CVE-2022-31711
Published: 26 January 2023
Summary
CVE-2022-31711 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Vmware Vrealize Log Insight. Its CVSS base score is 5.3 (Medium).
Operationally, ranked in the top 0.8% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
Deeper analysis
VMware vRealize Log Insight contains an information disclosure vulnerability, CVE-2022-31711, that permits remote collection of sensitive session and application information. The affected component is the VMware vRealize Log Insight product, and the issue carries a CVSS 3.1 base score of 5.3 with the vector AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N along with CWE-200 classification.
An unauthenticated attacker with network access can exploit the flaw to obtain limited confidential data without any user interaction or privileges. The attack requires no authentication and results solely in information exposure rather than integrity or availability impact.
The referenced VMware advisory VMSA-2023-0001 addresses the vulnerability, while additional public disclosures discuss related exploitation techniques against the product. The EPSS score has remained at a peak of 0.8241 with no material change from a lower baseline.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-53130
Vulnerability details
VMware vRealize Log Insight contains an Information Disclosure Vulnerability. A malicious actor can remotely collect sensitive session and application information without authentication.
- 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.
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.