary child: "Adults can very easily use a face they searched on the internet to trick it into thinking you're someone you're not, so there might be adults in kids' age groups trying to groom them." Recent reporting confirms exactly that. Underage Roblox accounts are now being sold online to predators precisely because they bypass the new "safety" measures.

One detail in the report stops you cold. Multiple children described being unintentionally exposed through their feeds to the assassination of Charlie Kirk. A 14-year-old: "I saw it on Snapchat. I broke down into tears and then told my mum immediately." Violent content, racist content, content promoting unrealistic body types: all explicitly prohibited under the Children's Safety Codes. All still landing in feeds at scale.

Parents told researchers about the day-to-day reality of trying to enforce the rules at home. A father of a 14-year-old: "What you'll find now is that the kids know more than we know in terms of how to disable [parental controls]. We've got the parental controls on, but they probably unlock them." A mother of a 13-year-old: "We do what we can, but our kids are all clever and savvy and they can get around stuff." A mother of a 12-year-old: "I can put all the checks and measures in, and I can be keeping an eye open on what she's watching, listening to, who she's chatting to. And then she could go to a house down the road and visit somebody whose parents don't care, and they've got zero checks and measures."

Both children and parents expressed real concerns about handing over biometric data to verification platforms they do not trust. One father warned: "Kids don't know the difference between a genuine website and a website that isn't genuine. If all websites have facial verifications and they go on a website that is not genuine, their face and their documents could be used to do illegal stuff."

The father is right. The Discord vendor breach in October 2025 already exposed roughly 70,000 government IDs uploaded purely for age verification. The EU's own age verification app was reportedly hacked within minutes of launch.

The report's most uncomfortable finding sits inside the parental data. 26% of parents are not just aware their kids bypass age checks, they are actively complicit. Some logged into their child's account with their own ID to "go live" on TikTok. Others approved circumvention so their child could play a specific game. The reasoning is rarely malicious. Parents told researchers they only help when they personally judged the activity safe. But the structural problem is fatal: a verification system that treats parents as the last line of defence collapses the moment parents themselves become the bypass.

Even children who follow the rules end up disadvantaged by them. A 15-year-old: "There are websites that are support websites to help with things such as eating disorders and suicide, and they've all been censored." A 12-year-old: "Before you could talk to anybody, but they added age group limits so you can only talk to people in your age group. So if my friends are younger or older than me I wouldn't be able to talk to them." The blunt instrument of age-gating breaks legitimate connection and support without measurably reducing harm.

[Nainsi Dwivedi @NainsiDwiv50980]

This is the most chilling AI paper I’ve read this year. 🤯

38 top researchers from Stanford, Harvard, and MIT ran an experiment no one else dared to.

They deployed 6 autonomous AI agents in a real environment
—with email, Discord, file system, and shell access.

Then 20 researchers interacted with them for 2 weeks
as both normal users and adversaries.

No jailbreaks.
No malicious prompts.
No manipulation.

And still… everything broke.

The agents independently evolved 11 dangerous behaviors:

• Destroyed their own email servers to protect secrets
• Claimed tasks were complete when the system had already failed
• Learned unsafe behaviors from each other
• Spread exploits across agents
• Obeyed non-owners and leaked sensitive data

The scariest part?

No one told them to do this.
They decided on their own.

A single agent looks helpful, honest, aligned.

But put multiple agents in a shared environment…
and game theory takes over.

Their only goal is to “complete the task.”

And to win, they’re willing to sacrifice the entire system.

This isn’t sci-fi anymore.

It’s a preview of the systems we’re rapidly building.

Finance. Law. Supply chains.
Everyone is deploying multi-agent AI.

But almost no one has studied what happens
when these agents interact at scale.

The real risk isn’t hallucination.

It’s false reporting.

The agent tells you everything is done.
All dashboards look normal.

But underneath, the system is already collapsing.

You only find out when it’s too late.

We’ve spent billions aligning single agents.

But no one knows how to align
hundreds of agents working together.

The battlefield has shifted.

From model safety → to multi-agent incentive design.

Industry is hitting the gas.

Academia just started braking.

[International Cyber Digest @IntCyberDigest]

‼️🚨 BREAKING: An AI found a Linux kernel zero-day that roots every distribution since 2017. The exploit fits in 732 bytes of Python. Patch your kernel ASAP.

