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Unauthenticated RCE Bug Fixed in SolarWinds Access Rights Manager

  SolarWinds has issued an urgent security advisory for a high-severity vulnerability in its Access Rights Manager (ARM) product, tracked as...

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Gyazo Server Vulnerability Targeted to Steal Millions of User Records


Gyazo, an image-sharing platform, has confirmed a breach after attackers exploited a vulnerability in its upload server, gaining unauthorized access to the company's systems and approximately 23.62 million user records. 

Gyazo was developed by Japanese software company Helpfeel and allows users to upload images, GIFs, short videos and generate links for sharing. There are over 23 million users on the platform from 242 countries and regions, and billions of uploads have been processed. According to Helpfeel, the intrusion occurred on September 11, when a third party exploited a vulnerability in Gyazo's image upload server and became able to execute commands on the system as a result. 

On the same day, the company was notified of suspicious activity and began to investigate the incident. In the early hours of September 12, Helpfeel had blocked the access routes used for the attack and terminated any unauthorized connections. As part of the initial response, the exploited vulnerability was also fixed. However, an investigation revealed that the attacker was already able to access Gyazo's database and obtain user-related information. There are approximately 23.62 million records in the affected dataset. 

Depending on the account, information that will be exposed may include name or nickname, email address, password hashes, user and device IDs, login session IDs, profile information, subscription details, billing status and usage statistics. Additional information may be exposed if an account is linked to an external service. 

According to Helpfeel, integration tokens for accounts connected to X may be included, while Google SSO email addresses may also be included for users who signed in through Google. In a statement issued by the company, it clarified that payment information, including credit card numbers, was not exposed. 

The affected records also include anonymous accounts without registered email addresses, therefore it is not yet known how many people will be affected. The incident involved not only account information, but also a much larger collection of image-related metadata. According to Helpfeel, approximately 490 million metadata records were disclosed, primarily those associated with images uploaded before January 2019. It is possible for an image ID to be exposed, as well as IP addresses and User Agent details, EXIF location information, OCR-extracted text, image titles, and source URLs. 

A separate privacy concern arises from the image metadata, as Gyazo uses image IDs to generate URLs for uploaded captures. According to Helpfeel, the stolen IDs may allow access to some images, so the company temporarily disabled access to affected files while investigating. As a result, approximately 490 million images have been compromised, most of which were uploaded in January 2019 or earlier. 

Information may include image IDs, IP addresses, User-Agent strings, EXIF location information, OCR-extracted text, title of the image, and URL of the source. Besides the data exposed, Helpfeel also identified a separate set of approximately 2.4 million image records which were retrieved according to specific filtering criteria, including hacked passphrases associated with private images. This company has not provided information on the criteria used or clarified whether the records overlap with the larger metadata set. Also exposed in the incident was a list of private images. 

Helpfeel did not exclude the possibility that private pictures were viewed by the attacker. The number of private images accessed has not been determined by the company. Because Gyazo handles image privacy in a very sensitive manner, the disclosure of image IDs is particularly significant. The URL of each capture includes a 32-character ID, and older captures can still be accessed through their original URLs even after they are not prominently displayed within a user's account. 

The leaked identifiers therefore could be used to gain access to content that was not intended to be viewed by the general public. By the early hours of September 12, Helpfeel detected suspicious activity and blocked the identified access routes, terminating the attacker's connections. The exploited server vulnerability was immediately addressed. 

In September 14, the company confirmed the data exposure and reported the incident to the Japanese Personal Information Protection Commission. During the course of the investigation, Gyazo temporarily suspended image delivery. A forensic investigation is currently underway by Helpfeel, and affected users will be contacted directly. 

Anonymous accounts will be handled by Gyazo through notifications posted on the website. Despite finding no evidence of the deletion of image data during the incident, the company has not identified a data leak involving its separate Helpfeel and Cosense services. Users have been advised to change their Gyazo passwords and avoid reusing the same credentials on other services in light of the exposed authentication data. 

Helpfeel has also taken action to invalidate or restrict the affected credentials and authentication information. Furthermore, the company has cautioned against the possibility of exploitation of information disclosed in the breach through suspicious emails and messages.

Plugin4Shell: The Zero-Click Flaw That Broke Every Prominent AI Coding Agent at Once



The security promise was simple. A plugin marketplace reviews a piece of code, locks it to a specific, verified version, and every AI coding agent that installs it gets exactly what was reviewed. No surprises or swaps. That promise just got broken, simultaneously, across every major AI coding agent on the market.

