Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2022-26133 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Atlassian Bitbucket Data Center. Its CVSS base score is 9.8 (Critical).
Operationally, ranked in the top 0.7% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and SI-2 (Flaw Remediation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2022-26133 is a Java deserialization vulnerability (CWE-502) in the SharedSecretClusterAuthenticator component of Atlassian Bitbucket Data Center. It affects versions 5.14.0 and later before 7.6.14, 7.7.0 and later prior to 7.17.6, 7.18.0 and later prior to 7.18.4, 7.19.0 and later prior to 7.19.4, and 7.20.0. The flaw carries a CVSS 3.1 score of 9.8 and stems from unsafe handling of serialized objects, commonly tied to an embedded Hazelcast instance.
A remote unauthenticated attacker can send a crafted serialized payload over the network to trigger arbitrary code execution on the Bitbucket server, achieving full confidentiality, integrity, and availability impact without any user interaction or credentials.
Atlassian security advisories reference the underlying Hazelcast issue (CVE-2016-10750) and direct administrators to upgrade Bitbucket Data Center to one of the fixed releases listed in the Jira ticket BSERV-13173; the advisories also recommend reviewing cluster authentication configurations and applying vendor patches promptly. The EPSS score has reached 0.8139, indicating substantial exploitation interest.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-30700
Vulnerability Data
SharedSecretClusterAuthenticator in Atlassian Bitbucket Data Center versions 5.14.0 and later before 7.6.14, 7.7.0 and later prior to 7.17.6, 7.18.0 and later prior to 7.18.4, 7.19.0 and later prior to 7.19.4, and 7.20.0 allow a remote, unauthenticated attacker to execute arbitrary…
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code via Java deserialization.
- CWE(s)
Related Threats
Likely ATT&CK TechniquesAI
Techniques this vulnerability likely enables, inferred from its description, weakness type, and attributed-actor tradecraft. Confidence is per-technique.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly blocks the crafted serialized object input that triggers arbitrary code execution in SharedSecretClusterAuthenticator.
Requires prompt application of the vendor patches listed in BSERV-13173 that eliminate the unsafe deserialization path.
Restricts network exposure of the Hazelcast/Bitbucket cluster ports used to deliver the unauthenticated serialized payload.
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.
PR.PS-02 addresses only post-deployment updates/patching and cannot prevent introduction of unsafe deserialization code, yet it can remediate some instances when the flaw exists in outdated libraries or components.
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.
Security testing includes validation of deserialization routines and the use of untrusted data, reducing the likelihood that unsafe object reconstruction will be deployed.
Requiring vetted libraries, regular updates and SAST before release reduces the likelihood that deserialization logic will accept and act on attacker-controlled serialized objects.
Regular scanning of third-party libraries and timely patching reduce the likelihood that unsafe deserialization vulnerabilities remain active.
Mandatory malware scanning of data received over networks or storage media intercepts malicious serialized payloads before they are deserialized by the target application.