GHSA-84RG-5QF5-CX44

Vulnerability from github – Published: 2026-09-18 15:32 – Updated: 2026-09-18 15:32
VLAI
Details

A denial of service flaw was found in Poppler's Splash backend. A crafted PDF with tiling-pattern geometry approaching the int32 boundary can cause SplashOutputDev::tilingPatternFill to compute an attacker-controlled repeat count that drives an excessively long loop in the pattern-fill scanline routine, without a corresponding memory allocation. An attacker could exploit this by supplying a malicious PDF to an application that renders it via Poppler's Splash backend, causing the rendering process to consume 100% CPU for an attacker-controlled, extended duration.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-93653"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-606"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-09-18T15:17:22Z",
    "severity": "MODERATE"
  },
  "details": "A denial of service flaw was found in Poppler\u0027s Splash backend. A crafted PDF with tiling-pattern geometry approaching the int32 boundary can cause SplashOutputDev::tilingPatternFill to compute an attacker-controlled repeat count that drives an excessively long loop in the pattern-fill scanline routine, without a corresponding memory allocation. An attacker could exploit this by supplying a malicious PDF to an application that renders it via Poppler\u0027s Splash backend, causing the rendering process to consume 100% CPU for an attacker-controlled, extended duration.",
  "id": "GHSA-84rg-5qf5-cx44",
  "modified": "2026-09-18T15:32:20Z",
  "published": "2026-09-18T15:32:20Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-93653"
    },
    {
      "type": "WEB",
      "url": "https://access.redhat.com/security/cve/CVE-2026-93653"
    },
    {
      "type": "WEB",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2537005"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/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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