Sony Network Communications has confirmed a data breach that compromised approximately 2.5 million records containing current and former customers’ personal information. A Sony Group Corporation subsidiary, the company provides telecommunications and technology services, acting as an internet service provider (ISP) in Japan. The breach occurred on October 19 and was detected four days later, when the company shut down the compromised servers and blocked external communication. In an announcement yesterday, the company said that its So-net member database, supporting its internet access service, was accessed by an unauthorized party. The investigation confirmed that a total of 2,585,481 customer records had been exposed, including the following types of information: No banking, payment card, or other account details were exposed.
Microsoft again asked Entra ID administrators to migrate users to phishing-resistant methods to avoid sign-in disruptions before it retires SMS and voice authentication in February 2027. This retirement process applies only to Microsoft Entra ID workforce tenant authentication scenarios and not to Azure AD B2C or Microsoft Entra External ID customer identity scenarios. Before Microsoft retires SMS and voice authentication, admins should ensure all users in their organizations use a phishing-resistant method, since they will no longer be able to use them to complete multifactor authentication and log in to their accounts. Admins can choose from passkeys, QR code authentication, FIDO2 security keys, and other Entra ID-supported sign-in methods. "Microsoft-provided SMS and voice authentication will retire starting February 1, 2027. Complete your migration before rollout begins to avoid interrupting users' sign-in experience," Microsoft said in a Microsoft 365 Message Center update on Tuesday.
Attackers are actively exploiting vulnerabilities across critical network infrastructure, and PHP flaws known as "PHP2Shell" put the web management interfaces of firewalls, VPNs, application delivery controllers, and other appliances at risk. The findings come from Eclypsium's October InfraTrust Pulse, a monthly report tracking security advisories affecting network devices, servers, firmware, chips, and other infrastructure. Between September 18 and October 14, InfraTrust tracked 133 new security advisories across 18 vendors, covering 2,813 vulnerabilities. Of those advisories, 37 were rated critical, five had a maximum CVSS score of 10.0, and 58 could be exploited remotely without authentication. Sixteen newly published advisories included vulnerabilities listed in CISA's Known Exploited Vulnerabilities catalog (KEV) as they were actively exploited.
Attackers have begun probing the Internet for systems unpatched against a recently disclosed critical Oracle E-Business Suite (EBS) vulnerability. Discovered in a core component of EBS's Application Object Library and tracked as CVE-2026-101767, this flaw lets unauthenticated threat actors with HTTP network access take over vulnerable systems in low-complexity attacks. Oracle released security updates to address the issue in its October 2026 Critical Security Patch Update on October 20 and urged customers to patch their systems immediately. "In some instances, it has been reported that attackers have been successful because targeted customers had failed to apply available Oracle patches," it said. "Oracle therefore strongly recommends that customers remain on actively-supported versions and apply security patches without delay."
On Tuesday, the US Cybersecurity and Infrastructure Security Agency (CISA) confirmed that hackers have begun exploiting a critical Brotli vulnerability known as Node2Shell, Broccoli2Shell, and HTTP2Shell. Tracked as CVE-2026-111497, this critical-severity flaw stems from an out-of-bounds write weakness in the Brotli decoder used to expand data compressed with Google's widely popular Brotli lossless compression algorithm. Unprivileged attackers can use a maliciously crafted Brotli-compressed stream to trigger crashes or memory leaks and, in some cases, gain remote code execution on devices with vulnerable Brotli libraries or binaries. The security issue was first identified in the Node.js JavaScript runtime environment, but it also affects HTTP servers and clients that rely on vulnerable Brotli implementations.
