FKIE_CVE-2026-55237

Vulnerability from fkie_nvd - Published: 2026-06-18 17:16 - Updated: 2026-06-18 18:16
Summary
AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Versions prior to 0.6.62 have a DOM-based Cross-Site Scripting (XSS) vulnerability in AutoGPT's signup page. The application improperly trusts a URL parameter (`next`), which is passed to `router.push`. An attacker can craft a malicious link that, when opened by an authenticated user, performs a client-side redirect and executes arbitrary JavaScript in the context of their browser. This could lead to credential theft, internal network pivoting, and unauthorized actions performed on behalf of the victim. Version 0.6.62 patches the issue.
Impacted products
Vendor Product Version

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "AutoGPT",
          "vendor": "Significant-Gravitas",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c 0.6.62"
            }
          ]
        }
      ],
      "source": "security-advisories@github.com"
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Versions prior to 0.6.62 have a DOM-based Cross-Site Scripting (XSS) vulnerability in AutoGPT\u0027s signup page. The application improperly trusts a URL parameter (`next`), which is passed to `router.push`. An attacker can craft a malicious link that, when opened by an authenticated user, performs a client-side redirect and executes arbitrary JavaScript in the context of their browser. This could lead to credential theft, internal network pivoting, and unauthorized actions performed on behalf of the victim. Version 0.6.62 patches the issue."
    }
  ],
  "id": "CVE-2026-55237",
  "lastModified": "2026-06-18T18:16:20.293",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "LOW",
          "baseScore": 8.8,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "LOW",
          "privilegesRequired": "NONE",
          "scope": "CHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:L/A:L",
          "version": "3.1"
        },
        "exploitabilityScore": 2.8,
        "impactScore": 5.3,
        "source": "security-advisories@github.com",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2026-55237",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-06-18T17:29:06.409362Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2026-06-18T17:16:34.900",
  "references": [
    {
      "source": "security-advisories@github.com",
      "url": "https://github.com/Significant-Gravitas/AutoGPT/security/advisories/GHSA-j2cp-jg5q-38wj"
    },
    {
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "url": "https://github.com/Significant-Gravitas/AutoGPT/security/advisories/GHSA-j2cp-jg5q-38wj"
    }
  ],
  "sourceIdentifier": "security-advisories@github.com",
  "vulnStatus": "Deferred",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-87"
        },
        {
          "lang": "en",
          "value": "CWE-601"
        }
      ],
      "source": "security-advisories@github.com",
      "type": "Secondary"
    }
  ]
}


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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

  • 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.
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