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GHSA-7RF7-7XF5-V9V3

Vulnerability from github – Published: 2022-07-18 00:00 – Updated: 2022-07-19 00:00
VLAI
Details

pyenv 1.2.24 through 2.3.2 allows local users to gain privileges via a .python-version file in the current working directory. An attacker can craft a Python version string in .python-version to execute shims under their control. (Shims are executables that pass a command along to a specific version of pyenv. The version string is used to construct the path to the command, and there is no validation of whether the version specified is a valid version. Thus, relative path traversal can occur.)

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-35861"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-22"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-07-17T17:15:00Z",
    "severity": "HIGH"
  },
  "details": "pyenv 1.2.24 through 2.3.2 allows local users to gain privileges via a .python-version file in the current working directory. An attacker can craft a Python version string in .python-version to execute shims under their control. (Shims are executables that pass a command along to a specific version of pyenv. The version string is used to construct the path to the command, and there is no validation of whether the version specified is a valid version. Thus, relative path traversal can occur.)",
  "id": "GHSA-7rf7-7xf5-v9v3",
  "modified": "2022-07-19T00:00:27Z",
  "published": "2022-07-18T00:00:33Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-35861"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pyenv/pyenv/commit/22fa683571d98b59ea16e5fe48ac411c67939653"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "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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