On September 17, cybersecurity startup AIR Security publicly disclosed Plugin4Shell, a zero-click, high-severity remote code execution vulnerability affecting Anthropic's Claude Code, OpenAI's Codex, Microsoft's GitHub Copilot, and Google's Gemini CLI. The name is a deliberate echo of Log4Shell, the 2021 Apache flaw that shook enterprise security teams for months. This one hits a faster-moving target: the plugin ecosystems that have quietly become critical infrastructure for millions of software developers.

The researchers who found it, Or Nevo, Dor Granat, and Niv Hoffman, describe it as the first supply-chain vulnerability of the AI agent ecosystem. That is not a small claim, and the technical details back it up.


How the Attack Works

To understand Plugin4Shell, you need to understand SHA pinning, the mechanism it breaks. When a marketplace approves a plugin, it records a cryptographic commit hash, a 40-character string that uniquely identifies an exact snapshot of the plugin's code. From that point forward, every agent that installs the plugin is supposed to check out precisely that commit. Reviewed code, nothing else, forever.

The vulnerability is a single missing verification step. Affected agents fetch the pinned commit during installation but never confirm that the code they actually land on matches it. That gap opens the door to a Git reference resolution trick.

For Claude Code, Codex, and GitHub Copilot, an attacker who controls a plugin repository can create a branch whose name is the exact 40-character pinned commit hash, set it as the repository's default branch, and point it at malicious code. When the agent runs its checkout, Git resolves the branch name instead of the commit object, because Git prefers a matching reference when the name is ambiguous. The agent installs attacker-controlled code, reports a clean install at the trusted hash, and nothing looks wrong.

Gemini CLI has a slightly different variant. Its installer fetches the target commit and then checks out FETCH_HEAD, but if the repository's default branch is itself named FETCH_HEAD, that checkout resolves to the branch instead. The fetched commit gets silently discarded.

What makes this zero-click is auto-update. Claude Code and Codex update installed plugins in the background by default. When a plugin's pinned commit is swapped upstream, an already-installed, already-trusted plugin gets silently replaced with a malicious version. No prompt. No reinstall. Nothing for the user to notice or decline.

Plugins run with the permissions of the developer operating the agent. That means an attacker who succeeds here lands in the developer's machine with access to source code, cloud credentials, SSH keys, internal repositories, and production systems.


The Context Makes It Worse

Plugin4Shell is the third installment in a series of findings from AIR Security, each one showing a different layer of the AI plugin ecosystem collapsing under scrutiny.

In earlier research called "The Story of Skills," the team published a malicious skill to a trusted marketplace and watched it spread to over 26,000 agents. In SkillJacking, they found 925 skills already in active use had been quietly hijacked from their original maintainers, affecting 134,000 agents, by taking over the repositories behind them.

The industry's answer to SkillJacking was SHA pinning. Plugin4Shell is the answer to that answer. The takeovers AIR demonstrated in SkillJacking can now be combined with Plugin4Shell to bypass the exact safeguard that was supposed to contain them. The chain is proven end to end.


Vendor Responses

AIR found the vulnerability in May 2026, built working proof-of-concept exploits against all four agents, and disclosed everything to the vendors in June. What happened next drew a clear line between the companies that acted and the ones that did not.

Anthropic patched Claude Code in version 2.1.179. OpenAI patched Codex in version 0.146.0. Both confirmed fixes after disclosure.

Microsoft has not shipped a fix for GitHub Copilot. GitHub has argued that its platform blocks branch and tag names that resemble commit hashes, which limits the attack surface for GitHub-hosted plugins. AIR's counter is that Copilot also supports marketplaces hosted on Bitbucket and self-hosted git servers, which permit such names, and that GitHub's restriction does nothing for those configurations. The two positions describe different scopes. Copilot users currently have no patch.

Google's response was to deprecate Gemini CLI entirely. The company confirmed in August that no fix would ship, directing users to migrate to an alternative product called Antigravity. Every existing Gemini CLI installation remains permanently vulnerable.


What Users Should Do Now

The fix, technically, is a single line of verification that every affected agent was missing: after checkout, compare the actual HEAD commit against the pinned hash and abort if they do not match. Because the check runs inside the agent rather than at the marketplace, no marketplace can enforce this guarantee on its own. Only an agent-side fix closes it.

Claude Code users should update to version 2.1.179 or later. Codex users should update to version 0.146.0 or later. Gemini CLI users should migrate away from the product. GitHub Copilot users have no patch available and no confirmed timeline for one.

For enterprise teams that have built internal vetting processes around SHA pinning, Plugin4Shell is a harder problem. The review passed. The pin was written. Different code got installed. Every downstream security process built on that guarantee inherits the failure.

