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CVE-2026-41862 (GCVE-0-2026-41862)

Vulnerability from cvelistv5 – Published: 2026-06-23 20:59 – Updated: 2026-06-24 15:24
VLAI
Summary
Spring Statemachine's Kryo-based persistence backends (JPA, MongoDB, Redis and ZooKeeper) deserialise persisted state-machine contexts without enforcing a class allowlist (CWE-502, deserialisation of untrusted data), which can lead to remote code execution inside the application JVM. Affected versions: Spring Statemachine 4.0.0 through 4.0.1 Spring Statemachine 3.2.0 through 3.2.4
Severity
8.8 (High)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-24 15:24 UTC
CWE
  • CWE-502 - Deserialization of Untrusted Data
Assigner
References
Impacted products
Vendor Product Version CPE status
Spring Spring Statemachine Affected: 4.0.0 , < 4.0.1.1 (custom)
Affected: 3.2.0 , < 3.2.5 (custom)
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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

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Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.


Detection rules are retrieved from Rulezet.


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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.