Mlflow
CVE-2024-0520
HIGH
Severity by source
AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Primary rating from NVD · only source for this CVE.
CVSS VectorNVD
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Lifecycle Timeline
1Blast Radius
ecosystem impact- 1 pypi packages depend on mlflow (1 direct, 0 indirect)
Ecosystem-wide dependent count for version 2.9.0.
DescriptionNVD
A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the mlflow.data.http_dataset_source.py module. Specifically, when loading a dataset from a source URL with an HTTP scheme, the filename extracted from the Content-Disposition header or the URL path is used to generate the final file path without proper sanitization. This flaw enables an attacker to control the file path fully by utilizing path traversal or absolute path techniques, such as '../../tmp/poc.txt' or '/tmp/poc.txt', leading to arbitrary file write. Exploiting this vulnerability could allow a malicious user to execute commands on the vulnerable machine, potentially gaining access to data and model information. The issue is fixed in version 2.9.0.
AnalysisAI
A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the. Rated high severity (CVSS 8.8), this vulnerability is remotely exploitable, no authentication required, low attack complexity. Public exploit code available.
Technical ContextAI
This vulnerability is classified as Path Traversal (CWE-22), which allows attackers to access files and directories outside the intended path. A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the mlflow.data.http_dataset_source.py module. Specifically, when loading a dataset from a source URL with an HTTP scheme, the filename extracted from the Content-Disposition header or the URL path is used to generate the final file path without proper sanitization. This flaw enables an attacker to control the file path fully by utilizing path traversal or absolute path techniques, such as '../../tmp/poc.txt' or '/tmp/poc.txt', leading to arbitrary file write. Exploiting this vulnerability could allow a malicious user to execute commands on the vulnerable machine, potentially gaining access to data and model information. The issue is fixed in version 2.9.0. Affected products include: Lfprojects Mlflow. Version information: version 8.2.1.
RemediationAI
A vendor patch is available. Apply the latest security update as soon as possible. Validate and canonicalize file paths. Use chroot or sandboxing. Reject input containing path separators or '../' sequences.
A path traversal vulnerability exists in mlflow/mlflow version 2.15.1. Rated high severity (CVSS 7.5), this vulnerabilit
Absolute Path Traversal in GitHub repository mlflow/mlflow prior to 2.5.0. Rated critical severity (CVSS 10.0), this vul
A malicious user could use this issue to get command execution on the vulnerable machine and get access to data & models
A malicious user could use this issue to access internal HTTP(s) servers and in the worst case (ie: aws instance) it cou
An attacker is able to arbitrarily create an account in MLflow bypassing any authentication requirment. Rated critical s
An attacker can overwrite any file on the server hosting MLflow without any authentication. Rated critical severity (CVS
Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.3.1. Rated critical severity (CVSS 9.8), th
Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.2.1. Rated critical severity (CVSS 9.8), th
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset. Rated critical se
Insufficient sanitization in MLflow leads to XSS when running an untrusted recipe. Rated critical severity (CVSS 9.6), t
mlflow/mlflow is vulnerable to Local File Inclusion (LFI) due to improper parsing of URIs, allowing attackers to bypass
Remote Code Execution can occur in versions of the MLflow platform running version 1.11.0 or newer, enabling a malicious
Same weakness CWE-22 – Path Traversal
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External POC / Exploit Code
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