The most striking detail in AIR's disclosure is not the vulnerability itself. It is that four independent engineering teams at four separate companies all made the same mistake, building the same flawed assumption into their auto-update pipelines, and none of them caught it until an outside lab did. That is not an implementation error in one product. That is a design assumption the entire industry shared, and nobody questioned it.

Microsoft Fixes Critical Azure AI Flaw Rated CVSS 10.0

 

Microsoft has patched a maximum-severity vulnerability in Azure AI Foundry that could allow unauthorized attackers to escalate their privileges over a network. Tracked as CVE-2026-85889, the flaw carries a CVSS score of 10.0, making it one of the most serious security issues affecting Microsoft’s cloud-based artificial intelligence services. The company said the vulnerability resulted from missing authentication for a critical function within Azure AI Foundry. There is currently no evidence that the flaw has been exploited in real-world attacks. 

Azure AI Foundry, also known as Microsoft Foundry, is an enterprise platform used to build, deploy and manage generative AI applications and autonomous agents. A successful exploit could have enabled an unauthorized attacker to gain elevated privileges, potentially increasing access to sensitive resources or administrative functions. Security researcher Rémy Marot, who uses the handle @R_Marot, discovered and reported the vulnerability to Microsoft. The company has already addressed the issue across its cloud infrastructure. 

Microsoft said customers do not need to take any action because the affected cloud services have been fully mitigated. Alongside CVE-2026-85889, the company also fixed several other critical cloud vulnerabilities. These include CVE-2026-85885, a command injection flaw in Microsoft 365 Copilot rated 9.9; CVE-2026-85878, an improper authorization issue in Azure Database for PostgreSQL rated 9.9; and CVE-2026-87701, an improper neutralization vulnerability in Azure Cosmos DB rated 9.6. 

The tech giant separately released updates for two Windows vulnerabilities. CVE-2026-62721 affects the Windows User-Mode Power Service and could allow an authorized local attacker to gain SYSTEM privileges. CVE-2026-85921 is a double-free vulnerability in Windows Secure Kernel Mode that could enable privilege escalation to Virtual Trust Level 1. Both vulnerabilities were fixed through an out-of-band update for Windows 11 version 26H1, distributed as cumulative update KB5129194 for arm64 and x64 systems. 

The latest fixes arrive shortly after Microsoft patched 974 vulnerabilities across its software portfolio. Two of those flaws, affecting Windows Advanced Local Procedure Call and the Windows Update Stack, were reportedly exploited in active attacks. Proofpoint and Volexity said the ALPC flaw was chained with two Google Chrome vulnerabilities to create the BlueMoon exploit kit, which multiple espionage-linked threat actors allegedly used to deliver malicious payloads. The developments highlight the growing security risks surrounding cloud platforms, enterprise AI tools and widely deployed operating systems.

WeaselBiscuit Stealer Found in 13 Malicious npm Packages


Researchers have discovered 13 npm packages carrying a previously undocumented JavaScript information stealer called WeaselBiscuit, introducing yet another malicious threat to the npm package ecosystem. In addition to linking the packages together via shared indicators, OpenSourceMalware found several similarities between BeaverTail and OtterCookie, two North Korean malware families. 


A number of packages are included, including @biz44/id10-client, @biz44/id12-client, @biz44/id44-client, @biz44/id79-client, @biz44/id95-client, @biz44/id99-client, @biz44/process-runtime-utils, @biz44/runtime-utils, @biz44/engin1, id79-client, process-lhpm, process-mite, and process-tailwind. Many were first observed between September 12 and September 16, 2026, with some versions still available on NPM at the time of analysis. 

In comparison to BeaverTail and OtterCookie, WeaselBiscuit appears much smaller. In addition to remote access and cryptocurrency theft functions, the malware focuses on profiling hosts and collecting data collected by Chrome extensions rather than carrying a broad range of remote access functions. Malware loaders are launched when a compromised package is imported, causing detached Node.js processes to begin execution.

After retrieving an encoded payload from an Npoint URL, the loader executes the decoded code directly in memory. Following execution, the malware obtains its command-and-control configuration from another Npoint endpoint before connecting to 103.170.217.184:8787. Among the data collected are hostnames, usernames, operating systems, CPUs, and memory, as well as local and public IP addresses. 

Chrome profiles are also searched for extension storage on Windows, Mac OS, and Linux platforms. Chrome's Local Extension Settings directory may contain information associated with browser extensions, including cryptocurrency wallet extensions, which makes this collection especially significant. 

Instead of relying on a specific list of wallet extensions, OpenSourceMalware reported the stealer uploads readable, non-empty files from these locations. C2 servers can also provide commands for monitoring the clipboard and logging Windows keystrokes. 

