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GHSA-QC8H-H7C3-V2GH

Vulnerability from github – Published: 2026-09-06 12:30 – Updated: 2026-09-06 12:30
VLAI
Details

wger versions through master contain an incomplete authorization bypass in wger/core/views/user.py where three views retain the original gym-scope check using raw integer comparison instead of the is_same_gym() helper, allowing gym staff with gym=None to delete, deactivate, or activate any other user with gym=None. Attackers with gym.manage_gym permission and gym=None affiliation can permanently delete user accounts, lock users out via deactivation, or undo defensive deactivations by exploiting the None != None comparison edge case.

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{
  "affected": [],
  "aliases": [
    "CVE-2026-86254"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-862"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-09-06T12:17:16Z",
    "severity": "MODERATE"
  },
  "details": "wger versions through master contain an incomplete authorization bypass in wger/core/views/user.py where three views retain the original gym-scope check using raw integer comparison instead of the is_same_gym() helper, allowing gym staff with gym=None to delete, deactivate, or activate any other user with gym=None. Attackers with gym.manage_gym permission and gym=None affiliation can permanently delete user accounts, lock users out via deactivation, or undo defensive deactivations by exploiting the None != None comparison edge case.",
  "id": "GHSA-qc8h-h7c3-v2gh",
  "modified": "2026-09-06T12:30:24Z",
  "published": "2026-09-06T12:30:24Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/wger-project/wger/security/advisories/GHSA-mw8f-w6p8-xrf4"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-86254"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/wger-incomplete-authorization-fix-cross-tenant-account-deletion"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:H/AT:P/PR:L/UI:N/VC:N/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
      "type": "CVSS_V4"
    }
  ]
}



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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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