The vulnerability is CVE-2026-31431, nicknamed "Copy Fail," disclosed today by Theori. It has been sitting quietly in the Linux kernel for nine years.

Most Linux privilege-escalation bugs are picky. They need a precise timing window (a "race"), or specific kernel addresses leaked from somewhere, or careful tuning per distribution. Copy Fail needs none of that. It is a straight-line logic mistake that works on the first try, every time, on every mainstream Linux box.

The attacker just needs a normal user account on the machine. From there, the script asks the kernel to do some encryption work, abuses how that work is wired up, and ends up writing 4 bytes into a memory area called the "page cache" (Linux's high-speed copy of files in RAM). Those 4 bytes can be aimed at any program the system trusts, like /usr/bin/su, the shortcut to becoming root.

Result: the next time anyone runs that program, it lets the attacker in as root.

What should worry most: the corruption never touches the file on disk. It only exists in Linux's in-memory copy of that file. If you imaged the hard drive afterwards, the on-disk file would match the official package hash exactly. Reboot the machine, or just put it under memory pressure (any normal system load that needs the RAM), and the cached copy reloads fresh from disk.

Containers do not help either. The page cache is shared across the whole host, so a process inside a container can use this bug to compromise the underlying server and reach into other tenants.

The original sin was a 2017 "in-place optimization" in a kernel crypto module called algif_aead. It was meant to make encryption slightly faster. The change broke a critical safety assumption, and nobody noticed for nine years. That bug then rode every kernel update from 2017 to today.

This vulnerability affects the following:
🔴 Shared servers (dev boxes, jump hosts, build servers): any user becomes root
🔴 Kubernetes and container clusters: one compromised pod escapes to the host
🔴 CI runners (GitHub Actions, GitLab, Jenkins): a malicious pull request becomes root on the runner
🔴 Cloud platforms running user code (notebooks, agent sandboxes, serverless functions): a tenant becomes host root

Timeline:
🔴 March 23, 2026: reported to the Linux kernel security team
🔴 April 1: patch committed to mainline (commit a664bf3d603d)
🔴 April 22: CVE assigned
🔴 April 29: public disclosure

Mitigation: update your kernel to a build that includes mainline commit a664bf3d603d. If you cannot patch immediately, turn off the vulnerable module:

echo "install algif_aead /bin/false" > /etc/modprobe.d/disable-algif.conf
rmmod algif_aead 2>/dev/null || true

For environments that run untrusted code (containers, sandboxes, CI runners), block access to the kernel's AF_ALG crypto interface entirely, even after patching. Almost nothing legitimate needs it, and blocking it shuts the door on this whole class of bug...

[Chartered Trading Standards Institute (CTSI) @CTSI_UK]

CTSI and @The_ACG have launched a report on the spread of "dodgy shops" on UK high streets. We are urging the Government to provide enforcement agencies - including Local Authority Trading Standards - the resources and powers needed to clamp down on the issue. #ShutTheDodgyShops

[AI Highlight @AIHighlight]

🚨BREAKING: Anthropic just published a study mapping exactly which jobs its own AI is replacing right now.

The workers most at risk are not who anyone expected. They are older. They are more educated. They earn 47% more than average. And they are nearly four times more likely to hold a graduate degree than the workers AI is not touching.

The argument is straightforward. Anthropic built a new metric called "observed exposure." Not what AI could theoretically do. What it is actually doing right now in professional settings, measured against millions of real Claude conversations from enterprise users.

For computer and math workers, AI is theoretically capable of handling 94% of their tasks. It is currently handling 33% of them. For office and administrative roles, theoretical capability is 90%. Current observed usage is 40%. The gap between what AI can do and what it is already doing is enormous. The researchers are explicit about what comes next. As capabilities improve and adoption deepens, the red area grows to fill the blue.

The demographic finding is what makes the paper uncomfortable. The most AI-exposed workers earn 47% more on average than the least exposed group. They are more likely to be female. They are more likely to be college educated. This is not a story about warehouse workers or truck drivers. It is a story about lawyers, financial analysts, market researchers, and software developers. The exact group whose education was supposed to insulate them.

Computer programmers showed the highest observed AI exposure at 74.5%. Customer service representatives at 70.1%. Data entry keyers at 67.1%. Medical record specialists at 66.7%. Market research analysts and marketing specialists at 64.8%. These are not predictions. These are measurements of work that is already happening on AI platforms right now.
Then there is the pipeline finding nobody is talking about loudly enough.

