CVE-2025-30222
Published: 25 March 2025
Summary
CVE-2025-30222 is a low-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability. Its CVSS base score is 2.1 (Low).
Operationally, ranked at the 28.4th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-8207
Vulnerability details
Shescape is a simple shell escape library for JavaScript. Versions 1.7.2 through 2.1.1 are vulnerable to potential environment variable exposure on Windows with CMD. This impact users of Shescape on Windows that explicitly configure `shell: 'cmd.exe'` or `shell: true` using…
more
any of `quote`/`quoteAll`/`escape`/`escapeAll`. An attacker may be able to get read-only access to environment variables. This bug has been patched in v2.1.2. For those who are already using v2 of Shescape, no further changes are required. Those who are are using v1 of Shescape should follow the migration guide to upgrade to v2. There is no plan to release a patch compatible with v1 of Shescape. As a workaround, users can remove all instances of `%` from user input before using Shescape.
- 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.