CVE-2024-37150
Published: 06 June 2024
Summary
CVE-2024-37150 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Deno Deno. Its CVSS base score is 7.6 (High).
Operationally, ranked in the top 36.0% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-36466
Vulnerability details
An issue in `.npmrc` support in Deno 1.44.0 was discovered where Deno would send `.npmrc` credentials for the scope to the tarball URL when the registry provided URLs for a tarball on a different domain. All users relying on .npmrc…
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are potentially affected by this vulnerability if their private registry references tarball URLs at a different domain. This includes usage of deno install subcommand, auto-install for npm: specifiers and LSP usage. It is recommended to upgrade to Deno 1.44.1 and if your private registry ever serves tarballs at a different domain to rotate your registry credentials.
- 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.