CVE-2024-12677 (GCVE-0-2024-12677)

Vulnerability from cvelistv5 – Published: 2024-12-20 16:44 – Updated: 2024-12-24 00:40
VLAI
Title
Delta Electronics DTM Soft Deserialization of Untrusted Data
Summary
Delta Electronics DTM Soft deserializes objects, which could allow an attacker to execute arbitrary code.
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-12-24 00:32 UTC
CWE
  • CWE-502 - Deserialization of Untrusted Data
Impacted products
Vendor Product Version CPE status
Delta Electronics DTM Soft Affected: 0 , ≤ 1.30 (custom)
guessed Create a notification for this product.
Show details on NVD website

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        "dateReserved": "2024-12-16T16:10:03.698Z",
        "dateUpdated": "2024-12-24T00:40:13.881Z",
        "state": "PUBLISHED"
      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.1"
    }
  }
}



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Tags
Taxonomy of the tags.


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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

Author Source Type Date Other

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.

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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.


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