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CVE-2024-3099 — mlflow

CVE-2024-3099 is a CWE-475 vulnerability in mlflow. 1 public exploit or proof-of-concept reference is indexed, so weaponization risk is real. The records list no fixed version yet; check the vendor advisory below and apply the mitigations in the meantime.

Also known asGHSA-8f8q-q2j7-7j2mPYSEC-2026-1645
Published
Updated
Affected
1 pkg
Patched
See advisory
Exploits
1 known
Exploitation data as of Nov 10, 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.

Exploitation and automatability from CISA’s SSVC triage for CVE-2024-3099.

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs39th percentile — riskier than 39% of all scored CVEsHighest risk
0.00%0.31%0.63%0.94%0.1%0.4%May 26Sep 26Nov 26

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

A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts.

Affected Packages

1 total
EcosystemPackageVulnerable rangeFix
📦Bitnamimlflowall versionsNo fix

Affected Products

1 product · 1 configurations
Application
mlflowlfprojects
all
Exploits & PoCs
1

Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.

Detection & mitigation playbook

Open-source dependency
  1. 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.

  2. Remediation status

    The records we use list no patched version of mlflow for CVE-2024-3099. Check the maintainer's advisory, and where your build allows, override or pin the dependency away from the vulnerable range.

  3. Mitigate without a patch

    Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Frequently Asked Questions

A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creati
O3 Security · Impact-Aware SCA

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CVE-2024-3099: mlflow DoS