U.S. Cybersecurity and Infrastructure Security Agency (CISA) adds Google Brotli and Adobe Commerce and Magento flaws to its Known Exploited Vulnerabilities catalog. The U.S. Cybersecurity and Infrastructure Security Agency (CISA) added Google Brotli and Adobe Commerce and Magento vulnerabilities to its Known Exploited Vulnerabilities (KEV) catalog: Below are the flaws added to the catalog: CVE-2026-111497 (CVSS score: 9.2) – An unchecked return value vulnerability in Google Brotli that could allow a remote, unauthenticated attacker to corrupt decoder memory, expose sensitive information, cause a denial-of-service, or potentially execute arbitrary code by sending a specially crafted Brotli-compressed stream. CVE-2026-48356 (CVSS score: 9.3) – An unrestricted file upload vulnerability in Adobe Commerce and Magento that could allow an attacker to execute arbitrary code with the privileges of the current user, potentially gaining elevated access or taking control of the victim’s account or session. Brotli is a data-compression algorithm developed by Google.It reduces the size of web content, such as HTML, CSS, JavaScript, and other text-based resources. Security researchers have observed exploitation attempts targeting CVE-2026-111497 (aka Node2Shell), a critical flaw in Google’s Brotli library. Previdian recorded one attempt by October 27, while ELLIO researchers recently detected traffic carrying a public exploit that could execute code on vulnerable systems. The activity may indicate attempts to exploit the flaw on a larger scale, but its scope remains unclear. An attacker can trigger the vulnerability to cause crashes, expose sensitive memory or remote code execution when applications decompress attacker-controlled Brotli data. Because Brotli is widely used, multiple projects and vendors have released security updates, including Node.js, PHP, Bun, and Microsoft .NET. Cybersecurity firm Wiz warned that 91% of cloud environments contain resources vulnerable to the flaw, while 82% have publicly exposed Node.js instances. The second flaw added to the catalog is an unrestricted file upload vulnerability tracked as CVE-2026-48356, dubbed PolyShell. Recently WordPress security firm Sansec warned of attacks exploiting CVE-2026-48356 to infect at least 953 of online stores. The attackers reportedly used a Magento CMS block to insert a malicious loader capable of retrieving and executing a payload hosted under their control. So far, researchers have not recovered the subsequent payload, leaving the campaign’s ultimate objectives unclear. The activity is believed to have been underway since at least July 2025 and remains ongoing. According to Binding Operational Directive (BOD) 22-01: Reducing the Significant Risk of Known Exploited Vulnerabilities, FCEB agencies have to address the identified vulnerabilities by the due date to protect their networks against attacks exploiting the flaws in the catalog. Experts also recommend that private organizations review the Catalog and address the vulnerabilities in their infrastructure. CISA orders federal agencies to fix the flaws by October 29, 2026. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, CISA)
Background Network-connected surveillance cameras are now widespread in both home and enterprise environments, so securing them is essential to safeguarding physical spaces and sensitive assets. As these devices continue to gain new features and network connectivity capabilities, vulnerabilities in their implementation can have significant security implications. During our research, we discovered a denial-of-service vulnerability that affects Intelbras IP cameras systems. The flaw resides in a firmware update endpoint that is accessible without authentication and allows anyone with access to the local Wi-Fi network to knock cameras offline. A single request disrupts the camera for only about a minute, but sending periodic requests keeps the device offline indefinitely. We reported the issue to Intelbras, monitored the remediation process, validated the fix in the new firmware, and will now demonstrate the exploitation procedure step-by-step. Following our notification, Intelbras patched the vulnerability and released updated firmware (R.260804) along with update instructions. A candidate ID of CAN-2026-2035970 has been assigned by MITRE following submission, pending the final CVE assignment. Additionally, the Intelbras team recently informed us that MITRE has classified the vulnerability as Medium, assigning it a score of 5.1 under the CVSS 4.0 framework. The issue discussed in this article is no longer present in the latest firmware version. Firmware Intelbras provides firmware files on its official website. While users can manually install these updates via an SD card, the cameras also natively support firmware upgrades over the local network via their web interface and mobile app. We obtained the firmware version v240927 for the iM3B-C camera, which was the latest available version at the time of our research. According to Intelbras, the same firmware is also compatible with the iMX C, iM4 C, iM5 SC, iME 360 C, and iM7+ FC models. Below, we can view the