CVE-2026-42782 (GCVE-0-2026-42782)
Vulnerability from cvelistv5 – Published: 2026-05-25 14:58 – Updated: 2026-05-27 20:31
VLAI
EPSS
VEX
Title
Apache Syncope: Post-auth RCE via Groovy static
Summary
Improper Isolation or Compartmentalization vulnerability in Apache Syncope.
An administrator with adequate entitlements for Implementations can create a malicious Groovy class containing untrusted code reaching a non-sandboxed execution path via the class static initializer.
This issue affects Apache Syncope: 3.0 through 3.0.16, 4.0 through 4.0.5, 4.1.0.
Users are recommended to upgrade to version 4.0.6 / 4.1.1, which fix this issue by forcing even the static initializer in Groovy code to run in a sandbox.
Severity
7.2 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-05-27 20:31 UTC
CWE
- CWE-653 - Improper Isolation or Compartmentalization
Assigner
References
2 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Apache Software Foundation | Apache Syncope |
Affected:
3.0 , ≤ 3.0.16
(semver)
Affected: 4.0 , ≤ 4.0.5 (semver) Affected: 4.1 , ≤ 4.1.0 (semver) |
guessed |
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Sightings
| Author | Source | Type | Date | Other |
|---|
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
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
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.