GHSA-HF67-5VVQ-FM3R

Vulnerability from github – Published: 2026-05-19 12:31 – Updated: 2026-05-20 18:31
VLAI?
Details

A session fixation vulnerability was found in Keycloak's login-actions endpoints. An unauthenticated attacker could exploit this flaw by pre-creating an authentication session and tricking a victim into visiting a maliciously crafted link. By leveraging the /login-actions/restart endpoint—which processes session handles without adequate CSRF protection or cookie ownership validation—an attacker can reset the authentication flow state. This causes Single Sign-On (SSO) to authenticate the victim transparently upon clicking the link, allowing the attacker to hijack the required-action form without needing the victim's credentials. A successful exploit could lead to complete account takeover, including highly privileged administrative accounts.

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{
  "affected": [],
  "aliases": [
    "CVE-2026-7507"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-290"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-05-19T12:16:19Z",
    "severity": "HIGH"
  },
  "details": "A session fixation vulnerability was found in Keycloak\u0027s login-actions endpoints. An unauthenticated attacker could exploit this flaw by pre-creating an authentication session and tricking a victim into visiting a maliciously crafted link. By leveraging the /login-actions/restart endpoint\u2014which processes session handles without adequate CSRF protection or cookie ownership validation\u2014an attacker can reset the authentication flow state. This causes Single Sign-On (SSO) to authenticate the victim transparently upon clicking the link, allowing the attacker to hijack the required-action form without needing the victim\u0027s credentials. A successful exploit could lead to complete account takeover, including highly privileged administrative accounts.",
  "id": "GHSA-hf67-5vvq-fm3r",
  "modified": "2026-05-20T18:31:32Z",
  "published": "2026-05-19T12:31:42Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-7507"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/errata/RHSA-2026:19594"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/errata/RHSA-2026:19595"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/errata/RHSA-2026:19596"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/errata/RHSA-2026:19597"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/security/cve/CVE-2026-7507"
    },
    {
      "type": "WEB",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2464145"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "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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