GHSA-M2V2-9GXP-2R53

Vulnerability from github – Published: 2025-03-20 12:32 – Updated: 2025-03-20 12:32
VLAI
Details

parisneo/lollms-webui version V13 (feather) suffers from a Server-Side Request Forgery (SSRF) vulnerability in the POST /api/proxy REST API. Attackers can exploit this vulnerability to abuse the victim server's credentials to access unauthorized web resources by specifying the JSON parameter {"url":"http://steal.target"}. Existing security mechanisms such as forbid_remote_access(lollmsElfServer), lollmsElfServer.config.headless_server_mode, and check_access(lollmsElfServer, request.client_id) do not protect against this vulnerability.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2024-12766"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-918"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-03-20T10:15:30Z",
    "severity": "HIGH"
  },
  "details": "parisneo/lollms-webui version V13 (feather) suffers from a Server-Side Request Forgery (SSRF) vulnerability in the `POST /api/proxy` REST API. Attackers can exploit this vulnerability to abuse the victim server\u0027s credentials to access unauthorized web resources by specifying the JSON parameter `{\"url\":\"http://steal.target\"}`. Existing security mechanisms such as `forbid_remote_access(lollmsElfServer)`, `lollmsElfServer.config.headless_server_mode`, and `check_access(lollmsElfServer, request.client_id)` do not protect against this vulnerability.",
  "id": "GHSA-m2v2-9gxp-2r53",
  "modified": "2025-03-20T12:32:43Z",
  "published": "2025-03-20T12:32:43Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-12766"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/a143a2e2-1293-4dec-b875-3312584bd2b1"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
      "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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  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
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