9.3
CRITICAL CVSS 3.1
CVE-2026-64849
MLflow: Unauthenticated full-read SSRF in webhook delivery: _validate_webhook_url bypassed via unvalidated HTTP redirects (and DNS rebinding)
Description

MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, the unauthenticated POST /api/2.0/mlflow/webhooks/{id}/test endpoint calls _validate_webhook_url() in mlflow/utils/validation.py only for the original URL while mlflow/webhooks/delivery.py follows redirects and re-resolves the hostname without pinning the validated address, allowing attackers to reach internal or cloud metadata services and receive response_status and response_body. This issue is fixed in version 3.15.0.

INFO

Published Date :

Aug. 17, 2026, 10:17 p.m.

Last Modified :

Aug. 17, 2026, 10:17 p.m.

Remotely Exploit :

Yes !
Affected Products

The following products are affected by CVE-2026-64849 vulnerability. Even if cvefeed.io is aware of the exact versions of the products that are affected, the information is not represented in the table below.

ID Vendor Product Action
1 Lfprojects mlflow
CVSS Scores
The Common Vulnerability Scoring System is a standardized framework for assessing the severity of vulnerabilities in software and systems. We collect and displays CVSS scores from various sources for each CVE.
Score Version Severity Vector Exploitability Score Impact Score Source
CVSS 3.1 CRITICAL [email protected]
CVSS 3.1 CRITICAL MITRE-CVE
Solution
Update MLflow to version 3.15.0 or later to fix SSRF vulnerability.
  • Update MLflow to version 3.15.0 or later.
  • Ensure webhook URLs are validated after redirects.
  • Restrict access to internal services.
References to Advisories, Solutions, and Tools
CWE - Common Weakness Enumeration

While CVE identifies specific instances of vulnerabilities, CWE categorizes the common flaws or weaknesses that can lead to vulnerabilities. CVE-2026-64849 is associated with the following CWEs:

Common Attack Pattern Enumeration and Classification (CAPEC)

Common Attack Pattern Enumeration and Classification (CAPEC) stores attack patterns, which are descriptions of the common attributes and approaches employed by adversaries to exploit the CVE-2026-64849 weaknesses.

We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).

Results are limited to the first 15 repositories due to potential performance issues.

The following list is the news that have been mention CVE-2026-64849 vulnerability anywhere in the article.

The following table lists the changes that have been made to the CVE-2026-64849 vulnerability over time.

Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.

  • New CVE Received by [email protected]

    Aug. 17, 2026

    Action Type Old Value New Value
    Added Affected [{'vendor': 'mlflow', 'product': 'mlflow', 'versions': [{'status': 'affected', 'version': '< 3.15.0'}]}]
    Added Description MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, the unauthenticated POST /api/2.0/mlflow/webhooks/{id}/test endpoint calls _validate_webhook_url() in mlflow/utils/validation.py only for the original URL while mlflow/webhooks/delivery.py follows redirects and re-resolves the hostname without pinning the validated address, allowing attackers to reach internal or cloud metadata services and receive response_status and response_body. This issue is fixed in version 3.15.0.
    Added CVSS V3.1 AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:L/A:N
    Added CWE CWE-918
    Added Reference https://github.com/mlflow/mlflow/commit/ba949522477cbd5915aa55d29b0cfad7d5ddf939
    Added Reference https://github.com/mlflow/mlflow/issues/24179
    Added Reference https://github.com/mlflow/mlflow/pull/24258
    Added Reference https://github.com/mlflow/mlflow/releases/tag/v3.15.0
    Added Reference https://github.com/mlflow/mlflow/security/advisories/GHSA-7gwp-5pfp-969j
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days. Following chart shows the EPSS score history of the vulnerability.