GHSA-G6R6-JR7G-HG95

Vulnerability from github – Published: 2026-08-03 18:30 – Updated: 2026-08-03 18:30
VLAI
Details

OpenEMR through 8.2.0 contains an authentication bypass vulnerability that allows attackers with valid credentials to circumvent multi-factor authentication by exploiting the exposed OAuth2 password grant flow through an unauthenticated client registration endpoint. Attackers can register an OAuth2 client via the unauthenticated registration endpoint and use the password grant to exchange credentials for an API access token, bypassing the normal web interface authentication and any enforced multi-factor authentication controls.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-67611"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-308"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-03T17:16:43Z",
    "severity": "HIGH"
  },
  "details": "OpenEMR through 8.2.0 contains an authentication bypass vulnerability that allows attackers with valid credentials to circumvent multi-factor authentication by exploiting the exposed OAuth2 password grant flow through an unauthenticated client registration endpoint. Attackers can register an OAuth2 client via the unauthenticated registration endpoint and use the password grant to exchange credentials for an API access token, bypassing the normal web interface authentication and any enforced multi-factor authentication controls.",
  "id": "GHSA-g6r6-jr7g-hg95",
  "modified": "2026-08-03T18:30:48Z",
  "published": "2026-08-03T18:30:48Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-67611"
    },
    {
      "type": "WEB",
      "url": "https://jivasecurity.com/writeups/openemr-preauth-disclosure-password-grant"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/openemr-oauth2-password-grant-authentication-bypass-via-smart-configuration"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:N/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"
    }
  ]
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…