CVE-2019-25210
Published: 03 March 2024
Summary
CVE-2019-25210 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Helm Helm. Its CVSS base score is 6.5 (Medium).
Operationally, ranked at the 38.1th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-0953
Vulnerability details
An issue was discovered in Cloud Native Computing Foundation (CNCF) Helm through 3.13.3. It displays values of secrets when the --dry-run flag is used. This is a security concern in some use cases, such as a --dry-run call by a…
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CI/CD tool. NOTE: the vendor's position is that this behavior was introduced intentionally, and cannot be removed without breaking backwards compatibility (some users may be relying on these values). Also, it is not the Helm Project's responsibility if a user decides to use --dry-run within a CI/CD environment whose output is visible to unauthorized persons.
- 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.