CVE-2024-28188
Published: 23 May 2024
Summary
CVE-2024-28188 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability. Its CVSS base score is 5.3 (Medium).
Operationally, ranked at the 39.4th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-1797
Vulnerability details
Jupyter Scheduler is collection of extensions for programming jobs to run now or run on a schedule. The list of conda environments of `jupyter-scheduler` users maybe be exposed, potentially revealing information about projects that a specific user may be working…
more
on. This vulnerability has been patched in version(s) 1.1.6, 1.2.1, 1.8.2 and 2.5.2.
- 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.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Session auditing enables detection of unauthorized exposure or access to sensitive information during user activities.
Audit record review and analysis can detect unauthorized exposure or access to sensitive information.
Penetration testing probes authentication mechanisms for bypasses, allowing identification and fixing of improper authentication issues.
The integrated analysis team enables faster detection and containment of incidents involving unauthorized exposure of sensitive information, limiting attacker success in exploiting such weaknesses.
Security architectures must specify authentication requirements and approaches, making systemic authentication weaknesses harder to introduce.
Trained staff understand data-handling requirements and are less likely to expose sensitive information through misconfiguration or poor design.
Hunting detects anomalous authentication patterns or successful bypasses that allow persistent unauthorized entry.