CVE-2026-100265 in Rider
Summary
by MITRE • 09/30/2026
In JetBrains Rider before 2026.2.1 aI Assistant could auto-update third-party skills without user confirmation
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Analysis
by VulDB Data Team • 09/30/2026
The vulnerability identified in JetBrains Rider prior to version 2026.2.1 involves an insecure default configuration within the integrated AI assistant feature, specifically concerning the management of third-party extension modules known as skills. This flaw allows the application to automatically download and install updates for these external components without requiring explicit user consent or confirmation. In modern software ecosystems that leverage artificial intelligence assistants, such tools often rely on a plugin architecture where core functionality is extended by community-developed or vendor-provided scripts and models. The design decision to enable automatic updates by default introduces a significant trust boundary violation, as it bypasses the principle of least privilege and user awareness regarding changes to the development environment's security posture.
From a technical perspective, this behavior constitutes an insecure configuration vulnerability where the software fails to enforce appropriate access controls or notification mechanisms for privileged operations. When the AI assistant initiates an auto-update sequence for third-party skills, it executes code from external sources that have not been vetted by the end-user at the time of installation. This process effectively grants remote entities the ability to modify local application behavior and potentially execute arbitrary commands within the context of the user's development environment. The lack of a confirmation dialog means that users are unaware when their IDE is pulling in new code, which could include malicious payloads disguised as legitimate feature enhancements or bug fixes.
The operational impact of this vulnerability extends beyond simple privacy concerns to encompass serious security risks related to supply chain integrity and system compromise. An attacker who compromises the repository hosting these third-party skills could push a malicious update that exploits local vulnerabilities, exfiltrates sensitive source code stored in open projects, or establishes persistence mechanisms on the developer's machine. Since JetBrains Rider is often used for complex enterprise applications containing proprietary intellectual property, the unauthorized execution of unverified scripts poses a direct threat to data confidentiality and integrity. Furthermore, this behavior can lead to unexpected changes in IDE functionality that may disrupt development workflows or introduce stability issues if the updated skills are incompatible with existing project configurations.
This vulnerability aligns closely with CWE-20 Improper Input Validation when considering how the application handles updates from external sources without sufficient verification of their authenticity and integrity before execution. It also maps to ATT&CK technique T1195 Supply Chain Compromise, where attackers exploit trusted relationships between software components to gain initial access or maintain persistence. The specific mechanism of auto-updating extensions mirrors tactics used in malware distribution via legitimate update channels, highlighting the risk inherent in automated systems that do not require human-in-the-loop validation for critical changes.
To mitigate this risk, users are strongly advised to upgrade JetBrains Rider to version 2026.2.1 or later immediately upon availability, as this release addresses the underlying configuration flaw by enforcing user confirmation before applying updates to third-party skills. In environments where upgrading is not immediately feasible, administrators should review IDE settings to disable automatic update features for extensions if such an option exists within the preferences menu. Additionally, organizations implementing JetBrains Rider in their development pipelines should establish strict policies regarding approved extension sources and monitor network traffic for unauthorized outbound connections related to plugin repositories. Regular auditing of installed plugins and verification of their digital signatures can further reduce exposure to supply chain attacks targeting AI-assisted development tools.