GSD-2023-37275

Vulnerability from gsd - Updated: 2023-12-13 01:20
Details
Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. The Auto-GPT command line UI makes heavy use of color-coded print statements to signify different types of system messages to the user, including messages that are crucial for the user to review and control which commands should be executed. Before v0.4.3, it was possible for a malicious external resource (such as a website browsed by Auto-GPT) to cause misleading messages to be printed to the console by getting the LLM to regurgitate JSON encoded ANSI escape sequences (`\u001b[`). These escape sequences were JSON decoded and printed to the console as part of the model's "thinking process". The issue has been patched in release version 0.4.3.
Aliases
Aliases
CVE-2023-37275
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{
  "GSD": {
    "alias": "CVE-2023-37275",
    "id": "GSD-2023-37275"
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2023-37275"
      ],
      "details": "Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. The Auto-GPT command line UI makes heavy use of color-coded print statements to signify different types of system messages to the user, including messages that are crucial for the user to review and control which commands should be executed. Before v0.4.3, it was possible for a malicious external resource (such as a website browsed by Auto-GPT) to cause misleading messages to be printed to the console by getting the LLM to regurgitate JSON encoded ANSI escape sequences (`\\u001b[`). These escape sequences were JSON decoded and printed to the console as part of the model\u0027s \"thinking process\". The issue has been patched in release version 0.4.3.\n",
      "id": "GSD-2023-37275",
      "modified": "2023-12-13T01:20:24.946039Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
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        "ID": "CVE-2023-37275",
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      "affects": {
        "vendor": {
          "vendor_data": [
            {
              "product": {
                "product_data": [
                  {
                    "product_name": "Auto-GPT",
                    "version": {
                      "version_data": [
                        {
                          "version_affected": "=",
                          "version_value": "\u003c 0.4.3"
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          }
        ]
      },
      "impact": {
        "cvss": [
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            "attackComplexity": "HIGH",
            "attackVector": "NETWORK",
            "availabilityImpact": "NONE",
            "baseScore": 3.1,
            "baseSeverity": "LOW",
            "confidentialityImpact": "NONE",
            "integrityImpact": "LOW",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "REQUIRED",
            "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:N/I:L/A:N",
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              {
                "cweId": "CWE-117",
                "lang": "eng",
                "value": "CWE-117: Improper Output Neutralization for Logs"
              }
            ]
          }
        ]
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      "source": {
        "advisory": "GHSA-r7f7-qrrv-3fjh",
        "discovery": "UNKNOWN"
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        "nodes": [
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      "impact": {
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            "attackVector": "NETWORK",
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            "confidentialityImpact": "NONE",
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            "scope": "UNCHANGED",
            "userInteraction": "REQUIRED",
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            "version": "3.1"
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          "exploitabilityScore": 2.8,
          "impactScore": 1.4
        }
      },
      "lastModifiedDate": "2023-07-27T14:55Z",
      "publishedDate": "2023-07-13T23:15Z"
    }
  }
}


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  • 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.
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  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



Detection rules are retrieved from Rulezet.