GHSA-RHQC-MH74-4JFX

Vulnerability from github – Published: 2026-04-27 00:30 – Updated: 2026-04-27 00:30
VLAI
Details

CEWE Photoshow 6.3.4 contains a buffer overflow vulnerability in the login dialog that allows attackers to crash the application by submitting oversized input. Attackers can inject 4000 bytes of data into the email address and password fields to trigger a denial of service condition.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2018-25294"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-120"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-04-26T22:17:30Z",
    "severity": "HIGH"
  },
  "details": "CEWE Photoshow 6.3.4 contains a buffer overflow vulnerability in the login dialog that allows attackers to crash the application by submitting oversized input. Attackers can inject 4000 bytes of data into the email address and password fields to trigger a denial of service condition.",
  "id": "GHSA-rhqc-mh74-4jfx",
  "modified": "2026-04-27T00:30:26Z",
  "published": "2026-04-27T00:30:26Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-25294"
    },
    {
      "type": "WEB",
      "url": "https://cewe-photoworld.com"
    },
    {
      "type": "WEB",
      "url": "https://cewe-photoworld.com/creator-software/windows-download"
    },
    {
      "type": "WEB",
      "url": "https://www.exploit-db.com/exploits/45211"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/cewe-photoshow-buffer-overflow-denial-of-service"
    }
  ],
  "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"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/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"
    }
  ]
}


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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

  • 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.


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