CVE-2021-41109
Published: 30 September 2021
Summary
CVE-2021-41109 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Parseplatform Parse-Server. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 41.3% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2021-2005
Vulnerability details
Parse Server is an open source backend that can be deployed to any infrastructure that can run Node.js. Prior to version 4.10.4, for regular (non-LiveQuery) queries, the session token is removed from the response, but for LiveQuery payloads it is…
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currently not. If a user has a LiveQuery subscription on the `Parse.User` class, all session tokens created during user sign-ups will be broadcast as part of the LiveQuery payload. A patch in version 4.10.4 removes session tokens from the LiveQuery payload. As a workaround, set `user.acl(new Parse.ACL())` in a beforeSave trigger to make the user private already on sign-up.
- 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.