GHSA-5QMG-PGG7-3RJJ

Vulnerability from github – Published: 2026-08-10 21:32 – Updated: 2026-08-11 21:32
VLAI
Details

A flaw was found in the Data Science Pipelines Operator. This vulnerability allows an unauthenticated attacker to derive sensitive credentials, such as MariaDB root/user passwords and MinIO access/secret keys, if they can access the MinIO Route or MariaDB Service. The flaw occurs because the operator uses a cryptographically weak pseudo-random number generator (PRNG) to generate these credentials, making them predictable. Successful exploitation could lead to unauthorized access to all pipeline artifacts and metadata, resulting in significant information disclosure.

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{
  "affected": [],
  "aliases": [
    "CVE-2026-18611"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-338"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-10T21:17:20Z",
    "severity": "HIGH"
  },
  "details": "A flaw was found in the Data Science Pipelines Operator. This vulnerability allows an unauthenticated attacker to derive sensitive credentials, such as MariaDB root/user passwords and MinIO access/secret keys, if they can access the MinIO Route or MariaDB Service. The flaw occurs because the operator uses a cryptographically weak pseudo-random number generator (PRNG) to generate these credentials, making them predictable. Successful exploitation could lead to unauthorized access to all pipeline artifacts and metadata, resulting in significant information disclosure.",
  "id": "GHSA-5qmg-pgg7-3rjj",
  "modified": "2026-08-11T21:32:32Z",
  "published": "2026-08-10T21:32:06Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-18611"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/errata/RHSA-2026:53261"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/errata/RHSA-2026:53262"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/errata/RHSA-2026:53263"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/security/cve/CVE-2026-18611"
    },
    {
      "type": "WEB",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2510299"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}



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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.

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Nomenclature

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