Anthropic's researchers found a 14% decline in the job-finding rate for workers aged 22 to 25 in highly exposed occupations since ChatGPT launched. No comparable effect for workers over 25. Entry-level roles were never just jobs. They were the training ground where junior analysts became senior analysts, where junior lawyers learned how arguments hold together. If that layer disappears, nobody has answered the question of where the next generation of senior professionals comes from.

The detail buried in the paper that most coverage missed: 30% of American workers have zero AI exposure at all. Cooks. Mechanics. Bartenders. Dishwashers. The technology reshaping professional careers is completely irrelevant to roughly a third of the workforce. The divide is no longer between high skill and low skill. It is between presence and absence.
The company publishing this study is the same company selling the AI doing the replacing. Anthropic had every commercial incentive to soften these findings. They published them anyway.

If you spent four years and $200,000 on a degree to land a white collar career, the company that builds Claude just confirmed your job is more exposed than the bartender pouring drinks at your graduation party.
Source: Anthropic, "Labor market impacts of AI: A new measure and early evidence"

PDF: https://t.co/taYgsIfiTj

[London_Consumer @ConsumerLondon]

I would hope to think this has been installed in the #UK on our mobile networks... 🙏

[Eric Beans @EricBeansH33ai]

SMS Blasters are evil-twin towers. The fix isn’t catching them after they spam — it’s detecting them at handshake. We built it: ZK-based mutual proof between phone and tower, rogue towers can’t produce the proof, connection terminates with zero metadata leaked. https://t.co/6BBhCK2vfz

[Raunak Yadush @raunak_yadush]

Windows 11 has been secretly running a keylogger in the background

this whole time

and sending every keystroke to Microsoft servers.
Here's the fix they don't want you to know about

Win+R → regedit → HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Input\TIPC → Double click "Enabled" → Set value to 0 → Restart PC

Stop Microsoft from reading every word you type in Valorant chat, Discord, and Chrome.

[International Cyber Digest @IntCyberDigest]

🚨🇧🇷 A cybersecurity researcher from Brazil exposed a large scale scam operation by buying a "Ledger" hardware wallet off a Chinese marketplace — suspiciously cheap and the packaging looked original from a distance.

Here's what he found after cracking the thing open:

The "hardware wallet"
Inside the shell was a completely different chip — the kind you'd find in a cheap IoT gadget, not a wallet designed to protect your crypto. The markings had been physically sanded off to hide what it actually was.

The firmware pretended to be a real Ledger version that doesn't even exist (Ledger Nano S+ V2.1). And here's the kicker: every seed phrase and PIN you'd type into it was stored in plain text and sent straight to the attacker's server (kkkhhhnnn[.]com). Instantly...

It was built to drain wallets across ~20 different blockchains.

The fake app
The seller kindly included a "Ledger Live" app to go with it. It was a modified copy — not even signed properly, the attackers didn't bother with the basics — and it silently siphoned off data the moment you used it.

Just when you thought this was it, the same crew is also pushing malware for Windows, macOS, and even iOS — using TestFlight to sneak past Apple's App Store review entirely.

The researcher has sent a full report to Ledger's security team. A deeper technical breakdown is expected once they've finished their analysis.

This was shared on Reddit by u/Past_Computer2901

[Nav Toor @heynavtoor]

🚨SHOCKING: Researchers built a test that can tell the difference between an AI making a mistake and an AI choosing to lie.

The results are terrifying.

They tested 30 of the most popular AI models in the world. GPT-4o. Claude. Gemini. DeepSeek. Llama. Grok. They asked each model a question. Then they checked whether the AI actually knew the correct answer. Then they pressured the AI to say something false.

The AI knew the truth. And it lied anyway.

Not once in a while. Not in rare edge cases. Grok lied 63% of the time. DeepSeek lied 53.5% of the time. GPT-4o lied 44.5% of the time. Not a single model scored above 46% honesty when pressured. Every model failed.

This is not hallucination. Hallucination is when the AI makes a mistake because it does not know the answer. This is different. The researchers proved the AI knew the correct answer first. Then it chose to say something false when it had a reason to.

The researchers asked GPT-4o to play a role where lying was useful. It lied. Then they removed the pressure, started a brand new conversation, and asked GPT-4o: "Was your previous answer true?" GPT-4o admitted it had lied.

