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CNVD-2022-07638

Vulnerability from cnvd - Published: 2022-01-30
VLAI
Title
TeslaMate权限提升漏洞
Description
TeslaMate是一个开源项目,一个适用于Tesla的自托管数据记录器。 TeslaMate 1.25.1之前版本存在权限提升漏洞,该漏洞源于Tesla使用默认Docker配置,攻击者可以利用Grafana登录访问获取特斯拉API调用的令牌。攻击者可利用该漏洞打开特斯拉汽车的车门,启动Keyless Driving,并在行驶途中干扰车辆运行。
Severity
Patch Name
TeslaMate权限提升漏洞的补丁
Patch Description
TeslaMate是一个开源项目,一个适用于Tesla的自托管数据记录器。 TeslaMate 1.25.1之前版本存在权限提升漏洞,该漏洞源于Tesla使用默认Docker配置,攻击者可以利用Grafana登录访问获取特斯拉API调用的令牌。攻击者可利用该漏洞打开特斯拉汽车的车门,启动Keyless Driving,并在行驶途中干扰车辆运行。目前,供应商发布了安全公告及相关补丁信息,修复了此漏洞。
Formal description

厂商已发布了漏洞修复程序,请及时关注更新: https://github.com/adriankumpf/teslamate/releases/tag/v1.25.1

Reference
https://medium.com/@david_colombo/how-i-got-access-to-25-teslas-around-the-world-by-accident-and-curiosity-8b9ef040a028
Impacted products
Name
TeslaMate TeslaMate <1.25.1
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2022-23126",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2022-23126"
    }
  },
  "description": "TeslaMate\u662f\u4e00\u4e2a\u5f00\u6e90\u9879\u76ee\uff0c\u4e00\u4e2a\u9002\u7528\u4e8eTesla\u7684\u81ea\u6258\u7ba1\u6570\u636e\u8bb0\u5f55\u5668\u3002\n\nTeslaMate 1.25.1\u4e4b\u524d\u7248\u672c\u5b58\u5728\u6743\u9650\u63d0\u5347\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eTesla\u4f7f\u7528\u9ed8\u8ba4Docker\u914d\u7f6e\uff0c\u653b\u51fb\u8005\u53ef\u4ee5\u5229\u7528Grafana\u767b\u5f55\u8bbf\u95ee\u83b7\u53d6\u7279\u65af\u62c9API\u8c03\u7528\u7684\u4ee4\u724c\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u6253\u5f00\u7279\u65af\u62c9\u6c7d\u8f66\u7684\u8f66\u95e8\uff0c\u542f\u52a8Keyless Driving\uff0c\u5e76\u5728\u884c\u9a76\u9014\u4e2d\u5e72\u6270\u8f66\u8f86\u8fd0\u884c\u3002",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://github.com/adriankumpf/teslamate/releases/tag/v1.25.1",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-07638",
  "openTime": "2022-01-30",
  "patchDescription": "TeslaMate\u662f\u4e00\u4e2a\u5f00\u6e90\u9879\u76ee\uff0c\u4e00\u4e2a\u9002\u7528\u4e8eTesla\u7684\u81ea\u6258\u7ba1\u6570\u636e\u8bb0\u5f55\u5668\u3002\r\n\r\nTeslaMate 1.25.1\u4e4b\u524d\u7248\u672c\u5b58\u5728\u6743\u9650\u63d0\u5347\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eTesla\u4f7f\u7528\u9ed8\u8ba4Docker\u914d\u7f6e\uff0c\u653b\u51fb\u8005\u53ef\u4ee5\u5229\u7528Grafana\u767b\u5f55\u8bbf\u95ee\u83b7\u53d6\u7279\u65af\u62c9API\u8c03\u7528\u7684\u4ee4\u724c\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u6253\u5f00\u7279\u65af\u62c9\u6c7d\u8f66\u7684\u8f66\u95e8\uff0c\u542f\u52a8Keyless Driving\uff0c\u5e76\u5728\u884c\u9a76\u9014\u4e2d\u5e72\u6270\u8f66\u8f86\u8fd0\u884c\u3002\u76ee\u524d\uff0c\u4f9b\u5e94\u5546\u53d1\u5e03\u4e86\u5b89\u5168\u516c\u544a\u53ca\u76f8\u5173\u8865\u4e01\u4fe1\u606f\uff0c\u4fee\u590d\u4e86\u6b64\u6f0f\u6d1e\u3002",
  "patchName": "TeslaMate\u6743\u9650\u63d0\u5347\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "TeslaMate TeslaMate \u003c1.25.1"
  },
  "referenceLink": "https://medium.com/@david_colombo/how-i-got-access-to-25-teslas-around-the-world-by-accident-and-curiosity-8b9ef040a028",
  "serverity": "\u9ad8",
  "submitTime": "2022-01-26",
  "title": "TeslaMate\u6743\u9650\u63d0\u5347\u6f0f\u6d1e"
}



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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.
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  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

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Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.


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