GHSA-qpgc-w4mg-6v92 BIT-mlflow-2024-27134 CVE-2024-27134 PYSEC-2024-224
MLflow's excessive directory permissions allow local privilege escalation
- Severity
- 0.0 / 10
- High · CVSS 4.0
- Exploit chance (EPSS)
- 0.12%
- Chance of exploitation in the next 30 days. Higher than 1.89% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-276 Incorrect Default Permissions
- Fix
2.16.0- Upgrade mlflow to this version or later
Description
Excessive directory permissions in MLflow leads to local privilege escalation when using spark_udf. This behavior can be exploited by a local attacker to gain elevated permissions by using a ToCToU attack. The issue is only relevant when the spark_udf() MLflow API is called.
Affected versions
PyPI
| Package | Vulnerable | Fixed in |
|---|---|---|
| mlflow | < 2.16.0 |
2.16.0 |
How to fix
Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.
mlflow PyPI → 2.16.0
- pip
pip install --upgrade "mlflow>=2.16.0"- poetry
poetry add "mlflow>=2.16.0"- uv
uv add "mlflow>=2.16.0"
Severity breakdown
CVSS 4.0 0.0
CVSS:4.0/AV:L/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
- Attack vector
- Local
- Attack complexity
- Low
- Attack requirements
- Present
- Privileges required
- None
- User interaction
- Passive
- Confidentiality (vulnerable system)
- High
- Integrity (vulnerable system)
- High
- Availability (vulnerable system)
- High
- Confidentiality (subsequent systems)
- None
- Integrity (subsequent systems)
- None
- Availability (subsequent systems)
- None
CVSS 3.1 7.0
CVSS:3.1/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
- Attack vector
- Local
- Attack complexity
- High
- Privileges required
- None
- User interaction
- Required
- Scope
- Unchanged
- Confidentiality
- High
- Integrity
- High
- Availability
- High
Weakness
CWE-276: Incorrect Default Permissions
During installation, installed file permissions are set to allow anyone to modify those files.
How to prevent it
- Architecture and Design, Operation: The architecture needs to access and modification attributes for files to only those users who actually require those actions.
- Architecture and Design: Compartmentalize the system to have "safe" areas where trust boundaries can be unambiguously drawn. Do not allow sensitive data to go outside of the trust boundary and always be careful when interfacing with a compartment outside of the safe area. Ensure that appropriate compartmentalization is built into the system design, and the compartmentalization allows for and reinforces privilege separation functionality. Architects and designers should rely on the principle of least privilege to decide the appropriate time to use privileges and the time to drop privileges.
References
Advisories
Packages
Other links
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-7gwp-5pfp-969j MLflow: Unauthenticated full-read SSRF in webhook delivery: _validate_webhook_url bypassed via unvalidated HTTP redirects (and DNS rebinding) | Critical Known exploited | Also affects mlflow |
| GHSA-26p8-2jq9-3vq9 MLflow vulnerable to remote code execution on unauthenticated servers via third-party scorer deserialization importing caller-placed artifact modules | Critical | Also affects mlflow |
| GHSA-j7qq-vr8c-xvw3 MLflow CrewAI autologging records LLM provider API keys in logged trace spans | Medium | Also affects mlflow |
| GHSA-m65p-9j7q-6w33 MLflow vulnerable to arbitrary file read on unauthenticated servers via prompt model version source | High | Also affects mlflow |
| GHSA-2wqp-q3c6-ccj5 MLflow: SSRF on unauthenticated MLflow servers via third-party scorer kwargs in the scorer invoke, register, and GenAI evaluate endpoints | Medium | Also affects mlflow |
| GHSA-wqmh-qccw-pqwf MLflow FileStore trace IDs allow path traversal and arbitrary file writes | High | Also affects mlflow |
| GHSA-gqvg-gmmx-x4hm MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False safety control bypassed by mlflow.statsmodels flavor — RCE via crafted model artifact | High | Also affects mlflow |
| GHSA-h7x2-h6g9-p789 MLflow AI Gateway permits SSRF through an unvalidated api_base | High | Also affects mlflow |
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