BIT-mlflow-2023-4033
OS Command Injection vulnerability in mlflow (PyPI)
What is BIT-mlflow-2023-4033 About?
This vulnerability is an OS Command Injection in the mlflow/mlflow GitHub repository prior to version 2.6.0. It allows an attacker to execute arbitrary operating system commands on the host system. The impact can range from data compromise to full system control. The ease of exploitation depends on the specific injection point, but OS command injection is generally considered easy to exploit once identified.
Affected Software
- mlflow
- <2.6.0
- <6dde93758d42455cb90ef324407919ed67668b9b
Technical Details
The OS Command Injection vulnerability exists within the mlflow/mlflow GitHub repository. This means that an attacker can embed arbitrary operating system commands into input fields or parameters that are subsequently used by the MLflow application to construct and execute system commands. When the vulnerable code processes this crafted input, the embedded commands are executed with the privileges of the MLflow application. The exact vector for command injection beyond 'prior to 2.6.0' is not detailed, but commonly involves lack of proper sanitization or validation of user-supplied data before passing it to functions like exec(), system(), or equivalents.
What is the Impact of BIT-mlflow-2023-4033?
Successful exploitation may allow attackers to execute arbitrary commands on the underlying operating system, leading to unauthorized access, data manipulation, or full system compromise.
What is the Exploitability of BIT-mlflow-2023-4033?
The exploitability of an OS Command Injection vulnerability largely depends on the specific injection point, but it typically involves low to moderate complexity. Attackers need to craft malicious input that includes OS commands. Authentication requirements would depend on whether the vulnerable functionality is accessible to unauthenticated users or if it requires authenticated access; generally, if the input point is accessible, exploitation is possible. Privilege requirements would be those of the MLflow application itself. The attack could be remote if the vulnerable input is accessible via a network interface, or local if it requires direct interaction with the system. Special conditions may include specific environmental variables or configurations that facilitate the injection. Risk factors include web-facing MLflow deployments and insufficient input validation in server-side code.
What are the Known Public Exploits?
| PoC Author | Link | Commentary |
|---|---|---|
| No known exploits | ||
What are the Available Fixes for BIT-mlflow-2023-4033?
Available Upgrade Options
- mlflow
- <2.6.0 → Upgrade to 2.6.0
- mlflow
- <6dde93758d42455cb90ef324407919ed67668b9b → Upgrade to 6dde93758d42455cb90ef324407919ed67668b9b
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Book a demoAdditional Resources
- https://github.com/mlflow/mlflow/commit/6dde93758d42455cb90ef324407919ed67668b9b
- https://github.com/mlflow/mlflow/commit/6dde93758d42455cb90ef324407919ed67668b9b
- https://huntr.dev/bounties/5312d6f8-67a5-4607-bd47-5e19966fa321
- https://github.com/mlflow/mlflow
- https://github.com/mlflow/mlflow/commit/6dde93758d42455cb90ef324407919ed67668b9b
- https://huntr.dev/bounties/5312d6f8-67a5-4607-bd47-5e19966fa321
- https://nvd.nist.gov/vuln/detail/CVE-2023-4033
- https://github.com/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2023-280.yaml
- https://osv.dev/vulnerability/PYSEC-2023-280
What are Similar Vulnerabilities to BIT-mlflow-2023-4033?
Similar Vulnerabilities: CVE-2022-24348 , CVE-2021-41223 , CVE-2020-13786 , CVE-2019-1002005 , CVE-2017-1000410
