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GHSA-6C35-RP78-P585

Vulnerability from github – Published: 2026-08-10 15:33 – Updated: 2026-08-10 15:33
VLAI
Details

An improper authorization vulnerability in Attendize through commit 9289acb allows an authenticated remote attacker to inject persistent mandatory survey questions into another organizer's events via the POST /event/{event_id}/question/create endpoint. The postCreateEventQuestion method loads the target event without the tenant-isolation scope, enabling cross-tenant writes; the injected question cannot be removed by the victim because the victim's account-scoped delete path cannot resolve a question owned by another tenant.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-72690"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-639"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-10T13:20:39Z",
    "severity": "HIGH"
  },
  "details": "An improper authorization vulnerability in Attendize through commit 9289acb allows an authenticated remote attacker to inject persistent mandatory survey questions into another organizer\u0027s events via the POST /event/{event_id}/question/create endpoint. The postCreateEventQuestion method loads the target event without the tenant-isolation scope, enabling cross-tenant writes; the injected question cannot be removed by the victim because the victim\u0027s account-scoped delete path cannot resolve a question owned by another tenant.",
  "id": "GHSA-6c35-rp78-p585",
  "modified": "2026-08-10T15:33:51Z",
  "published": "2026-08-10T15:33:51Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-72690"
    },
    {
      "type": "WEB",
      "url": "https://github.com/Attendize/Attendize"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/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.

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