How severe is CVE-2024-37057?

No CVSS score has been assigned to CVE-2024-37057 yet. Review the advisory details and affected package list to assess your exposure.

Which packages are affected by CVE-2024-37057?

CVE-2024-37057 affects the following packages: mlflow (Bitnami). Ecosystems affected: Bitnami.

How do I fix CVE-2024-37057?

The records we use list no patched version of mlflow for CVE-2024-37057. Check the maintainer's advisory, and where your build allows, override or pin the dependency away from the vulnerable range.

How do I detect CVE-2024-37057 in my Bitnami dependencies?

Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for mlflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

How do I mitigate CVE-2024-37057 if there is no patch (or I can't update yet)?

Do not deserialise data from untrusted sources: where the format allows it, restrict deserialisation to an explicit allowlist of expected types, and prefer a data-only format (JSON, Protobuf) over one that can reconstruct arbitrary objects until you can upgrade.

Is CVE-2024-37057 actively exploited in the wild?

No public exploit code has been indexed for CVE-2024-37057 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

What is the EPSS score for CVE-2024-37057?

CVE-2024-37057 has an EPSS (Exploit Prediction Scoring System) score of 0.6%, placing it in the 50th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is CVE-2024-37057?

CVE-2024-37057 is classified as Deserialization of Untrusted Data (CWE-502). This weakness type describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation. This is a high-impact weakness class that often enables remote code execution or data exposure.

When was CVE-2024-37057 published, and has it been updated?

CVE-2024-37057 was published on June 10, 2024 and was last updated on September 8, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

📦 Bitnami

Not in CISA KEV

CVE-2024-37057 — mlflow

CVE-2024-37057 is a Deserialization of Untrusted Data vulnerability in mlflow. The records list no fixed version yet; check the vendor advisory below and apply the mitigations in the meantime.

Also known asGHSA-j8mg-pqc5-x9gjPYSEC-2026-1654

Published

Jun 10, 2024

Updated

Sep 8, 2026

Affected

1 pkg

Patched

See advisory

Exploits

None indexed

Exploitation data as of Nov 6, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
A successful exploit gives an attacker total control of the affected component, not partial access.

Exploitation and automatability from CISA’s SSVC triage for CVE-2024-37057.

EPSS Exploitation Probability

via FIRST.org ↗

0.6%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs50th percentile — riskier than 50% of all scored CVEsHighest risk

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

Real-World Exposure

1 pkg affected

📦mlflow

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects Bitnami packages — download data is not available via public APIs for these ecosystems.

Description

Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.0.0rc0 or newer, enabling a maliciously uploaded Tensorflow model to run arbitrary code on an end user’s system when interacted with.

Affected Packages

1 total

Ecosystem	Package	Vulnerable range	Fix
📦Bitnami	`mlflow`	≥ 2.0.0	No fix

Affected Products

1 product · 1 configurations

Application

mlflowlfprojects

≥ 2.0.0

range

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for mlflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Remediation status
The records we use list no patched version of mlflow for CVE-2024-37057. Check the maintainer's advisory, and where your build allows, override or pin the dependency away from the vulnerable range.
Mitigate without a patch
Do not deserialise data from untrusted sources: where the format allows it, restrict deserialisation to an explicit allowlist of expected types, and prefer a data-only format (JSON, Protobuf) over one that can reconstruct arbitrary objects until you can upgrade.

Frequently Asked Questions

Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.0.0 or newer, enabling a maliciously uploaded Tensorflow model to run arbitrary code on an end user’s system when interacted with.

O3 Security · Impact-Aware SCA

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