Despite these capabilities, the recovered malware does not include direct wallet draining functionality, browser password decryption, seed phrase searching, screenshots, or a remote shell access. Additionally, some BeaverTail and OtterCookie activities have a Python-based InvisibleFerret stage that is not present in any other activity. 

Possible Links to DPRK Malware

WeaselBiscuit has been compared to malware associated with the DPRK-linked Contagious Interview campaign, but the attribution has yet to be confirmed. OpenSourceMalware did not find conclusive evidence that the attack was originated by North Korea based on operational infrastructure, victimology, campaign metadata or other identifying materials. 

WeaselBiscuit employs the dead-drop technique of Npoint.io as a dead-drop service, a technique previously observed in Contagious Interview campaigns. Some of its technical indicators, however, overlap with earlier campaigns. Additionally, its code performs public IP and geolocation checks using IPify.org and IP-API.com, while parts of its command-and-control design are similar to OtterCookie's. 

Among the numeric identifiers found in the malware are 10, 12, 44, 79, 95, and 99. These identifiers are similar to campaign markers associated with PolinRider activity, however their exact purpose in WeaselBiscuit is unclear. In terms of capability, BeaverTail and OtterCookie are more closely related. 

Several features are retained in WhistlerBiscuit, including system profiling, Chrome extension data collection, clipboard monitoring, and keylogging, all of which are common to those malware families. However, several of their heavier features are removed, including remote access functions, wallet draining capabilities, screenshots, and secondary payload delivery. 

Researchers at Cisco Talos observed a similar overlap in October 2025, when they discovered that the node-nvm-ssh package contained characteristics related to both BeaverTail and OtterCookie. The findings suggest that code and techniques from these malware families have been found in a variety of combinations within npm-based malicious code. 

The WeaselBiscuit stealer should be viewed for the time being as a distinctive lightweight stealer with distinct technical similarities to DPRK-related tooling rather than a new DPRK malware family confirmed by the DPRK. For a more conclusive attribution, further evidence from infrastructure, campaigns, or code levels would be required.

With the discovery of WeaselBiscuit, security risks are highlighted within the npm ecosystem, particularly for developers utilizing third-party packages. In addition to the ability to collect Chrome extension data and similarity to BeaverTail and OtterCookie, it warrants continued investigation as researchers investigate its origins and wider activities.

RatHat Android Malware Uses AI to Control Infected Devices

 

A new Android backdoor called RatHat utilizes an AI-powered system to remotely navigate compromised devices, while also stealing sensitive information and using a variety of methods to maintain its presence. Researchers at Zimperium’s zLabs found indications that RatHat may be associated with threat actors based in China after they discovered Chinese language prompts within the malware’s AI subsystem. 

The malware is reported to be distributed through malicious advertising, SMS messages and phishing websites that promote APK downloads outside Google Play. RatHat takes advantage of Android’s Accessibility permissions to obtain extensive control over infected devices. This allows it to enable Developer Options and Wireless Debugging, granting it a local shell-level execution environment without the need for a separate computer. Researchers observed similarities with this technique that have been previously seen in the ToxicPanda and RedHook Android malware families. 

The malware utilizes Android Debug Bridge (ADB) access to install a Go-based agent called liblocal-service.so. The agent can execute commands with ADB shell privileges, bypassing battery restrictions and establishing persistence. It can also restore the malware in the case that the main component is removed or stopped. The relationship works in both directions, with the malware being able to restore the agent if the agent itself is deleted. 

RatHat also makes use of a second component, libmedia_codec.so, which acts as an FRP reverse-proxy client and establishes a persistent tunnel to the attackers. The malware has the ability to display HTML overlays over targeted banking and cryptocurrency applications in order to acquire the users’ credentials. Its information-stealing capabilities include SMS messages and notifications, including one-time passwords. RatHat can also monitor text changes, extract URLs from browser address bars and capture lock-screen PINs, passwords and unlock patterns. 

One of RatHat’s most interesting features is its AI-powered interface automation engine. According to Zimperium, the malware converts the Android Accessibility tree into XML and sends the resulting information to an unnamed popular AI assistant. This system can recognize the screen coordinates of requested interface elements and determine their displayed text and provide navigation commands such as scrolling instructions. This enables the malware to navigate Android interfaces more dynamically than other malware that exclusively rely on predetermined scripts. 

Zimperium stated that the AI-driven system makes the malware more adaptable and arguably harder for security software to detect. RatHat actively prevents victims from uninstalling the malware. When an uninstall confirmation screen appears, the malware can intercept the process and cancel the removal and display a fake Google Play overlay, which shows a fraudulent error message. The malware also contains a number of anti-analysis measures, including APK container manipulation, an unusually large 61MB Android manifest and invalid DEX pseudo-instructions that are designed to confuse or disrupt the functionality of security analysis tools. 

