CVE-2024-7340
Published: 31 July 2024
Summary
CVE-2024-7340 is a high-severity Path Traversal (CWE-22) vulnerability in Jfrog (inferred from references). Its CVSS base score is 8.8 (High).
Operationally, ranked in the top 0.5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis
The vulnerability CVE-2024-7340 is a path traversal flaw (CWE-22) stemming from missing input validation (CWE-20) in the Weave server API. Remote callers can request files from a designated directory, but the absence of proper sanitization permits directory traversal and leakage of arbitrary files outside that scope. The affected component is the Weave server, part of the wandb/weave project.
A low-privileged remote attacker can exploit the issue over the network with low complexity to read sensitive files on the host. In typical deployments this access is sufficient for the attacker to obtain administrative credentials or configuration data and thereby assume full server-administrator privileges, producing a CVSS 3.1 score of 8.8.
Public references point to mitigation in wandb/weave pull request 1657 and to detailed analysis published by JFrog Research. The associated EPSS score is currently 0.8769 with a recorded peak of 0.8770.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-2408
Vulnerability details
The Weave server API allows remote users to fetch files from a specific directory, but due to a lack of input validation, it is possible to traverse and leak arbitrary files remotely. In various common scenarios, this allows a low-privileged…
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user to assume the role of the server admin.
- 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.
Directly implements checks on information inputs to reject invalid data before processing.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.