CVE-2022-24725
Published: 03 March 2022
Summary
CVE-2022-24725 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Shescape Project Shescape. Its CVSS base score is 6.2 (Medium).
Operationally, ranked in the top 46.7% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-1297
Vulnerability details
Shescape is a shell escape package for JavaScript. An issue in versions 1.4.0 to 1.5.1 allows for exposure of the home directory on Unix systems when using Bash with the `escape` or `escapeAll` functions from the _shescape_ API with the…
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`interpolation` option set to `true`. Other tested shells, Dash and Zsh, are not affected. Depending on how the output of _shescape_ is used, directory traversal may be possible in the application using _shescape_. The issue was patched in version 1.5.1. As a workaround, manually escape all instances of the tilde character (`~`) using `arg.replace(/~/g, "\\~")`.
- 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.