CVE-2023-25165
Published: 08 February 2023
Summary
CVE-2023-25165 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Helm Helm. Its CVSS base score is 4.3 (Medium).
Operationally, ranked at the 42.0th 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-2023-0766
Vulnerability details
Helm is a tool that streamlines installing and managing Kubernetes applications.`getHostByName` is a Helm template function introduced in Helm v3. The function is able to accept a hostname and return an IP address for that hostname. To get the IP…
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address the function performs a DNS lookup. The DNS lookup happens when used with `helm install|upgrade|template` or when the Helm SDK is used to render a chart. Information passed into the chart can be disclosed to the DNS servers used to lookup the IP address. For example, a malicious chart could inject `getHostByName` into a chart in order to disclose values to a malicious DNS server. The issue has been fixed in Helm 3.11.1. Prior to using a chart with Helm verify the `getHostByName` function is not being used in a template to disclose any information you do not want passed to DNS servers.
- 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.