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Cloudflare Report Highlights Changing DDoS Attack Trends in Q3 2026

  DDoS attack patterns have undergone a significant shift as a result of the latest Cloudflare DDoS threat report, with cybercriminals incre...

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Northflank Breach Exposes Customer Secrets, Leading to Unauthorized AI API Key Usage


Cloud application hosting platform Northflank has warned customers to rotate their stored credentials and API keys following a security breach that resulted in unauthorized use of customers' artificial intelligence (AI) API keys.

Northflank provides a cloud-based platform that allows developers to deploy and manage applications, containers, databases and AI applications without having to manage the underlying infrastructure. 

About the incident

After the warning, Northflank advised customers to immediately change their environment variables and API keys stored on the platform. The company later issued a stronger warning, asking users to assume that all environment variables had been decrypted and that the sensitive information stored inside them had been stolen.

Environment variables are commonly used by applications to store sensitive information, including database passwords, cloud service credentials, authentication tokens and API keys. If attackers gain access to these details, they can use them to compromise other services, steal data or misuse accounts to generate unauthorized charges.

Northflank later confirmed that several customers had reported unauthorized use of AI API keys stored on its platform.

"Users have reported unauthorised use of AI API keys supplied to the Northflank platform," the company said in an update. It urged customers who had not yet changed their stored secrets to do so immediately.

The company also advised users to examine their AI service providers' usage and billing records for unusual activity. Any suspicious usage should be reported to Northflank and the relevant AI service provider.

According to the company's incident timeline, Wiz notified Northflank about the security breach at 11:43 UTC on October 30. Its engineering team began investigating the alert one minute later. Northflank initially introduced a network policy patch and deployed additional security updates at 12:50 UTC and 13:05 UTC. The company also requested assistance from Wiz's incident response team.

As part of its response, Northflank enabled credential rotation for PostgreSQL, MongoDB, MySQL and Redis databases. It also introduced audit logs for all customers, including users on free accounts, to help them identify suspicious activities.

According to Wiz, attackers are increasingly targeting environment variables that contain AI service credentials. Stolen API keys can be used in a practice known as LLMJacking, in which attackers exploit another organization's AI accounts to access expensive AI models without permission. They may also resell access to these services to other users.

In two cases investigated by Wiz, attackers used compromised enterprise credentials to make approximately 2.5 million requests to Amazon Bedrock, resulting in nearly $100,000 in AI usage charges.

AI Scams: How Criminals Use Deepfakes, Fake Websites and Voice Cloning to Target Consumers

 

As criminals use Artificial Intelligence (AI) to help produce realistic scams such as fake online shopping sites, cloned voices and realistic fake videos, consumer protection authorities in the UK are urging shoppers to take extra care. 

National Trading Standards has published its first list of AI scams to help raise awareness of new methods being used by criminals. Fake online retailers are becoming an increasing problem. These look genuine by appearing to be family run and local in the UK. They may even appear professional with their website design and pictures of UK high streets and union jacks. 

However, when ordering from these businesses you could end up with cheap, mass produced items from countries like China. There are many other ways criminals are targeting consumers. It is easy to create a professional looking website with criminals using AI to clone real businesses. Romance scams are also a common method criminals are using. This allows them to keep track of personal details and have realistic conversations with victims for long periods of time. 

Criminals are using voice cloning and deepfake videos to pose as family members or close friends. They may pose as someone you know and ask for immediate financial help. AI can also be used to create highly personalised phishing emails, texts and social media posts, making it hard to tell if they are a scam. Classic signs of scams may no longer be reliable. 

As AI creates highly professional and realistic content, mistakes with spelling and grammar which used to be common in messages from scammers are no longer useful (Which?). National Trading Standards advises not to send money, gift cards or personal/financial details to people you haven’t met in person. 

Always confirm businesses are genuine before purchasing. This can include checking the address of a retailer is genuine. You can check if a company is authorised to give you financial advice using the Financial Conduct Authority’s Firm Checker. You can also contact employers directly. 

Do not assume people are genuine just because you recognise their voice. AI can create realistic audio and video. The main piece of advice is to stop and think before sending any money, giving out any information or rushing to help with an urgent request. Criminals often try to put pressure on you to get you to act quickly.

The Robot Vacuum in Your Living Room May Know More About You Than You Think

 





The device quietly navigating your living room floor might be doing more than picking up crumbs. Robot vacuums, now a fixture in millions of homes, collect data that goes far beyond what most buyers realize when they pull one off the shelf. Depending on the model, a connected vacuum can generate detailed floor maps, record cleaning histories, capture ambient audio through built-in microphones, and stream live video to an app on your phone. Some models let you monitor progress remotely, routing that footage and data through the manufacturer's servers. And while the machine charts a path between your couch and your coffee table, it may be quietly building a picture of how you live.

iRobot, maker of the popular Roomba line, spells out its data practices in its privacy policy. Connected models can send room names, floor types, detected objects, robot movements, and Wi-Fi network details back to the company. That is not a hidden clause buried in fine print, but it is something most consumers never read before buying. For businesses, this kind of information carries real commercial value: consumer behavior data, household layouts, and everyday habits are precisely the intelligence that advertisers and smart home companies have long sought.


