CVE-2023-46315
Published: 22 October 2023
Summary
CVE-2023-46315 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Zanllp Stable Diffusion Webui Infinite Image Browsing. Its CVSS base score is 7.5 (High).
Operationally, ranked at the 37.1th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Other AI Platforms.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-50536
Vulnerability details
The zanllp sd-webui-infinite-image-browsing (aka Infinite Image Browsing) extension before 977815a for stable-diffusion-webui (aka Stable Diffusion web UI), if Gradio authentication is enabled without secret key configuration, allows remote attackers to read any local file via /file?path= in the URL, as…
more
demonstrated by reading /proc/self/environ to discover credentials.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other AI Platforms
- Risk Domain
- N/A
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: stable diffusion
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.
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.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
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.