CVE-2026-28509 in LangBot
Summary
by MITRE • 03/06/2026
LangBot is a global IM bot platform designed for LLMs. Prior to version 4.8.7, LangBot’s web UI renders user-supplied raw HTML using rehypeRaw, which can lead to a cross-site scripting (XSS) vulnerability. This issue has been patched in version 4.8.7.
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Analysis
by VulDB Data Team • 03/16/2026
The vulnerability identified as CVE-2026-28509 affects LangBot, a global instant messaging platform specifically designed for large language models. This security flaw exists in versions prior to 4.8.7 and represents a critical cross-site scripting vulnerability that compromises user safety and platform integrity. The issue stems from the platform's web user interface implementation where user-supplied raw HTML content is processed through the rehypeRaw library without adequate sanitization measures. This processing method creates an exploitable condition where malicious actors can inject harmful scripts into the platform's interface, potentially affecting all users who view the compromised content.
The technical flaw manifests through the improper handling of user-generated content within LangBot's web UI environment. When users submit HTML content that includes malicious script tags or other harmful code elements, the rehypeRaw library processes this raw HTML without filtering or sanitizing the input. This processing approach directly violates secure coding principles and creates a pathway for attackers to execute arbitrary JavaScript code within the context of other users' browsers. The vulnerability falls under CWE-79 which specifically addresses cross-site scripting flaws, and aligns with ATT&CK technique T1566.001 for initial access through spearphishing attachments or links. The implementation of rehypeRaw without proper content validation creates an environment where attackers can craft malicious payloads that persist within the platform and execute when other users interact with the compromised content.
The operational impact of this vulnerability extends beyond simple script execution, as it represents a fundamental security weakness in a platform designed for artificial intelligence interactions. Users who engage with the LangBot platform may unknowingly be exposed to various attack vectors including credential theft, session hijacking, or redirection to malicious websites. The vulnerability affects all users who might encounter malicious HTML content within the platform's messaging or content display areas, creating a widespread security risk. Given that LangBot is designed for LLM interactions, the potential for exploitation increases as users may be more likely to trust content from the platform, making social engineering aspects of the attack more effective. The persistence of this vulnerability across multiple versions indicates a lack of proper input validation and security testing in the platform's development lifecycle.
The mitigation strategy for CVE-2026-28509 requires immediate implementation of the patched version 4.8.7 which addresses the root cause by properly sanitizing user-supplied HTML content before rendering. Organizations should implement comprehensive input validation and output encoding mechanisms to prevent similar issues in the future. The fix should include integration of proper HTML sanitization libraries that can strip malicious content while preserving legitimate formatting. Security teams should conduct thorough penetration testing and code reviews focusing on all user input handling within the platform. Additionally, implementing content security policies and regular security assessments will help prevent future vulnerabilities of this nature. The patch addresses the specific rehypeRaw processing issue while reinforcing the platform's overall security posture through improved content handling protocols.