GHSA-HJWH-6X9J-WJWQ

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

The raster Rust crate's crop() function (src/editor.rs) clamps the crop width/height against source dimensions but only clamps the offset_x/offset_y parameters against 0, never against the source width/height. When an offset exceeds the corresponding source dimension, width2 - offset_x (or the height equivalent) underflows to a negative i32, which release builds do not trap; the negative value is then cast to usize inside Image::blank()'s Vec::with_capacity() call, triggering a capacity-overflow panic and crashing the process on a single crafted crop request.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-71202"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-191"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-05T08:16:42Z",
    "severity": "HIGH"
  },
  "details": "The raster Rust crate\u0027s crop() function (src/editor.rs) clamps the crop width/height against source dimensions but only clamps the offset_x/offset_y parameters against 0, never against the source width/height. When an offset exceeds the corresponding source dimension, `width2 - offset_x` (or the height equivalent) underflows to a negative i32, which release builds do not trap; the negative value is then cast to usize inside Image::blank()\u0027s Vec::with_capacity() call, triggering a capacity-overflow panic and crashing the process on a single crafted crop request.",
  "id": "GHSA-hjwh-6x9j-wjwq",
  "modified": "2026-08-05T09:31:18Z",
  "published": "2026-08-05T09:31:18Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-71202"
    },
    {
      "type": "WEB",
      "url": "https://github.com/kosinix/raster/issues/30"
    }
  ],
  "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.

Sightings

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Nomenclature

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