CVE-2024-37054VulnerabilityPublished 8 Jun 2024Updated 21 Aug 2026

CVE-2024-37054: versions of the MLflow platform running · Deserialization of Untrusted Data Can Occur

Affects mlflowSource GCVE Database

Not known to be exploited : upgrade to 2.14.2 soon.

Data as of 25 Oct 2026, 19:02 UTC

Severity

High

Rated by Threat Radar · No CVSS score from NVD or the CNA

EPSS: 0.7% chance of exploitation in 30 days – higher than 53% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 2.14.2

Exploitation evidence

Disclosed: evidence found.
CVE published 8 Jun 2024
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-25.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Upgrade mlflow to 2.14.2.

Affected software

Product	Affected	Fixed in
Bitnamimlflow`pkg:bitnami/mlflow`Other threats	Affected >=0.9.0 <2.14.2	Fixed in 2.14.2

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

A patch is available for this vulnerability. Users should upgrade MLflow to version 2.14.2 or later to remediate this issue. Until patched, avoid interacting with untrusted PyFunc models to mitigate risk.

Description

A deserialization vulnerability exists in the MLflow platform versions 0.9.0 and newer up to but not including 2.14.2. This flaw allows a maliciously crafted PyFunc model to execute arbitrary code on a user's system when the model is interacted with. The vulnerability is classified as high severity. A patch is available to address this issue.

Impact

Successful exploitation allows arbitrary code execution on the end user's system via a malicious PyFunc model. This can lead to full compromise of the affected system depending on the privileges of the MLflow process. There are no known exploits in the wild at this time.

Summary

CVE-2024-37054 describes a deserialization of untrusted data vulnerability in MLflow versions >=0.9.0 and <2.14.2. An attacker can upload a malicious PyFunc model that, when loaded or interacted with, can execute arbitrary code on the end user's system. This vulnerability arises from unsafe deserialization practices within the MLflow platform. No CVSS score is provided, but the impact is considered high due to the potential for arbitrary code execution.

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 21 Aug 2026, 14:42 UTC

Technical details

References

Community reviews

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