CVE-2024-21685
Published: 18 June 2024
Summary
CVE-2024-21685 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Atlassian Jira Data Center. Its CVSS base score is 6.5 (Medium).
Operationally, ranked in the top 22.8% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-19301
Vulnerability details
This High severity Information Disclosure vulnerability was introduced in versions 9.4.0, 9.12.0, and 9.15.0 of Jira Core Data Center. This Information Disclosure vulnerability, with a CVSS Score of 7.4, allows an unauthenticated attacker to view sensitive information via an Information…
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Disclosure vulnerability which has high impact to confidentiality, no impact to integrity, no impact to availability, and requires user interaction. Atlassian recommends that Jira Core Data Center customers upgrade to latest version, if you are unable to do so, upgrade your instance to one of the specified supported fixed versions: Jira Core Data Center 9.4: Upgrade to a release greater than or equal to 9.4.21 Jira Core Data Center 9.12: Upgrade to a release greater than or equal to 9.12.8 Jira Core Data Center 9.16: Upgrade to a release greater than or equal to 9.16.0 See the release notes. You can download the latest version of Jira Core Data Center from the download center. This vulnerability was found internally.
- 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.