CVE-2020-21642 (GCVE-0-2020-21642)

Vulnerability from cvelistv5 – Published: 2022-08-15 19:10 – Updated: 2024-08-04 14:30
VLAI
Summary
Directory Traversal vulnerability ZDBQAREFSUBDIR parameter in /zropusermgmt API in Zoho ManageEngine Analytics Plus before 4350 allows remote attackers to run arbitrary code.
CWE
  • n/a
References
Show details on NVD website

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                "negate": false,
                "operator": "OR"
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            ]
          }
        ],
        "cveTags": [],
        "descriptions": [
          {
            "lang": "en",
            "value": "Directory Traversal vulnerability ZDBQAREFSUBDIR parameter in /zropusermgmt API in Zoho ManageEngine Analytics Plus before 4350 allows remote attackers to run arbitrary code."
          },
          {
            "lang": "es",
            "value": "Una vulnerabilidad de Salto de Directorio en el par\u00e1metro ZDBQAREFSUBDIR en la API /zropusermgmt en Zoho ManageEngine Analytics Plus versiones anteriores a 4350, permite a atacantes remotos ejecutar c\u00f3digo arbitrario."
          }
        ],
        "id": "CVE-2020-21642",
        "lastModified": "2024-11-21T05:12:44.610",
        "metrics": {
          "cvssMetricV31": [
            {
              "cvssData": {
                "attackComplexity": "LOW",
                "attackVector": "NETWORK",
                "availabilityImpact": "HIGH",
                "baseScore": 9.8,
                "baseSeverity": "CRITICAL",
                "confidentialityImpact": "HIGH",
                "integrityImpact": "HIGH",
                "privilegesRequired": "NONE",
                "scope": "UNCHANGED",
                "userInteraction": "NONE",
                "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
                "version": "3.1"
              },
              "exploitabilityScore": 3.9,
              "impactScore": 5.9,
              "source": "nvd@nist.gov",
              "type": "Primary"
            }
          ]
        },
        "published": "2022-08-15T20:15:08.970",
        "references": [
          {
            "source": "cve@mitre.org",
            "tags": [
              "Release Notes",
              "Vendor Advisory"
            ],
            "url": "https://www.manageengine.com/analytics-plus/release-notes.html"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
              "Release Notes",
              "Vendor Advisory"
            ],
            "url": "https://www.manageengine.com/analytics-plus/release-notes.html"
          }
        ],
        "sourceIdentifier": "cve@mitre.org",
        "vulnStatus": "Modified",
        "weaknesses": [
          {
            "description": [
              {
                "lang": "en",
                "value": "CWE-22"
              }
            ],
            "source": "nvd@nist.gov",
            "type": "Primary"
          }
        ]
      }
    }
  }
}



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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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