CVE-2024-23331
Published: 19 January 2024
Summary
CVE-2024-23331 is a high-severity Improper Handling of Case Sensitivity (CWE-178) vulnerability in Vitejs Vite. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 34.5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-0322
Vulnerability details
Vite is a frontend tooling framework for javascript. The Vite dev server option `server.fs.deny` can be bypassed on case-insensitive file systems using case-augmented versions of filenames. Notably this affects servers hosted on Windows. This bypass is similar to CVE-2023-34092 --…
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with surface area reduced to hosts having case-insensitive filesystems. Since `picomatch` defaults to case-sensitive glob matching, but the file server doesn't discriminate; a blacklist bypass is possible. By requesting raw filesystem paths using augmented casing, the matcher derived from `config.server.fs.deny` fails to block access to sensitive files. This issue has been addressed in vite@5.0.12, vite@4.5.2, vite@3.2.8, and vite@2.9.17. Users are advised to upgrade. Users unable to upgrade should restrict access to dev servers.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
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.
Associating and retaining security attributes with data directly supports enforcement of access control decisions across storage, processing, and transmission.
Enforces rules governing access to the system and its data from external systems based on established trust relationships.
This control requires verifying that a sharing partner's access authorizations match the information's restrictions before sharing occurs.
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.