firmware version and the camera model used as an example. To provide context, we will explain how the camera’s authentication mechanism works and why it is relevant to accessing the camera’s endpoints. The main firmware component is an ARM binary named sonia, responsible for controlling the kernel drivers used by the camera hardware, authentication, and livestream recording, among other things. How authentication works The global.login RPC method handles authentication at the /RPC2_Login endpoint. First, the client, such as the mobile app or a custom script, sends the username and an empty password. The camera responds with an authentication challenge (a set of values to verify the password without transmitting it). This response returns a temporary session, the encryption type in the encryption field, a random value, and a realm (authentication scope). At this stage, a false response is normal and does not indicate a failed login, as the authentication process is not yet complete. Next, the client calculates the response password from the authentication challenge. It first generates an MD5 (username:realm:original_password) hash as the base. It then calculates a second MD5 (username:random:first_md5) hash, where first_md5 is the result of the previous step. To complete the authentication, the client sends this final result back to /RPC2_Login in a second global.login call, passing the username, calculated password, and temporary session ID. If the login is accepted, the camera returns true and a new, authenticated session. This session must be used for all subsequent RPC calls, including the camera’s other endpoints, for example, the one that reboots the device or those that expose sensitive information. Affected endpoint The affected endpoint is the firmware upgrade route http://<ip_address>/firmwareUpgrade_service/Demo, which lacks authentication checks; furthermore, it fails to verify whether the firmware is actually valid before initiating the upgrade process. This creates a serious issue because the upgrade requires the camera to reboot, and that is precisely when the problem occurs: the camera enters reboot mode and eventually shuts down, appearing offline to the user and anyone who has the camera registered on their device. PoC: vulnerability exploitation Now that we have outlined how the vulnerability works, we will use a Python script on an iM3B-C camera to exploit it for demonstration purposes. The exploit contacts the camera’s endpoint to upload firmware. Below, we can see sonia creating the endpoint responsible for the firmware upgrade. Next, the exploit will hit the endpoint and cause the camera to reboot. Consequently, mobile phones running the Intelbras app will lose connection with the registered device. Below, we can see the camera operating normally: the green light is on and the app is showing it is available for viewing. The camera is online After the exploit executes, we can see the effects: the camera goes offline and loses connection to the registered devices. The camera is offline The exploit is quite simple: it sends an HTTP POST request with the firmware, which causes the camera to accept the request and initiate the reboot process. It does not matter whether the firmware is original; the reboot process will start regardless. New firmware version After we notified Intelbras about this flaw in the endpoint implementation, the company contacted the OEM vendor. As a result, a new firmware version was released that requires authentication to initiate an update through this endpoint. Below, we can compare the new firmware, which validates cookies and session data, with the old firmware, which performed no authentication checks and proceeded directly to the update routine. Real risk An attacker can remotely trigger the camera firmware upgrade and reboot process without authenticating or supplying a valid firmware image. This may cause the device to go offline, which results in a denial-of-service condition preventing legitimate users from accessing live monitoring or managing the camera. The potential impact is significant due to the number of affected users. The Intelbras Mibo Smart app, which the company provides to connect and manage the devices mentioned in this report, has over 4,000,000 downloads. Brazil represents the largest user base, followed by Paraguay, Ecuador, Colombia, Argentina, Chile, Peru, Bolivia, Uruguay, and Venezuela. As a result, exploitation of this issue affects a large number of users. Takeaways This is a medium-severity vulnerability that Intelbras is already aware of. The issue has been addressed in a newer firmware release (R.260804 along with update instructions), which mitigates this attack vector. Because the vulnerability directly affects the availability and normal operation of the affected cameras, it is highly recommended that users verify the firmware version currently installed on their devices and update to the latest available version as soon as possible. Keeping the firmware up to date is an essential security practice, especially for internet-connected surveillance devices, as outdated versions may remain exposed to known vulnerabilities.
