CVE-2023-6568 Scanner

Mlflow is used worldwide by data scientists and AI/ML engineers to track experiments, train models, and manage the end-to-end machine learning lifecycle. It provides various features to support user activities, including data collection, model training, and deployment. Companies utilize Mlflow to maintain consistency and reproducibility in their machine learning projects. It is widely adopted due to its ability to integrate easily with existing data pipelines and infrastructure. Researchers and developers benefit from its open-source nature, allowing for extensive customization. Essentially, Mlflow helps simplify the management of machine learning model lifecycle tracking.

The vulnerability in question is a Cross-Site Scripting (XSS) flaw, which allows attackers to inject and execute malicious scripts in the context of a user's browser session. These scripts can potentially hijack user sessions or perform actions on behalf of the users. The vulnerability specifically targets the Content-Type header of a POST request in Mlflow. If unmitigated, XSS vulnerabilities can lead to significant security breaches, compromising user data and application integrity. Cross-Site Scripting is a common attack vector in web applications due to inadequate input validation. This highlights the need for rigorous input sanitization and validation practices.

The vulnerability stems from inadequate sanitization of user-supplied values, particularly within the Content-Type header. Attackers can inject JavaScript code such as "<script>alert(document.domain)</script>" into this header. When the malicious request is processed, the payload is reflected back to the user in an unsanitized manner. This flaw could allow attackers to present bogus information to unsuspecting users or extract sensitive data within user cookies. The vulnerable endpoint '/api/2.0/mlflow/users/create' in the HTTP POST request is particularly susceptible to this input manipulation. Validation of headers, particularly content-type, is crucial to thwart these types of attacks.

Exploitation of this XSS vulnerability could lead to unauthorized actions performed on behalf of users and the leakage of sensitive data. Potential outcomes include session hijacking, unauthorized transaction execution, and manipulation of content delivered to the end-users. Attackers could also craft phishing scams by leveraging the application’s trusted interface. Additionally, the spread of misinformation could occur if scripts were used to alter user-visible data. In severe cases, this could result in monetary losses or tarnishing of the organization's reputation.

REFERENCES

• https://huntr.com/bounties/816bdaaa-8153-4732-951e-b0d92fddf709
• https://nvd.nist.gov/vuln/detail/CVE-2023-6568