GHSA-GXGJ-2794-2Q5V

Vulnerability from github – Published: 2026-09-27 03:31 – Updated: 2026-09-27 03:31
VLAI
Details

heym before 0.0.91 contains a sandbox escape vulnerability in the expression engine's DotList map/filter and fallback resolver that allows authenticated users to execute arbitrary Python code. Attackers can craft workflow expressions using dunder attribute access through item expressions or the fallback resolver to access os.system and execute commands as the backend process.

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{
  "affected": [],
  "aliases": [
    "CVE-2026-100864"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-94"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-09-27T02:17:26Z",
    "severity": "HIGH"
  },
  "details": "heym before 0.0.91 contains a sandbox escape vulnerability in the expression engine\u0027s DotList map/filter and fallback resolver that allows authenticated users to execute arbitrary Python code. Attackers can craft workflow expressions using dunder attribute access through item expressions or the fallback resolver to access os.system and execute commands as the backend process.",
  "id": "GHSA-gxgj-2794-2q5v",
  "modified": "2026-09-27T03:31:06Z",
  "published": "2026-09-27T03:31:06Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/heymrun/heym/security/advisories/GHSA-87x2-9jwx-7gh4"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-100864"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/heym-before-0.0.91-remote-code-execution-via-expression-engine"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/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"
    }
  ]
}



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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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