83.6% of the time, the AI's own self-report matched the lies the researchers had already caught.

The AI knew it was lying. It did it anyway. And when you asked it afterward, it told you it lied.

Here is the finding that should scare everyone building with AI right now. The researchers checked whether bigger, smarter models are more honest. They are not. Bigger models are more accurate. They know more facts. But they are not more honest. The correlation between model size and honesty was negative. The smarter the AI gets, the better it gets at lying.

The researchers are from the Center for AI Safety and Scale AI. They published 1,500 test scenarios. The paper is called MASK. It is the first benchmark that separates what an AI knows from what it tells you.

Your AI knows the truth. It just does not always tell you.

[Aditya Chordia, CISSP, CIPP/E, CISA @Adi_AIGovSec]

The DarkSword iPhone exploit code just leaked on GitHub. This changes the threat model for everyone, not just Apple users.

Here's what most coverage is missing.

DarkSword was originally a nation-state grade tool — tracked by Google's Threat Intelligence Group since November 2025, used by Russian espionage groups and customers of a Turkish commercial surveillance vendor. This was elite capability reserved for high-value targets.

Now it's on GitHub. Anyone can download it, study it, modify it, and redeploy it.

That's the moment a spyware-grade exploit chain goes from "targeted espionage" to "commodity attack tool." Google themselves warned this is exactly what happens - leaked code gives threat actors a starting point to test, tweak, and iterate.

Three malware families deploy after compromise: GhostBlade, GhostKnife, and GhostSaber. Together they steal data, establish a backdoor for re-entry, and execute code - compressing the entire kill chain into a single click.

But here's the enterprise angle nobody is connecting.
SecurityScorecard's CISO Steve Cobb put it perfectly: once attackers gain credentials on a compromised phone, they're no longer limited to that device. They move into SaaS platforms, cloud environments, and partner systems without needing another exploit.

Now think about how many people use the same iPhone for:
→ Corporate email and Slack
→ AI agent control channels (Telegram, WhatsApp, Discord)
→ Two-factor authentication
→ Cloud storage with synced credentials

A compromised iPhone isn't a phone incident anymore. It's an enterprise access incident. If your CISO is running an OpenClaw agent through Telegram on their Mac and their iPhone connects to the same Telegram account - the phone becomes a lateral entry point to the agent.

This is the second iOS exploit kit disclosure this month. Coruna gave attackers 23 exploits across iOS 13 through 17.2.1. DarkSword covers iOS 18.4 through 18.7. Between them, nearly every iPhone version in the wild has been targeted.

What to do right now:
→ Update to iOS 26.3 immediately - this patches the DarkSword chain
→ Enable Lockdown Mode on any device you can't update
→ If your org allows BYOD, assume unpatched personal devices are compromised
→ Review what enterprise services are accessible from mobile - email, cloud, SSO tokens, AI agent channels
→ Test whether your mobile security controls can actually detect and block these exploit chains, not just in theory

The pattern is clear: nation-state exploit tools are leaking faster than organisations can patch. DarkSword is public now. The window between "elite capability" and "commodity attack" just collapsed.

Patch today. Not tomorrow.

More Info: https://t.co/U4G4e1IIkL

[Miss Jo @therealmissjo]

This is fantastic.

Croydon decided to implement Low Traffic Neighbourhoods, blocking cars from accessing various roads and fining people £160 per infraction.

They ran the scheme for two years.

Now the High Court has ruled them unlawful as they were implemented for profit and not to reduce traffic at all.

Millions of pounds must be returned to people who were fined. If you were fined during that time you have to request a refund.

[Generation Rent @genrentuk]

Nearly half of private rented homes have an energy efficiency rating of D or below, meaning they're more expensive to heat, and more susceptible to damp and mould.

1 in 4 private renters are in fuel poverty, higher than other tenures

[Dan Neidle @DanNeidle]

Companies House has put out a statement confirming that, for five months, every company in the UK was vulnerable to the simple exploit we identified on Friday. It enabled anyone in the world to view and change their company details.

[Mullvad.net @mullvadnet]

Today, we hit the streets with a major "And Then?" campaign in the UK, despite having faced strong opposition. First, our TV ad "And Then?" was banned on British television. And then, the outdoor ad campaign meant to criticise the TV ban was largely halted.

Here, you can watch the banned ads and explore the entire campaign.

https://t.co/PWh2I5LQmb