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CVE-2025-40807 (GCVE-0-2025-40807)

Vulnerability from cvelistv5 – Published: 2025-12-09 10:44 – Updated: 2025-12-09 16:43
VLAI
Summary
A vulnerability has been identified in Gridscale X Prepay (All versions < V4.2.1). The affected application is vulnerable to capture-replay of authentication tokens. This could allow an authenticated but already locked-out user to establish still valid user sessions.
Severity
6.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L
5.3 (Medium)
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-12-09 16:43 UTC
CWE
  • CWE-294 - Authentication Bypass by Capture-replay
Assigner
References
Impacted products
Vendor Product Version CPE status
Siemens Gridscale X Prepay Affected: 0 , < V4.2.1 (custom)
guessed Create a notification for this product.
Show details on NVD website
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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.