CVE-2022-36079
Published: 07 September 2022
Summary
CVE-2022-36079 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Parseplatform Parse-Server. Its CVSS base score is 8.6 (High).
Operationally, ranked in the top 30.2% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-6666
Vulnerability details
Parse Server is an open source backend that can be deployed to any infrastructure that can run Node.js. Internal fields (keys used internally by Parse Server, prefixed by `_`) and protected fields (user defined) can be used as query constraints.…
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Internal and protected fields are removed by Parse Server and are only returned to the client using a valid master key. However, using query constraints, these fields can be guessed by enumerating until Parse Server, prior to versions 4.10.14 or 5.2.5, returns a response object. The patch available in versions 4.10.14 and 5.2.5 requires the maser key to use internal and protected fields as query constraints. As a workaround, implement a Parse Cloud Trigger `beforeFind` and manually remove the query constraints.
- 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.