Three Japan-focused cyberattacks show how AI helps hackers scale operations, while exploiting old systems and weak security remains key. In autumn 2026, Japanese companies and other organizations reported a series of data leaks involving their web systems. On October 9, Japan’s National Cybersecurity Office issued a warning to businesses, while the head of the ruling party’s cybersecurity team described cyberspace as being in a “state of emergency.” Researchers at Trend Micro studied three attack infrastructures to understand how hackers use AI. Their findings show three different approaches, ranging from limited AI assistance to systems that use AI agents to manage almost an entire attack. The researchers looked at files that attackers left on servers anyone could reach. These included attack scripts, lists of targets, logs, and records of commands. The files showed attacks on organizations in Japan and other countries. But the researchers could not see the victims’ own logs or network records. So they could not confirm every break-in, measure the full damage, or say who was behind it. Attackers also like to claim more success than they really had. The researchers only counted a result as real when the evidence backed it up. The three cases show that AI does not play the same role in every cyberattack. “The cases differ along two dimensions: how much of the attack AI handled and how confidently we can establish its involvement.” reads the report. “Case A used AI to drive the entire workflow, which we confirmed. Case B was human-led, with confirmed AI assistance in planning and tool development. Case C showed high-confidence indications of AI use in a limited role, such as tool development. All three were active in 2026, and much of the activity preceded the previously published ARTEX reports.” Case A: AI agents managed the attack workflow. The researchers confirmed the use of CyberStrikeAI, an open-source penetration-testing platform built around AI agents. It handled reconnaissance, vulnerability checks, exploitation, data theft and reporting as part of a repeatable process. The platform split tasks among multiple AI agents. One record mentioned a credential-search agent in a system that used 44 agents. The platform could also generate Japanese content, including forms and fake login pages. Researchers identified at least 19 target organizations, including at least 16 in Japan. The system worked on several targets at once and kept traffic to each organization relatively low. This made the activity harder to detect by checking the logs of a single victim. Despite this automation, the platform rarely gained deep access to target systems. In many cases, it had no active session or web shell and showed no evidence of stolen data. The clearest intrusion started through an administration page that was publicly accessible on an old web system. The attackers did not need to exploit a newly discovered vulnerability. Case B: A human attacker used AI to plan and build tools. In this case, the operator made the main decisions but used a large language model to speed up planning and tool development. The researchers found an attack plan written by an LLM that targeted services providing AI and GPU resources. The attacker presented requests as authorized security testing to get around the model’s safety limits. The researchers say this was a false claim, although they did not publish the exact method. The attacker also targeted AI infrastructure, including platforms for AI workflows, data processing and model inference. The researchers believe the goal may have been to gain access to computing resources that could be used to run AI models cheaply. Some intrusions had serious consequences. In one case, the attacker gained control across several systems, including an FTP service, a database, an administrator account, a web shell and SSH access. The attacker also restored backdoors after they had been removed. In another case, a geographic information system server was exposed with default credentials. This provided access to hundreds of thousands of land and business records, as well as Windows credentials and email data. The evidence confirmed that information was downloaded. However, the researchers found no evidence that AI carried out these attacks independently. It helped the operator plan and build tools, while the actual work relied mainly on scripts, existing software and human decisions. Case C: AI played a limited role. Here, the operator appears to have used AI mainly to develop tools and scripts. The researchers found no evidence that it was involved in planning or managing the wider operation. They rated AI involvement as highly likely, but not confirmed, because they found no direct evidence such as prompts or API keys. The operator ran at least six campaigns in 2026, targeting exposed VPN devices and Oracle WebLogic servers. The targets included devices from Cisco, Citrix, F5 and Yamaha. In attacks against Yamaha RTX1210 routers, the operator did not exploit a product vulnerability. Instead, the attacker used credentials found in configuration files. These credentials provided direct access to internal corporate networks. The researchers also found signs that AI may