CVE-2023-6709
Improper Neutralization of Special Elements Used in a Template Engine vulnerability in mlflow (PyPI)
What is CVE-2023-6709 About?
This vulnerability involves improper neutralization of special elements within a template engine in MLflow. This flaw can lead to the execution of arbitrary code or data manipulation. Exploiting this vulnerability would likely be moderately difficult, requiring specific knowledge of the template engine's processing and potential bypasses.
Affected Software
Technical Details
The vulnerability stems from the mlflow/mlflow repository prior to version 2.9.2, where special elements used in a template engine are not properly neutralized. This allows an attacker to inject specially crafted input that the template engine interprets as executable code or commands rather than benign data. This could arise from insufficient sanitization or encoding of user-supplied input before it is rendered by the template engine, leading to various injection attacks.
What is the Impact of CVE-2023-6709?
Successful exploitation may allow attackers to execute arbitrary code, manipulate data, or gain unauthorized access to sensitive information within the affected system.
What is the Exploitability of CVE-2023-6709?
Exploitation of this vulnerability requires a moderate level of technical expertise, as an attacker would need to craft specific input that leverages the improper neutralization in the template engine. Prerequisites include access to an interface that allows input to be processed by the vulnerable template engine. Authentication might be required to submit such input, depending on the application's design, but the vulnerability itself could reside in a feature accessible to authenticated or unauthenticated users. The attack is likely remote, as it involves sending malicious data to the application. Risk factors include applications that process untrusted user input without robust sanitization, increasing likelihood of exploitation.
What are the Known Public Exploits?
| PoC Author | Link | Commentary |
|---|---|---|
| No known exploits | ||
What are the Available Fixes for CVE-2023-6709?
Available Upgrade Options
- mlflow
- <2.9.2 → Upgrade to 2.9.2
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Book a demoAdditional Resources
- https://github.com/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2023-281.yaml
- https://huntr.com/bounties/9e4cc07b-6fff-421b-89bd-9445ef61d34d
- https://osv.dev/vulnerability/GHSA-cxfr-5q3r-2rc2
- https://github.com/mlflow/mlflow/commit/432b8ccf27fd3a76df4ba79bb1bec62118a85625
- https://nvd.nist.gov/vuln/detail/CVE-2023-6709
- https://github.com/mlflow/mlflow
- https://huntr.com/bounties/9e4cc07b-6fff-421b-89bd-9445ef61d34d
- https://github.com/mlflow/mlflow/commit/432b8ccf27fd3a76df4ba79bb1bec62118a85625
What are Similar Vulnerabilities to CVE-2023-6709?
Similar Vulnerabilities: CVE-2022-23577 , CVE-2021-39239 , CVE-2021-33519 , CVE-2020-28153 , CVE-2020-13778
