CVE-2022-37346 (GCVE-0-2022-37346)

Vulnerability from cvelistv5 – Published: 2022-09-27 01:55 – Updated: 2025-05-21 18:25
VLAI
Summary
EC-CUBE plugin 'Product Image Bulk Upload Plugin' 1.0.0 and 4.1.0 contains an insufficient verification vulnerability when uploading files. Exploiting this vulnerability allows a remote unauthenticated attacker to upload arbitrary files other than image files. If a user with an administrative privilege of EC-CUBE where the vulnerable plugin is installed is led to upload a specially crafted file, an arbitrary script may be executed on the system.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-05-21 18:25 UTC
CWE
  • Improper input validation
  • CWE-434 - Unrestricted Upload of File with Dangerous Type
References
Impacted products
Vendor Product Version CPE status
EC-CUBE CO.,LTD. Product Image Bulk Upload Plugin Affected: 1.0.0 and 4.1.0
guessed Create a notification for this product.
Show details on NVD website

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                  "value": "EC-CUBE plugin \u0027Product Image Bulk Upload Plugin\u0027 1.0.0 and 4.1.0 contains an insufficient verification vulnerability when uploading files. Exploiting this vulnerability allows a remote unauthenticated attacker to upload arbitrary files other than image files. If a user with an administrative privilege of EC-CUBE where the vulnerable plugin is installed is led to upload a specially crafted file, an arbitrary script may be executed on the system."
                }
              ]
            },
            "problemtype": {
              "problemtype_data": [
                {
                  "description": [
                    {
                      "lang": "eng",
                      "value": "Improper input validation"
                    }
                  ]
                }
              ]
            },
            "references": {
              "reference_data": [
                {
                  "name": "https://www.ec-cube.net/info/weakness/20220909/product_images_uploader.php",
                  "refsource": "MISC",
                  "url": "https://www.ec-cube.net/info/weakness/20220909/product_images_uploader.php"
                },
                {
                  "name": "https://jvn.jp/en/jp/JVN30900552/index.html",
                  "refsource": "MISC",
                  "url": "https://jvn.jp/en/jp/JVN30900552/index.html"
                }
              ]
            }
          }
        }
      },
      "cveMetadata": {
        "assignerOrgId": "ede6fdc4-6654-4307-a26d-3331c018e2ce",
        "assignerShortName": "jpcert",
        "cveId": "CVE-2022-37346",
        "datePublished": "2022-09-27T01:55:15.000Z",
        "dateReserved": "2022-09-09T00:00:00.000Z",
        "dateUpdated": "2025-05-21T18:25:42.293Z",
        "state": "PUBLISHED"
      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.1"
    }
  }
}



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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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