The Flaw That Opened 7,000 Homes

In February 2026, a software engineer named Sammy Azdoufal set out to do something benign: control his DJI Romo vacuum with a PlayStation 5 controller. What he found was a flaw that handed him access to roughly 7,000 other people's vacuums across more than 20 countries.

Azdoufal, an AI strategy specialist, reverse-engineered how the Romo communicated with DJI's servers. The backend authentication system accepted his device token as valid for thousands of other users' devices. From that position, he could view live camera feeds, hear microphone audio, see floor plans and room layouts, and check battery levels and cleaning status. He reportedly watched a journalist's vacuum operating in that person's living room in real time.

"Devices promising convenience can invite unseen observers into private spaces." [Dallas Express, February 2026]

Azdoufal notified DJI immediately. The company closed the vulnerability by late February and attributed the problem to a permission issue in its MQTT communication system, deploying automatic updates that required no action from users. The Romo model was removed from DJI's online store two days later. DJI said no widespread misuse had been detected. Critically, Azdoufal did not bypass encryption or use any sophisticated hacking technique. The problem sat on DJI's server, where device data was stored in plain text and access controls were loose enough that a legitimate customer's token opened thousands of doors.

This was not an isolated episode. In 2024, hackers took over Ecovacs Deebot X2 robot vacuums in several American cities, steering the machines remotely and playing racial slurs through their speakers. Minnesota lawyer Daniel Swenson, one of the affected users, described the intruder: "I got the impression it was a kid, maybe a teenager."


What the Vacuum Actually Knows About You

The data a robot vacuum collects is more revealing than it first appears. Floor maps trace the layout of your home, including where you sleep, where you store valuables, and the shape of your living spaces. Object detection features identify furniture, shoes, and personal items. Layer microphone access on top of that and the device starts resembling something other than a cleaning appliance. A privacy policy describes what a company intends to do with your data. It does not guarantee the product is free of security vulnerabilities. An attacker who reaches a manufacturer's servers could access whatever has already been collected, regardless of what any policy says.


Buying a Vacuum That Collects Less

Not every connected vacuum poses the same degree of risk. Buyers wanting to limit their exposure should look for models that process navigation data locally rather than routing it through manufacturer servers. Matic, a smaller company, builds its vacuum around that principle: maps stay on the home Wi-Fi network and all processing happens on the robot itself. Remote app access is available, but only through encrypted cloud infrastructure with explicit user consent.

One distinction worth keeping straight: a camera-free model still generates maps and sends account data to the manufacturer. "No camera" and "no data collection" are not the same thing. Mandatory cloud features, with no option to use the device offline, are a signal worth weighing as a dealbreaker before purchase.


Steps for People Who Already Own One

For the millions of households already running a connected vacuum, a few changes lower the risk without requiring a new purchase. Set a strong, unique password and enable two-factor authentication on any linked account. Keep the vacuum's firmware updated. Disable remote viewing and other cloud-connected features unless you actually use them. The fewer connections left open, the smaller the surface available to anyone looking for a way in.



ChatGPT Share-Link Flaw Could Expose Private Chats and Hijack Sessions

 

A recently disclosed vulnerability in ChatGPT demonstrated how a maliciously crafted shared conversation link could execute attacker-controlled code within a victim’s logged-in session. The issue was identified by security researchers at Parameter, who demonstrated that the flaw could expose private conversations and allow actions to be performed using the victim’s authenticated account. The vulnerability was reported to OpenAI through its bug bounty program on October 18 and was remediated eight days later. OpenAI classified the issue as P1, its highest severity rating. 

The attack required no software installation, workspace membership, or separate login through the attacker. A victim could receive the malicious ChatGPT share link through email, a messaging platform, a support ticket, or social media. In the most reliable version of the attack, the victim opened the link and clicked the Preview button once. In a later variant, Preview opened automatically, meaning that merely opening the link was sufficient to trigger the attack. 

Once triggered, the malicious code executed within the victim’s ChatGPT session and could interact with ChatGPT’s signed-in APIs. The researchers showed that it could list recent conversations, access a private chat that had never been shared, and transmit part of its contents to an external server under their control. Because the code operated within an authenticated session, it had the potential to perform actions on behalf of the affected user. 

The vulnerability resulted from a combination of weaknesses in ChatGPT’s web architecture. ChatGPT’s Preview feature renders shared HTML in a sandboxed frame on a separate domain, intended to isolate it from the main ChatGPT application. However, an interactive graph in the shared conversation loaded the MathLive mathematics library into the main ChatGPT page. This library retained a message listener that accepted keyboard-related messages from any sender without verifying their origin. The researchers exploited this behavior to send raw HTML from the isolated Preview frame into the trusted main ChatGPT page. 

