Bentoml Server-Side-Request-Forgery Scanner

BentoML is a platform for building, shipping, and running machine learning services. It is widely used by data scientists and developers to streamline the deployment of machine learning models. The platform provides a range of features including model packaging, asynchronous inference, and auto-scaling. Due to its ease of use and flexibility, BentoML is utilized in diverse environments from development to production. Organizations leverage BentoML to reduce the operational complexity involved in serving machine learning models. With its robust feature set, BentoML empowers users to efficiently manage production-grade ML deployments.

The Server-Side-Request-Forgery (SSRF) vulnerability detected in BentoML allows an attacker to make unauthorized requests to internal services. SSRF vulnerabilities occur when an attacker can influence server-side requests that the server makes to unintended resources or services. This type of vulnerability can lead to unauthorized access and data leakage, potentially exposing sensitive internal resources. Exploiting SSRF vulnerabilities often involves directing the server to areas within the local network that are not intended to be accessed by external users. Detection of such vulnerabilities is crucial to ensuring that external parties cannot exploit them for malicious purposes.

The SSRF vulnerability in BentoML exists in its file upload request handling, specifically within the /encode_image endpoint. The vulnerability arises from the mishandling of user input without proper validation or sanitization. An attacker can craft a malicious HTTP request leveraging this endpoint to access unintended resources using interactsh for detection. The vulnerability allows the attacker to specify URLs in the request body, potentially leading to unauthorized interactions with internal network services. Successful exploitation can result in unauthorized data access or modification, further illustrating the importance of securing inputs against such attacks.

Exploiting the SSRF vulnerability in BentoML could allow attackers to interact with internal services within the network. This can result in unauthorized access to sensitive information or disturbance of internal operations. If exploited effectively, attackers could pivot through the network, gaining deeper access into potentially critical infrastructure. The security breach could lead to data exfiltration or manipulation, impacting the confidentiality and integrity of organizational data. Additionally, such vulnerabilities can pave the way for further attack vectors, making remediation a high priority for affected systems.

REFERENCES

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