PYSEC-2026-159

Vulnerability from pysec - Published: 2026-04-06 18:16 - Updated: 2026-05-20 12:35
VLAI?
Details

BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.38, the Dockerfile generation function generate_containerfile() in src/bentoml/_internal/container/generate.py uses an unsandboxed jinja2.Environment with the jinja2.ext.do extension to render user-provided dockerfile_template files. When a victim imports a malicious bento archive and runs bentoml containerize, attacker-controlled Jinja2 template code executes arbitrary Python directly on the host machine, bypassing all container isolation. This vulnerability is fixed in 1.4.38.

Impacted products
Name purl
bentoml pkg:pypi/bentoml

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "bentoml",
        "purl": "pkg:pypi/bentoml"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.4.38"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.0.1",
        "0.0.2",
        "0.0.3",
        "0.0.5",
        "0.0.6a0",
        "0.0.7",
        "0.0.7.dev0",
        "0.0.8",
        "0.0.8.post1",
        "0.0.9",
        "0.1.1",
        "0.1.2",
        "0.10.0",
        "0.10.1",
        "0.11.0",
        "0.11.dev0",
        "0.12.0",
        "0.12.1",
        "0.13.0",
        "0.13.1",
        "0.13.2",
        "0.2.0",
        "0.2.1",
        "0.2.2",
        "0.3.0",
        "0.3.1",
        "0.3.3",
        "0.3.4",
        "0.4.0",
        "0.4.1",
        "0.4.2",
        "0.4.3",
        "0.4.4",
        "0.4.5",
        "0.4.7",
        "0.4.8",
        "0.4.9",
        "0.5.0",
        "0.5.1",
        "0.5.2",
        "0.5.3",
        "0.5.4",
        "0.5.5",
        "0.5.6",
        "0.5.7",
        "0.5.8",
        "0.6.0",
        "0.6.1",
        "0.6.2",
        "0.6.3",
        "0.7.0",
        "0.7.1",
        "0.7.2",
        "0.7.3",
        "0.7.4",
        "0.7.5",
        "0.7.6",
        "0.7.7",
        "0.7.8",
        "0.8.0",
        "0.8.1",
        "0.8.2",
        "0.8.3",
        "0.8.4",
        "0.8.5",
        "0.8.6",
        "0.9.0",
        "0.9.0rc0",
        "0.9.1",
        "0.9.2",
        "1.0.0",
        "1.0.0.dev0",
        "1.0.0.dev1",
        "1.0.0a1",
        "1.0.0a2",
        "1.0.0a3",
        "1.0.0a4",
        "1.0.0a5",
        "1.0.0a6",
        "1.0.0a7",
        "1.0.0rc0",
        "1.0.0rc1",
        "1.0.0rc2",
        "1.0.0rc3",
        "1.0.10",
        "1.0.11",
        "1.0.12",
        "1.0.13",
        "1.0.14",
        "1.0.15",
        "1.0.16",
        "1.0.17",
        "1.0.18",
        "1.0.19",
        "1.0.2",
        "1.0.20",
        "1.0.21",
        "1.0.22",
        "1.0.23",
        "1.0.24",
        "1.0.25",
        "1.0.3",
        "1.0.4",
        "1.0.5",
        "1.0.6",
        "1.0.7",
        "1.0.8",
        "1.0.9",
        "1.1.0",
        "1.1.1",
        "1.1.10",
        "1.1.11",
        "1.1.2",
        "1.1.3",
        "1.1.4",
        "1.1.5",
        "1.1.6",
        "1.1.7",
        "1.1.8",
        "1.1.9",
        "1.2.0",
        "1.2.0a0",
        "1.2.0a1",
        "1.2.0a2",
        "1.2.0a3",
        "1.2.0a4",
        "1.2.0a5",
        "1.2.0a6",
        "1.2.0a7",
        "1.2.0rc1",
        "1.2.1",
        "1.2.10",
        "1.2.11",
        "1.2.12",
        "1.2.13",
        "1.2.14",
        "1.2.15",
        "1.2.16",
        "1.2.17",
        "1.2.18",
        "1.2.19",
        "1.2.1a1",
        "1.2.2",
        "1.2.20",
        "1.2.3",
        "1.2.4",
        "1.2.5",
        "1.2.6",
        "1.2.7",
        "1.2.8",
        "1.2.9",
        "1.3.0",
        "1.3.0a1",
        "1.3.0a2",
        "1.3.0a3",
        "1.3.1",
        "1.3.10",
        "1.3.11",
        "1.3.12",
        "1.3.13",
        "1.3.14",
        "1.3.15",
        "1.3.16",
        "1.3.17",
        "1.3.18",
        "1.3.19",
        "1.3.2",
        "1.3.20",
        "1.3.21",
        "1.3.22",
        "1.3.3",
        "1.3.4.post1",
        "1.3.5",
        "1.3.6",
        "1.3.7",
        "1.3.8",
        "1.3.9",
        "1.4.0",
        "1.4.0a1",
        "1.4.0a2",
        "1.4.1",
        "1.4.10",
        "1.4.11",
        "1.4.12",
        "1.4.13",
        "1.4.14",
        "1.4.15",
        "1.4.16",
        "1.4.17",
        "1.4.18",
        "1.4.19",
        "1.4.2",
        "1.4.20",
        "1.4.21",
        "1.4.22",
        "1.4.23",
        "1.4.24",
        "1.4.25",
        "1.4.26",
        "1.4.27",
        "1.4.28",
        "1.4.29",
        "1.4.3",
        "1.4.30",
        "1.4.31",
        "1.4.32",
        "1.4.33",
        "1.4.34",
        "1.4.35",
        "1.4.36",
        "1.4.37",
        "1.4.4",
        "1.4.5",
        "1.4.6",
        "1.4.7",
        "1.4.8",
        "1.4.9"
      ]
    }
  ],
  "aliases": [
    "CVE-2026-35044",
    "GHSA-v959-cwq9-7hr6"
  ],
  "details": "BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.38, the Dockerfile generation function generate_containerfile() in src/bentoml/_internal/container/generate.py uses an unsandboxed jinja2.Environment with the jinja2.ext.do extension to render user-provided dockerfile_template files. When a victim imports a malicious bento archive and runs bentoml containerize, attacker-controlled Jinja2 template code executes arbitrary Python directly on the host machine, bypassing all container isolation. This vulnerability is fixed in 1.4.38.",
  "id": "PYSEC-2026-159",
  "modified": "2026-05-20T12:35:10.976510Z",
  "published": "2026-04-06T18:16:41.990Z",
  "references": [
    {
      "type": "EVIDENCE",
      "url": "https://github.com/bentoml/BentoML/security/advisories/GHSA-v959-cwq9-7hr6"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/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

  • 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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