Raw vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-22307 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Tribe29 Checkmk Appliance Firmware. Its CVSS base score is 5.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique NTDS (T1003.003); ranked at the 12th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-26470
Vulnerability Data
Sensitive data exposure in Webconf in Tribe29 Checkmk Appliance before 1.6.4 allows local attacker to retrieve passwords via reading log files.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V14.2.1
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.
Controls whether organization resources are exposed to external system spheres by permitting or prohibiting their use.
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.
Documenting information locations and authorized users enables better protection against unauthorized exposure of sensitive data.
Media marking ensures sensitive information on removable or system media is handled according to its classification, reducing the chance of inadvertent exposure to unauthorized actors.
Protecting and controlling media during external transport prevents exposure of sensitive information to unauthorized actors.
Assessing control effectiveness and providing incident communication channels at alternate sites reduces the likelihood of sensitive information exposure to unauthorized actors.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
HTTPS encryption protects query strings in transit but does not address the root design flaw of placing sensitive data in URLs.
Secure SDLC practices directly prevent embedding sensitive data in query strings as part of input-handling and data-flow design.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
A.5.10 only requires awareness, a topic-specific acceptable-use policy stating expected behaviours/monitoring, and procedures referencing classification and other controls; per the owner's explicit rule on labelling and similar dependency-style clauses, this does not itself prevent exposure (CWE-200) unless access/DLP/etc. act on it.
Requiring the return of all physical and electronic assets plus secure deletion of organizational data from personal devices reduces the chance that sensitive information remains accessible to departing personnel.
A.5.12 only defines and communicates a classification scheme so that protection needs can be understood; per the owner's explicit rule, labeling/classification does not itself prevent exposure and requires other controls (e.g. access enforcement) to act on it.
By requiring classification labels and metadata on all information assets, the control makes it harder for sensitive data to be inadvertently exposed because downstream systems and users can recognize and enforce handling rules based on those labels.
Requiring encryption, access controls, and recipient authentication for transfers directly reduces the chance that sensitive data reaches an unauthorized observer.
Secure delivery, protected storage, and confidentiality of allocation records limit exposure of authentication material to unauthorized observers.
Hardening callouts derived
DISA STIG baselines are authored against specific weaknesses. Where this CVE cites a broad weakness class, the mapping is not asserted at that abstraction (owner ruling, 2026-09-25: grade only at Base and below), so no rule is shown here rather than a rule shown against the wrong grain.