CVE-2026-112265 in LangBot
Summary
by MITRE • 10/19/2026
LangBot through 4.11.0 contains a missing authenticity verification vulnerability that allows unauthenticated attackers to inject forged Lark/Feishu events by skipping signature checks. Attackers knowing a bot UUID can POST fabricated im.message.receive_v1 or card.action.trigger events to drive the LLM pipeline, tools, and approvals as other users.
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Analysis
by VulDB Data Team • 10/19/2026
The vulnerability identified in LangBot versions through 4.11.0 represents a critical failure in authentication mechanisms within the integration layer for Lark and Feishu platforms. This flaw is classified under CWE-347, which denotes Improper Verification of Cryptographic Signature, indicating that the application fails to adequately verify the authenticity of incoming data payloads before processing them. The core technical issue lies in the absence of rigorous signature validation when handling events received from the Lark or Feishu APIs. Specifically, the system does not enforce checks on the cryptographic signatures associated with webhook events, allowing any external actor who possesses a valid bot UUID to bypass security controls entirely. This architectural oversight transforms what should be an authenticated channel into an open vector for unauthorized command injection and data manipulation.
From an operational perspective, this vulnerability enables unauthenticated attackers to inject forged Lark or Feishu events directly into the application's event stream. By exploiting the lack of signature verification, adversaries can POST fabricated im.message.receive_v1 or card.action.trigger payloads to the system. These specific event types are particularly dangerous because they serve as primary inputs for downstream processing pipelines. The im.message.receive_v1 event typically triggers natural language processing and response generation, while card.action.trigger events often initiate complex workflows involving tools, approvals, or external API calls. Consequently, an attacker can manipulate these flows to execute arbitrary actions on behalf of legitimate users without their knowledge or consent.
The impact of this vulnerability extends beyond simple data injection; it fundamentally compromises the integrity of the Large Language Model pipeline and associated automation tools. Since LangBot relies on these events to determine user intent and trigger corresponding actions, forged inputs can lead to severe security breaches such as unauthorized access to sensitive information, execution of malicious commands via connected tools, or manipulation of approval workflows. This aligns with MITRE ATT&CK technique T1059, Command and Scripting Interpreter, where the attacker uses the application's own logic against it to perform actions that were not intended by the system administrators or end-users. The ability to impersonate other users further exacerbates the risk, as it allows for social engineering attacks within the organizational chat environment and potential privilege escalation if certain tools have elevated permissions.
To mitigate this vulnerability, immediate remediation is required by updating LangBot to a version later than 4.11.0 where proper signature verification has been implemented. Developers must ensure that all incoming webhook events from Lark or Feishu are validated against the expected cryptographic signatures using the provided secret keys before any processing occurs. This involves implementing strict input validation and ensuring that the application rejects any payload lacking a valid, verifiable signature. Additionally, organizations should review their bot configurations to minimize permissions granted to bots, adhering to the principle of least privilege. Regular security audits and penetration testing focused on API authentication mechanisms are recommended to detect similar weaknesses in other integrations before they can be exploited by malicious actors seeking to compromise organizational workflows or data integrity.