GHSA-84VG-9R54-XPGH

Vulnerability from github – Published: 2026-08-05 09:31 – Updated: 2026-08-05 09:31
VLAI
Details

changedetection.io's /settings save handler builds an update dict from form.data['application'] and blind-merges it into the stored application settings via .update(). Because WTForms represents an unchecked checkbox as False rather than 'unchanged', and only the 'password' field is special-cased against this problem, a POST to /settings that omits the api_access_token_enabled field (e.g. a minimal scripted request) silently disables API key enforcement for the entire REST API, exposing the full watch list, history, and configuration to unauthenticated requests.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-71204"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-284"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-05T08:16:42Z",
    "severity": "MODERATE"
  },
  "details": "changedetection.io\u0027s /settings save handler builds an update dict from form.data[\u0027application\u0027] and blind-merges it into the stored application settings via .update(). Because WTForms represents an unchecked checkbox as False rather than \u0027unchanged\u0027, and only the \u0027password\u0027 field is special-cased against this problem, a POST to /settings that omits the api_access_token_enabled field (e.g. a minimal scripted request) silently disables API key enforcement for the entire REST API, exposing the full watch list, history, and configuration to unauthenticated requests.",
  "id": "GHSA-84vg-9r54-xpgh",
  "modified": "2026-08-05T09:31:18Z",
  "published": "2026-08-05T09:31:18Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-71204"
    },
    {
      "type": "WEB",
      "url": "https://github.com/dgtlmoon/changedetection.io"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:H/UI:N/S:U/C:H/I:H/A:L",
      "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.

Sightings

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Nomenclature

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