PYSEC-2026-2547

Vulnerability from pysec - Published: 2026-07-13 15:02 - Updated: 2026-07-13 16:04
VLAI
Details

A vulnerability in the TFSMLayer class of the keras package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of .keras models, even when safe_mode=True. This bypasses the security guarantees of safe_mode and enables arbitrary attacker-controlled code execution during model inference under the victim's privileges. The issue arises due to the unconditional loading of external SavedModels, serialization of attacker-controlled file paths, and the lack of validation in the from_config() method.

Severity
8.8 (High)
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Impacted products
Name purl
keras pkg:pypi/keras
Aliases
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "keras",
        "purl": "pkg:pypi/keras"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.13.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.2.0",
        "0.3.0",
        "0.3.1",
        "0.3.2",
        "0.3.3",
        "1.0.0",
        "1.0.1",
        "1.0.2",
        "1.0.3",
        "1.0.4",
        "1.0.5",
        "1.0.6",
        "1.0.7",
        "1.0.8",
        "1.1.0",
        "1.1.1",
        "1.1.2",
        "1.2.0",
        "1.2.1",
        "1.2.2",
        "2.0.0",
        "2.0.1",
        "2.0.2",
        "2.0.3",
        "2.0.4",
        "2.0.5",
        "2.0.6",
        "2.0.7",
        "2.0.8",
        "2.0.9",
        "2.1.0",
        "2.1.1",
        "2.1.2",
        "2.1.3",
        "2.1.4",
        "2.1.5",
        "2.1.6",
        "2.10.0",
        "2.10.0rc0",
        "2.10.0rc1",
        "2.11.0",
        "2.11.0rc0",
        "2.11.0rc1",
        "2.11.0rc2",
        "2.11.0rc3",
        "2.12.0",
        "2.12.0rc0",
        "2.12.0rc1",
        "2.13.1",
        "2.13.1rc0",
        "2.13.1rc1",
        "2.14.0",
        "2.14.0rc0",
        "2.15.0",
        "2.15.0rc0",
        "2.15.0rc1",
        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.2.3",
        "2.2.4",
        "2.2.5",
        "2.3.0",
        "2.3.1",
        "2.4.0",
        "2.4.1",
        "2.4.2",
        "2.4.3",
        "2.5.0rc0",
        "2.6.0",
        "2.6.0rc0",
        "2.6.0rc1",
        "2.6.0rc2",
        "2.6.0rc3",
        "2.7.0",
        "2.7.0rc0",
        "2.7.0rc2",
        "2.8.0",
        "2.8.0rc0",
        "2.8.0rc1",
        "2.9.0",
        "2.9.0rc0",
        "2.9.0rc1",
        "2.9.0rc2",
        "3.0.0",
        "3.0.1",
        "3.0.2",
        "3.0.3",
        "3.0.4",
        "3.0.5",
        "3.1.0",
        "3.1.1",
        "3.10.0",
        "3.11.0",
        "3.11.1",
        "3.11.2",
        "3.11.3",
        "3.12.0",
        "3.12.1",
        "3.12.2",
        "3.12.3",
        "3.13.0",
        "3.13.1",
        "3.2.0",
        "3.2.1",
        "3.3.0",
        "3.3.1",
        "3.3.2",
        "3.3.3",
        "3.4.0",
        "3.4.1",
        "3.5.0",
        "3.6.0",
        "3.7.0",
        "3.8.0",
        "3.9.0",
        "3.9.1",
        "3.9.2"
      ]
    }
  ],
  "aliases": [
    "CVE-2026-1462",
    "GHSA-4f3f-g24h-fr8m"
  ],
  "details": "A vulnerability in the `TFSMLayer` class of the `keras` package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of `.keras` models, even when `safe_mode=True`. This bypasses the security guarantees of `safe_mode` and enables arbitrary attacker-controlled code execution during model inference under the victim\u0027s privileges. The issue arises due to the unconditional loading of external SavedModels, serialization of attacker-controlled file paths, and the lack of validation in the `from_config()` method.",
  "id": "PYSEC-2026-2547",
  "modified": "2026-07-13T16:04:25.046932Z",
  "published": "2026-07-13T15:02:47.434341Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-1462"
    },
    {
      "type": "WEB",
      "url": "https://github.com/keras-team/keras/pull/22035"
    },
    {
      "type": "WEB",
      "url": "https://github.com/keras-team/keras/commit/b6773d3decaef1b05d8e794458e148cb362f163f"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/keras-team/keras"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/7e78d6f1-6977-4300-b595-e81bdbda331c"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/keras"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-4f3f-g24h-fr8m"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Keras has an untrusted deserialization vulnerability"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.





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.


Detection rules are retrieved from Rulezet.