GHSA-6MC8-MX43-H2QW

Vulnerability from github – Published: 2026-08-05 09:31 – Updated: 2026-08-05 09:31
VLAI
Details

imagecli's scale <ratio> pipeline operation (Scale::apply() in src/image_ops.rs) computes output width/height as (dimension as f32 * ratio) as u32 with no upper-bound validation on the CLI-supplied ratio, which is parsed via nom::number::complete::float with no range check. A large ratio (e.g. 100000) causes an attempted allocation of hundreds of terabytes, aborting the process. Any application embedding imagecli as a library and accepting user-controlled pipeline strings is remotely crashable with a single request.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-70377"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-789"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-05T08:16:41Z",
    "severity": "HIGH"
  },
  "details": "imagecli\u0027s `scale \u003cratio\u003e` pipeline operation (Scale::apply() in src/image_ops.rs) computes output width/height as (dimension as f32 * ratio) as u32 with no upper-bound validation on the CLI-supplied ratio, which is parsed via nom::number::complete::float with no range check. A large ratio (e.g. 100000) causes an attempted allocation of hundreds of terabytes, aborting the process. Any application embedding imagecli as a library and accepting user-controlled pipeline strings is remotely crashable with a single request.",
  "id": "GHSA-6mc8-mx43-h2qw",
  "modified": "2026-08-05T09:31:18Z",
  "published": "2026-08-05T09:31:18Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-70377"
    },
    {
      "type": "WEB",
      "url": "https://github.com/theotherphil/imagecli/issues/66"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/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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