GHSA-V865-HP77-22RM

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

Ghostscript before 10.08.0 contains a heap-based buffer overflow vulnerability in the JPEG 2000 output adapter (base/sjpx_openjpeg.c) that allows attackers to cause memory corruption by supplying a crafted PDF containing a JPEG 2000 image with mismatched component subsampling factors. When image components declare different subsampling values, the non-samescale sub-byte-depth output path allocates a row buffer sized for packed output but writes a full byte per output column regardless of bit depth, overflowing the allocation and corrupting internal chunk-allocator metadata to achieve code execution.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-39919"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-122"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-09-15T15:17:14Z",
    "severity": "CRITICAL"
  },
  "details": "Ghostscript before 10.08.0 contains a heap-based buffer overflow vulnerability in the JPEG 2000 output adapter (base/sjpx_openjpeg.c) that allows attackers to cause memory corruption by supplying a crafted PDF containing a JPEG 2000 image with mismatched component subsampling factors. When image components declare different subsampling values, the non-samescale sub-byte-depth output path allocates a row buffer sized for packed output but writes a full byte per output column regardless of bit depth, overflowing the allocation and corrupting internal chunk-allocator metadata to achieve code execution.",
  "id": "GHSA-v865-hp77-22rm",
  "modified": "2026-09-15T15:32:11Z",
  "published": "2026-09-15T15:32:11Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-39919"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ArtifexSoftware/ghostpdl/commit/0a8bf88e39db07b0751a58d6ec1cf992073e4dc1"
    },
    {
      "type": "WEB",
      "url": "https://bugs.ghostscript.com/show_bug.cgi?id=709666"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ArtifexSoftware/ghostpdl-downloads/releases/tag/gs10080"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/ghostscript-heap-buffer-overflow-via-jpeg-2000-output-adapter"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
      "type": "CVSS_V4"
    }
  ]
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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

Author Source Type Date Other

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.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…

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.


Loading…