CVE-2025-67732
Published: 05 January 2026
Summary
CVE-2025-67732 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Dify Dify. Its CVSS base score is 8.4 (High).
Operationally, ranked at the 22.0th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Privacy and Disclosure risk domain.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-206235
Vulnerability details
Dify is an open-source LLM app development platform. Prior to version 1.11.0, the API key is exposed in plaintext to the frontend, allowing non-administrator users to view and reuse it. This can lead to unauthorized access to third-party services, potentially…
more
consuming limited quotas. Version 1.11.0 fixes the issue.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: dify, llm
Related Threats
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.
Encrypting or otherwise protecting data at rest directly prevents unauthorized actors from reading sensitive information stored on disk or other media.
Out-of-band delivery transmits sensitive data on a separate path, directly reducing exposure to unauthorized actors on the primary channel.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.