CVE-2026-33981
Published: 27 March 2026
Summary
CVE-2026-33981 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Webtechnologies Changedetection. Its CVSS base score is 8.3 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Unsecured Credentials (T1552); ranked at the 37.4th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-16880
Vulnerability details
changedetection.io is a free open source web page change detection tool. Prior to 0.54.7, the `jq:` and `jqraw:` include filter expressions allow use of the jq `env` builtin, which reads all process environment variables and stores them as the watch…
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snapshot. An authenticated user (or unauthenticated user when no password is set, the default) can leak sensitive environment variables including `SALTED_PASS`, `PLAYWRIGHT_DRIVER_URL`, `HTTP_PROXY`, and any secrets passed as env vars to the container. Version 0.54.7 patches the issue.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Vulnerability directly enables extraction of credentials/secrets stored in process environment variables via crafted filter expressions.
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.