GHSA-34J3-4JPJ-GX6Q

Vulnerability from github – Published: 2026-06-17 21:34 – Updated: 2026-06-17 21:34
VLAI
Details

Hermes WebUI before 0.51.443 contains an authorization bypass vulnerability in the session export endpoint that allows authenticated users to access sessions from other profiles. The _handle_session_export handler in api/routes.py fails to verify active-profile ownership before serializing session data, enabling attackers to exfiltrate foreign session transcripts by guessing or knowing session identifiers.

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{
  "affected": [],
  "aliases": [
    "CVE-2026-55198"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-639"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-06-17T19:18:13Z",
    "severity": "HIGH"
  },
  "details": "Hermes WebUI before 0.51.443 contains an authorization bypass vulnerability in the session export endpoint that allows authenticated users to access sessions from other profiles. The _handle_session_export handler in api/routes.py fails to verify active-profile ownership before serializing session data, enabling attackers to exfiltrate foreign session transcripts by guessing or knowing session identifiers.",
  "id": "GHSA-34j3-4jpj-gx6q",
  "modified": "2026-06-17T21:34:38Z",
  "published": "2026-06-17T21:34:38Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-55198"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nesquena/hermes-webui/pull/3991"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nesquena/hermes-webui/pull/4269"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nesquena/hermes-webui/commit/2a3baa71b81ca92da8ece8616a09f15894beec71"
    },
    {
      "type": "WEB",
      "url": "https://github.com/nesquena/hermes-webui/releases/tag/v0.51.443"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/hermes-webui-cross-profile-session-data-exfiltration-via-session-export-endpoint"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/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"
    }
  ]
}


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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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