GCVE Workshop - 22 September 2026 (14:00-18:00), Luxembourg Before The Vulnopticon Conference - Registration

FKIE_CVE-2023-31300

Vulnerability from fkie_nvd - Published: 2023-12-29 06:15 - Updated: 2026-06-17 05:56
Summary
An issue was discovered in Sesami Cash Point & Transport Optimizer (CPTO) version 6.3.8.6 (#718), allows remote attackers to obtain sensitive information via transmission of unencrypted, cleartext credentials during Password Reset feature.
Impacted products
Vendor Product Version
sesami cash_point_\&_transport_optimizer 6.3.8.6.718

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "n/a",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "n/a"
            }
          ]
        }
      ],
      "source": "cve@mitre.org"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:sesami:cash_point_\\\u0026_transport_optimizer:6.3.8.6.718:*:*:*:*:*:*:*",
              "matchCriteriaId": "1FF8F540-DE41-4C35-BA23-64A08F2474E7",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "An issue was discovered in Sesami Cash Point \u0026 Transport Optimizer (CPTO) version 6.3.8.6 (#718), allows remote attackers to obtain sensitive information via transmission of unencrypted, cleartext credentials during Password Reset feature."
    },
    {
      "lang": "es",
      "value": "Se descubri\u00f3 un problema en Sesami Cash Point \u0026amp; Transport Optimizer (CPTO) versi\u00f3n 6.3.8.6 (#718), que permite a atacantes remotos obtener informaci\u00f3n confidencial mediante la transmisi\u00f3n de credenciales de texto plano y sin cifrar durante la funci\u00f3n de Password Reset."
    }
  ],
  "id": "CVE-2023-31300",
  "lastModified": "2026-06-17T05:56:45.480",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 7.5,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 3.6,
        "source": "nvd@nist.gov",
        "type": "Primary"
      },
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 7.5,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 3.6,
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2023-31300",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "yes"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2024-01-03T16:29:06.096732Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2023-12-29T06:15:43.633",
  "references": [
    {
      "source": "cve@mitre.org",
      "tags": [
        "Third Party Advisory"
      ],
      "url": "https://herolab.usd.de/en/security-advisories/usd-2022-0057/"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Third Party Advisory"
      ],
      "url": "https://herolab.usd.de/en/security-advisories/usd-2022-0057/"
    }
  ],
  "sourceIdentifier": "cve@mitre.org",
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-319"
        }
      ],
      "source": "nvd@nist.gov",
      "type": "Primary"
    },
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-319"
        }
      ],
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "type": "Secondary"
    }
  ]
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…

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.


Loading…