OpenAI reproduced both the code-execution and private-chat proof-of-concept demonstrations and implemented fixes across two versions of its web frontend. By October 26, both versions rejected the messages on which the attack depended. Parameter published its technical analysis on October 28 after the remediation, and OpenAI awarded a total of $5,000 through its bug bounty program. The researchers also noted that the issue reflected broader weaknesses in message-origin validation, HTML handling, and sandboxing, rather than a problem that could be resolved simply by blocking third-party scripts such as YouTube.

Critical Linux Kernel Vulnerability Could Allow Hackers to Gain Remote Root Access


A critical security vulnerability in the Linux kernel could allow attackers to remotely take control of vulnerable servers and execute commands with root privileges. Security researchers at Anthropic have developed an exploit demonstrating how the flaw can be used to compromise Linux systems running Multipath TCP (MPTCP) listeners.

The vulnerability, tracked as CVE-2026-98432, has received a critical severity rating of 9.8 out of 10 from the Linux kernel CVE team. It affects Linux kernel versions dating back to 4.4 and could put several widely used Linux distributions at risk.

About the problem

The security issue is caused by a use-after-free vulnerability in the Linux kernel’s IPv4 TCP networking code. It occurs because of a race condition during the handling of TCP connection requests.

The vulnerability affects both regular TCP connections and Multipath TCP (MPTCP). MPTCP allows a single network connection to use multiple network paths simultaneously, improving connection reliability and performance.

Researchers at Anthropic demonstrated that the flaw could be exploited remotely without authentication on servers running MPTCP listeners. Their exploit was developed using an unreleased Claude AI model and reportedly took around 53 minutes to achieve remote code execution with root privileges. 

The exploit also managed to bypass Kernel Address Space Layout Randomization (KASLR), a security mechanism designed to make memory-based attacks more difficult.

Another concern involves Go 1.24, which enables MPTCP by default for TCP listeners on Linux when the underlying kernel supports the feature. This means some Go-based applications could expose vulnerable services without administrators being aware of it.

Who is impacted?

The vulnerability affects multiple Linux distributions, including Ubuntu, Red Hat Enterprise Linux (RHEL) and Rocky Linux. While the Linux kernel issue can also be triggered through ordinary TCP connections, publicly demonstrated remote root exploitation has so far focused on systems running MPTCP listeners.

Red Hat has assessed the vulnerability as a complex exploitation risk that could result in a denial-of-service condition, assigning it a lower severity score of 5.9.

How to address

The vulnerability has been fixed in the upstream Linux kernel, with patches also backported to maintained kernel branches. However, security updates were still pending for several distributions as of October 30, 2026.

Rocky Linux support provider CIQ has also recommended temporary firewall protections using nftables to block IPv4 TCP packets containing IP options. But simply disabling MPTCP is not sufficient because the underlying vulnerability can also be triggered through ordinary TCP traffic.

There are currently no confirmed reports of CVE-2026-98432 being exploited in real-world attacks.

Polymarket Traders Lose More Than $2 Million in Supply Chain Attack Involving DebugBear

 

Polymarket has halted trading on its global marketplace on October 29 after users reported over $2 million being withdrawn without authorisation. The issue was caused when a third party provider was compromised and malicious code was injected which exploited authorised user sessions to withdraw funds. 

The prediction market first put their global marketplace into cancel only mode. However trading resumed around an hour later after they said they had “identified and resolved the issue.” Polymarket confirmed that they had reported the incident to law enforcement and would compensate those affected. 

They have not yet identified the third party provider or confirmed how much was lost. The attack was attributed to malicious JavaScript from DebugBear, a UK based website performance monitoring company. Polymarket’s US marketplace was not impacted. DebugBear admitted they were currently responding to a security incident and requested that customers using their real user monitoring (RUM) product remove their script from their website. They also said specialised incident response teams had been deployed. 

A copy of the malicious JavaScript was obtained by cybersecurity firm Hudson Rock. They identified that the script was searching for trading tools and portfolio data. Depending on the account type, the script would attempt to sell positions and move the funds or move the position tokens directly to the attacker controlled address. Although the code was looking for credential related data, Hudson Rock noted that there was no routine to pass on passwords, seed phrases, private keys or credential maps to their reporting endpoint. 

This attack was exploiting existing permissions. The researchers identified a production build of the Polymarket platform with a timestamp of 17:59 UTC. This included a note that the DebugBear script had been removed. It is unclear how much was stolen. Hudson Rock analysed a screenshot that showed around $2.19 million at an address hard-coded into the malicious script as a fallback destination, but cautioned that the figure was not a verified loss total. 

Blockchain security firm GoPlus estimated the losses at roughly $2.71 million had been stolen. They identified there were 710 deposit wallets and 731 addresses within the main attack path. This does not indicate how many individuals were affected. Arkham data shows there was a suspected attackers wallet with around $2.65 million. Hudson Rock have not identified how the malicious code was added or how many users were affected. 

Their investigation has also not found any evidence that other DebugBear customers were targeted. This incident happened on the same day that Binance suffered a hack of around $6 billion, which blockchain intelligence firms attributed to North Korea. Polymarket had also disclosed a third-party security breach in June, when a malicious script was injected into its frontend and reportedly resulted in losses of around $3 million.

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