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GHSA-Q4Q2-FVWF-6GHV

Vulnerability from github – Published: 2022-05-13 01:36 – Updated: 2022-11-04 18:41
VLAI
Summary
Cross-Site Request Forgery in hawtio
Details

It was found that hawtio contains a CSRF flaw that allows unrelated websites to perform actions as the authenticated user. Attackers could use this vulnerability to trick the user to visit his website that contains a malicious script which can be submitted to hawtio server on behalf of the user.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "Maven",
        "name": "io.hawt:project"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.5.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2017-7556"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-352"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-11-04T18:41:35Z",
    "nvd_published_at": "2017-08-17T19:29:00Z",
    "severity": "HIGH"
  },
  "details": "It was found that hawtio contains a CSRF flaw that allows unrelated websites to perform actions as the authenticated user. Attackers could use this vulnerability to trick the user to visit his website that contains a malicious script which can be submitted to hawtio server on behalf of the user.",
  "id": "GHSA-q4q2-fvwf-6ghv",
  "modified": "2022-11-04T18:41:35Z",
  "published": "2022-05-13T01:36:16Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-7556"
    },
    {
      "type": "WEB",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=1480060"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/hawtio/hawtio"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Cross-Site Request Forgery in hawtio"
}



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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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