FKIE_CVE-2026-9617

Vulnerability from fkie_nvd - Published: 2026-05-27 14:17 - Updated: 2026-06-02 00:40
Summary
PostgreSQL Anonymizer contains a vulnerability that allows a user to gain superuser privileges by creating a table and placing malicious code inside a column identifier. If a superuser calls the k-anonymity function, the malicious code is executed with superuser privileges. The risk is higher with PostgreSQL 14 or with instances upgraded from PostgreSQL 14 or a prior version. With PostgreSQL 15 and later, the creation permission on the public schema is revoked by default and this exploit can only be achieved by a user who was explicitly granted the CREATE TABLE privilege. The problem is resolved in PostgreSQL Anonymizer 3.1.0 and further versions
References
Impacted products
Vendor Product Version
dalibo anonymizer 2.5.1

{
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:dalibo:anonymizer:2.5.1:*:*:*:*:postgresql:*:*",
              "matchCriteriaId": "6BF4BD78-55DD-4319-B426-B356673BD381",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "PostgreSQL Anonymizer contains a vulnerability that allows a user to gain superuser privileges by creating a table and placing malicious code inside a column identifier. If a superuser calls the k-anonymity function, the malicious code is executed with superuser privileges. The risk is higher with PostgreSQL 14 or with instances upgraded from PostgreSQL 14 or a prior version. With PostgreSQL 15 and later, the creation permission on the public schema is revoked by default and this exploit can only be achieved by a user who was explicitly granted the CREATE TABLE privilege. The problem is resolved in PostgreSQL Anonymizer 3.1.0 and further versions"
    }
  ],
  "id": "CVE-2026-9617",
  "lastModified": "2026-06-02T00:40:18.397",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 6.8,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "HIGH",
          "scope": "UNCHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:U/C:H/I:H/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 0.9,
        "impactScore": 5.9,
        "source": "f86ef6dc-4d3a-42ad-8f28-e6d5547a5007",
        "type": "Secondary"
      },
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 8.8,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "LOW",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 2.8,
        "impactScore": 5.9,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ]
  },
  "published": "2026-05-27T14:17:40.273",
  "references": [
    {
      "source": "f86ef6dc-4d3a-42ad-8f28-e6d5547a5007",
      "tags": [
        "Exploit",
        "Third Party Advisory",
        "Issue Tracking"
      ],
      "url": "https://gitlab.com/dalibo/postgresql_anonymizer/-/issues/640"
    }
  ],
  "sourceIdentifier": "f86ef6dc-4d3a-42ad-8f28-e6d5547a5007",
  "vulnStatus": "Analyzed",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-89"
        }
      ],
      "source": "f86ef6dc-4d3a-42ad-8f28-e6d5547a5007",
      "type": "Secondary"
    }
  ]
}


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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.
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