CVE-2026-96804

HIGH
Published September 23, 2026

MLflow's statsmodel flavor, versions 2.1.0 to 3.14.0, omits the MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False security control entirely in _load_model(), which allows a remote attacker to execute arbitrary code via a crafted MLmodel...

Full CISO analysis pending enrichment.

How severe is it?

CVSS 3.1
8.8 / 10
EPSS
N/A
Exploitation Status
No known exploitation
Sophistication
N/A

What is the attack surface?

AV AC PR UI S C I A
AV Network
AC Low
PR Low
UI None
S Unchanged
C High
I High
A High

What should I do?

No patch available

Monitor for updates. Consider compensating controls or temporary mitigations.

Which compliance frameworks are affected?

Compliance analysis pending. Sign in for full compliance mapping when available.

Frequently Asked Questions

What is CVE-2026-96804?

MLflow's statsmodel flavor, versions 2.1.0 to 3.14.0, omits the MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False security control entirely in _load_model(), which allows a remote attacker to execute arbitrary code via a crafted MLmodel artifact.

Is CVE-2026-96804 actively exploited?

No confirmed active exploitation of CVE-2026-96804 has been reported, but organizations should still patch proactively.

How to fix CVE-2026-96804?

No patch is currently available. Monitor vendor advisories for updates.

What is the CVSS score for CVE-2026-96804?

CVE-2026-96804 has a CVSS v3.1 base score of 8.8 (HIGH).

What are the technical details?

Original Advisory

MLflow's statsmodel flavor, versions 2.1.0 to 3.14.0, omits the MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False security control entirely in _load_model(), which allows a remote attacker to execute arbitrary code via a crafted MLmodel artifact.

Weaknesses (CWE)

CWE-502 — Deserialization of Untrusted Data: The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.

  • [Architecture and Design, Implementation] If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
  • [Implementation] When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.

Source: MITRE CWE corpus.

CVSS Vector

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Timeline

Published
September 23, 2026
Last Modified
September 23, 2026
First Seen
September 23, 2026