CVE-2026-65316 (GCVE-0-2026-65316)
Vulnerability from cvelistv5 – Published: 2026-07-21 21:23 – Updated: 2026-09-24 14:18
VLAI
EPSS
VEX
Title
xxl-job Cross-Job-Group Log Disclosure via Missing Authorization Check in /joblog/logDetailCat
Summary
XXL-Job version 2.4.2 contains an insecure direct object reference vulnerability that allows authenticated users to read execution log content from job groups they are not authorized to access by supplying arbitrary sequential log IDs to the logDetailCat endpoint. Attackers can enumerate log records across all job groups by calling the logDetailCat endpoint with incremented logId parameter values, bypassing the permission check present in the sibling logDetailPage endpoint, and retrieve sensitive log content from restricted job groups.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-07-23 18:29 UTC
CWE
- CWE-639 - Authorization Bypass Through User-Controlled Key
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/xuxueli/xxl-job/issues/3983 | issue-tracking |
| https://github.com/xuxueli/xxl-job | product |
| https://www.vulncheck.com/advisories/xxl-job-cros… | third-party-advisory |
Impacted products
Date Public
2026-07-21 00:00
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Sightings
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|---|
Nomenclature
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
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The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.