CVE-2023-23613
Published: 26 January 2023
Summary
CVE-2023-23613 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Amazon Opensearch. Its CVSS base score is 5.7 (Medium).
Operationally, ranked in the top 41.9% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0551
Vulnerability details
OpenSearch is an open source distributed and RESTful search engine. In affected versions there is an issue in the implementation of field-level security (FLS) and field masking where rules written to explicitly exclude fields are not correctly applied for certain…
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queries that rely on their auto-generated .keyword fields. This issue is only present for authenticated users with read access to the indexes containing the restricted fields. This may expose data which may otherwise not be accessible to the user. OpenSearch 1.0.0-1.3.7 and 2.0.0-2.4.1 are affected. Users are advised to upgrade to OpenSearch 1.3.8 or 2.5.0. Users unable to upgrade may write explicit exclusion rules as a workaround. Policies authored in this way are not subject to this issue.
- 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.