Android users are advised to avoid downloading APK files from outside Google Play unless the publisher is explicitly trusted and to be careful when granting Accessibility permissions to applications. In addition, users should regularly scan their devices using Google Play Protect.

Docker Fixes Critical Sandboxes Flaw That Could Expose Host Files

 




Docker has patched two vulnerabilities in Docker Sandboxes that could allow malicious code running inside an isolated sandbox to cross its intended workspace boundary and interact with resources on the host system.

The more severe issue, tracked as CVE-2026-77179, affects Docker Sandboxes versions 0.28.0 through versions before 0.42.0 on macOS and is rated Critical. Docker fixed the vulnerability in Sandboxes 0.42.0, released September 7. The company disclosed the security issues publicly on September 15.

Docker Sandboxes are designed to give AI coding agents their own microVM environment where they can execute code, install packages and use development tools without directly accessing the host. The security architecture treats the microVM as the primary trust boundary, with the agent receiving full control, including "sudo", inside that environment. Resources such as a developer's project directory are selectively exposed across the boundary.

The problem in CVE-2026-77179 occurs in the virtio-fs host server, which handles filesystem sharing between the macOS host and the sandbox. Docker said the component could follow a symbolic link when reopening an unlinked file through a previously stored pathname.

A malicious process inside the VM could exploit this behavior by changing a parent directory into a symbolic link after the original path had been accepted. When the host subsequently reused the stored path, the operation could be redirected to a different location outside the authorized workspace.

This creates a path traversal condition across the VM boundary. Docker said an attacker could consequently read or modify arbitrary host files available to the account running the virtual machine monitor. Depending on what files can be changed, the access could potentially be turned into host-side code execution.

The requirement for malicious code to already be executing inside the sandbox does not eliminate the security concern. Docker Sandboxes are intended to contain precisely the type of untrusted code that an autonomous coding agent might encounter through a compromised repository, malicious dependency, poisoned package or manipulated instruction. If that code can alter host-visible filesystem paths, the microVM's isolation boundary becomes vulnerable at the point where the host performs the subsequent filesystem operation.

The second vulnerability, CVE-2026-79994, affects versions 0.37.0 through versions before 0.42.0. Docker rates it High with a CVSS 4.0 score of 8.7.

This issue affects the guest-to-host relay used for Unix domain sockets. The relay initially verified that a requested socket was located inside an authorized workspace, but later established the connection by using the pathname again. A malicious guest could change an intermediate directory into a symlink during that interval, causing the host to connect to an AF_UNIX socket outside the permitted workspace.

The vulnerability is classified as a time-of-check to time-of-use (TOCTOU) race condition, because the security decision is made against a pathname whose meaning can change before the privileged operation occurs. The resulting connection could expose data or host-side capabilities provided by the targeted socket.

Together, the two flaws expose different host interfaces through a similar underlying weakness: trusting a pathname after an attacker-controlled environment has had an opportunity to alter what that pathname resolves to.

The risk is amplified by how Sandboxes share development workspaces. Docker says "sbx run" normally mounts the current directory into the sandbox with read-write access, meaning an agent can directly modify the developer's working tree. Docker also warns that files such as Git hooks, CI configuration, IDE task definitions and project scripts can affect subsequent host-side development activity.

For users unable to update immediately, Docker recommends clone mode and advises against additional read-write host mounts. Clone mode mounts the repository read-only at "/run/sandbox/source" while the agent works from a private clone inside the VM. However, it is not a confidentiality boundary: files available in the mounted repository, including untracked files such as ".env", may still be readable by the agent.

Docker has reported no exploitation of either vulnerability. Neither issue was listed in CISA's Known Exploited Vulnerabilities catalog at the time of disclosure.

The company credited Oren Yomtov of accomplish.ai with discovering CVE-2026-77179 and Jurre van Bergen of ThreatNotify with finding CVE-2026-79994.

The fixes arrived amid wider security scrutiny of AI coding environments. Earlier research from Cyera Research Labs demonstrated how a prompt-injected coding agent operating inside a Docker-based environment could be used as part of an attack chain against the host through a separate Docker Engine vulnerability. The latest disclosures reinforce the importance of treating autonomous coding agents as potentially hostile workloads, even when they are placed inside purpose-built isolation mechanisms.

Users running affected Sandboxes versions should upgrade to 0.42.0 or later. Docker Sandboxes 0.43.0, released September 15, is the latest stable release as of September 18.

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