have helped write some commands and scripts. These included unusually structured comments and emoji used as status markers. Such clues can support an assessment, but they cannot prove AI use on their own. Japan was the main target in all three operations, but attackers also targeted other countries and regions. All three used Simplified Chinese, but this does not prove they came from the same group or location. “Simplified Chinese was the working language in all three infrastructures. Japan was the largest target country, although the operators also pursued nearby countries and regions. Entry points were exposed legacy systems or weaknesses left in default configurations.” concludes the report. “Target selection was opportunistic across industries: the operators sought systems that were easy to attack from outside and acted on what they found.” The main difference was how AI was used. In one case, AI agents managed much of the attack and worked on many targets at once. In another, AI helped a human plan attacks and build tools. In the third, AI was mainly used to develop tools. AI helped make attacks faster and easier to scale, but attackers still exploited familiar weaknesses, such as outdated web systems, exposed admin pages, default passwords and poorly secured network devices. Researchers also found that AI tools sometimes reported planned actions as successful, making it essential to verify their results. AI can also help defenders discover vulnerabilities. However, researchers found no evidence that these three operations used AI-discovered zero-day flaws. Their attacks relied on known vulnerabilities and poor security settings. The report identifies six main priorities for defenders: Review public-facing systems. Identify old web applications and update them or isolate them if they cannot be secured. Protect administration pages. Check that management interfaces are not exposed to the internet without a clear need and strong access controls. Secure VPNs and network devices. Review configurations, remove default credentials and check for reused passwords. Protect internal AI services. Include AI workflows, inference services and GPU systems in asset inventories, and check whether they are exposed. Improve monitoring. Look for low-volume attacks spread across many targets, which may be difficult to spot in the logs of a single organization. Prepare for AI misuse. Organizations that use LLMs for work should train staff to recognize requests that falsely claim to be authorized security testing. These security weaknesses existed long before AI became widely available. AI simply helps attackers find and exploit them faster and across more systems. The time between discovering a vulnerability and using it in an attack may also become shorter. Organizations should install security updates quickly and apply temporary protections when patches are not available. Researchers still don’t know who was behind the three operations, whether they were connected or how much damage they caused. Further reports may provide more answers. “The attackers’ identities, whether the three cases share an operator, the full scale of the damage, and the AI models used remain unresolved. Our observations come from attacker-side files and still require confirmation from the affected organizations.” concludes the report. “We are considering further technical reporting on individual cases: AI-driven activity in Case A, AI assistance in Case B, and limited AI assistance in Case C. We will also continue working with the relevant organizations.” The main lesson is clear: AI can make cyberattacks faster and larger, but the basic security priorities remain the same. Organizations must identify systems exposed to the internet, strengthen access controls and detect suspicious activity before attackers turn a simple weakness into a serious breach. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, Italy)
Tailscale has released version 1.104.4 to fix flaws in its built-in SSH server that could let an attacker reach services and files on other servers that only the root user should be able to touch. The flaws are in how Tailscale SSH forwards network connections, a job the Tailscale background process carries out with root privileges. To use them, an attacker must
A credit card skimming group reportedly compromised a shared analytics script used by e-commerce platform Convertr to steal shoppers’ payment data during checkout. The campaign was identified on October 24 and has been attributed to a Brazilian gang, active since at least July 2024, that focuses on infecting online stores running Magento, OpenCart, and WooCommerce platforms. Convertr is a Brazilian e-commerce platform that powers online stores and checkout systems for dozens of major fashion brands in the country, handling R$2 billion ($370M) in sales. E-commerce security firm Sansec says that the attacker modified the Plausible tracker file hosted on a self-managed server operated by Convertr. Ecommerce cybersecurity company Sansec says that the attacker modified the tracker file on a self-hosted server for Plausible, an open source alternative to Google Analytics, managed by Convertr.
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