CVE-2023-39951
Published: 08 August 2023
Summary
CVE-2023-39951 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Linuxfoundation Opentelemetry Instrumentation For Java. Its CVSS base score is 6.5 (Medium).
Operationally, ranked at the 48.2th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-43649
Vulnerability details
OpenTelemetry Java Instrumentation provides OpenTelemetry auto-instrumentation and instrumentation libraries for Java. OpenTelemetry Java Instrumentation prior to version 1.28.0 contains an issue related to the instrumentation of Java applications using the AWS SDK v2 with Amazon Simple Email Service (SES) v1…
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API. When SES POST requests are instrumented, the query parameters of the request are inserted into the trace `url.path` field. This behavior leads to the http body, containing the email subject and message, to be present in the trace request url metadata. Any user using a version before 1.28.0 of OpenTelemetry Java Instrumentation to instrument AWS SDK v2 call to SES’s v1 SendEmail API is affected. The e-mail content sent to SES may end up in telemetry backend. This exposes the e-mail content to unintended audiences. The issue can be mitigated by updating OpenTelemetry Java Instrumentation to version 1.28.0 or later.
- 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.