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Drupal Commerce Flaw Exposes Online Stores to Fraudulent Order Manipulation

  Drupal has confirmed active exploitation of a highly critical access bypass vulnerability in its Commerce Core module, warning online reta...

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Cyber-Attacks Target Ukraine and Russia Emergency Alert Apps

 

Ukraine and Russia have both reported cyber-attacks on their emergency warning applications, sending false alerts that briefly raised fears of nuclear, chemical, and street-fighting threats. In Ukraine, residents began receiving fake red-level air-raid notifications at around 22:47 local time on Sunday, followed by warnings of radiation, a chemical attack, and fighting in Kyiv. The alerts were cancelled within an hour, and Ukraine’s air force said there was no radiation threat, blaming Russian interference. Hours later, Russia said its own emergency ministry app had also been hit by a “massive cyber-attack,” although it insisted the country’s wider public alert system remained operational. 

The false messages caused understandable alarm, particularly in Kyiv, where residents are already accustomed to repeated warnings of drone and missile attacks. One resident, Olena, told the BBC that her first reaction was fear because she had prepared for blackouts and disruptions to heating and water, but not for a nuclear attack. She said later alerts written in Russian made her realise the application had been compromised, since official notifications normally arrive in Ukrainian. Ukraine’s emergency service urged citizens to rely on loudspeaker announcements and avoid clicking links from unknown sources. 

A possible tit-for-tat attack

The nature of the messages has led cyber experts to suspect hacktivist involvement rather than a highly disciplined state operation. Some alerts were informal and provocative, while a newly created Telegram channel linked to one message quickly attracted more than 15,000 subscribers and spread anti-Ukrainian propaganda. The BBC’s cyber correspondent reported that dozens of hacktivist groups have emerged on both sides since Russia’s full-scale invasion, often using attention-grabbing hacks for political messaging. However, no group has officially claimed responsibility, and it remains unclear whether the two incidents were directly connected.

The near-simultaneous attacks have also raised questions about retaliation. Reports suggest Ukraine’s Trivoha app was compromised first, followed shortly by Russia’s emergency app, prompting speculation of a tit-for-tat cyber exchange. A Ukrainian parliamentarian said he could neither confirm nor deny Ukrainian involvement in the attack on Russia, while arguing that Russia was likely behind the intrusion into Ukraine’s system. Russian officials, including President Vladimir Putin’s press secretary Dmitry Peskov, said government digital resources face constant cyber-threats, though they did not directly attribute the emergency app incident. 

The episode highlights how digital infrastructure has become a central battlefield in the Russia-Ukraine war. Beyond physical strikes, attacks on communications and warning systems can undermine public trust, create confusion during emergencies, and weaken civilians’ sense of security. UK Defence Secretary Wes Streeting said the identity of the attacker was not yet known but that Britain was monitoring the situation closely, while EU foreign policy chief Kaja Kallas described cyber-attacks as part of Russia’s broader warfare against Ukraine. As both countries continue exchanging strikes on energy and military targets, the hacking of emergency alert apps shows that the conflict is increasingly fought through screens as well as on the ground.

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 increasingly focusing on frequent, short-duration attacks in place of concentrated traffic floods. According to the company, 18.2 million network-layer DDoS attacks were mitigated during the third quarter of 2026, an increase of 208% from the previous period. 

It was published on October 29, analyzing attack activity between July and September. Cloudflare's threat intelligence team, Cloudforce One, also reported mitigating 14.4 trillion HTTP DDoS requests during the quarter. There were approximately 8,226 network-layer attacks per hour, which equates to one attack every 0.44 seconds. These findings provide an indication that attackers are altering their operational approaches. 

In Q3, Cloudflare recorded 251 attacks exceeding 1 terabit per second (Tbps), compared with 805 in Q3. This represents approximately a 69% decrease in attacks exceeding 1 Tbps. There was a significant increase in smaller, short-lived attacks as one of the most notable findings. According to Cloudflare, 96% of network-layer DDoS incidents lasted less than 10 minutes, while 98% generated traffic below one gigabyte per second. 

Even though these attacks have relatively low bandwidth, they can cause disruptions to websites, servers, and online services, particularly when infrastructures lack network capacity or are inadequately protected. Security teams that rely on manual investigation and response may have difficulty identifying and resolving these attacks due to their short duration, since attacks may end before analysts can identify and address Cloudflare's incident associated with DDoS-for-hire, commonly referred to as booters or stressers. 

The use of such services allows attackers to flood targeted websites without requiring sophisticated attack infrastructure. These campaigns targeted software development, gambling and gaming businesses, as well as information technology companies. As a consequence of law enforcement operations in 2026 that disrupted four major Internet of Things botnets: Aisuru, KimWolf, JackSkid, and Mossad, hyper-volumetric attacks decreased earlier in 2026. 

The reduction in compromised connected device threats has not been eliminated, however. Cloudflare has continued to observe emerging IoT botnet variants, including Dysphoria and Evooo1Bot, which indicates the ecosystem continues to operate despite disruption efforts. Additionally, Mirai-classified traffic remained substantial in August, reaching 57.23 petabytes in mitigation. 

Organizations should also monitor exposed network services as attack methods change. DNS resolvers and directory services accessible from the public internet can be abused to perform reflection and amplifier attacks. To prevent attackers from exploiting these systems to generate malicious traffic, security teams must ensure that these systems are properly configured and restricted. It is also evident that Cloudflare's findings point to a broader distribution of DDoS targets.

Although Media, Production & Publishing was the most attacked industry in Q3, the share dropped by approximately a quarter compared to its previous quarter. There was substantial activity in information technology, computer software, telecommunications, as well as internet infrastructure in Q3. The top ten also included Consumer Services and Adult Entertainment, ranking eighth and ninth respectively. Geographic targeting indicated similar changes. 

The United States regained its position as the most attacked country, followed by China, while Indonesia became third with 2.93% of recorded attacks. Among the sharpest increases occurred in Canada, which moved from 16th to sixth place after attacks targeted retailers, telecommunications companies, service providers, and marketing firms. Furthermore, Israel jumped seven places to reach tenth place after sustained DDoS activity occurred during September. 

Cloudflare attributed the increase to heightened tensions in the region and domestic political developments in September. With the increasing frequency of short-duration attacks, organizations relying on manual incident response face a particular challenge. In the event of a network-layer attack ending within ten minutes, security teams may not have time to investigate alerts and implement countermeasures before the attack ends. 

The repeated disruption of online transactions, customer-facing platforms and other internet-based services, regardless of whether or not they cause prolonged outages, can also adversely affect them. A significant component of modern DDoS protection is automated detection and mitigation, according to Cloudflare. With a global network of more than 330 cities and a reported capacity of 500 Tbps, Cloudflare provides protection across more than 330 cities. 

The company provides a free DDoS Botnet Threat Feed that assists hosting providers, cloud platforms and internet service providers in detecting malicious IP addresses and accounts related to botnet activity. Over 800 networks worldwide have enrolled in this service. DDoS protection must be capable of addressing both high volumes of attacks as well as repeated smaller disruptions, according to Q3 findings. 

The presence of new variants and changing traffic techniques continues to pose risks to internet-facing infrastructure, even as law enforcement operations reduce the frequency of some large-scale botnet attacks.

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.

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