CVE-2023-39357
Published: 05 September 2023
Summary
CVE-2023-39357 is a high-severity Improper Input Validation (CWE-20) vulnerability in Fedoraproject Fedora. Its CVSS base score is 8.8 (High).
Operationally, ranked in the top 11.5% 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-2023-43083
Vulnerability details
Cacti is an open source operational monitoring and fault management framework. A defect in the sql_save function was discovered. When the column type is numeric, the sql_save function directly utilizes user input. Many files and functions calling the sql_save function…
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do not perform prior validation of user input, leading to the existence of multiple SQL injection vulnerabilities in Cacti. This allows authenticated users to exploit these SQL injection vulnerabilities to perform privilege escalation and remote code execution. This issue has been addressed in version 1.2.25. Users are advised to upgrade. There are no known workarounds for this vulnerability.
- 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.
Penetration testing uses SQL injection payloads against database interfaces, identifying and supporting fixes for SQL injection weaknesses.
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.