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    CVE-2021-32677

    FastAPI is a web framework for building APIs with Python 3.6+ based on standard Python type hints. FastAPI versions lower than 0.65.2 that used cookies for authentication in path operations that received JSON payloads sent by browsers were vulnerable to a Cross-Site Request Forgery (CSRF) attack. In versions lower than 0.65.2, FastAPI would try to read the request payload as JSON even if the content-type header sent was not set to application/json or a compatible JSON media type (e.g. application/geo+json). A request with a content type of text/plain containing JSON data would be accepted and the JSON data would be extracted. Requests with content type text/plain are exempt from CORS preflights, for being considered Simple requests. The browser will execute them right away including cookies, and the text content could be a JSON string that would be parsed and accepted by the FastAPI application. This is fixed in FastAPI 0.65.2. The request data is now parsed as JSON only if the content-type header is application/json or another JSON compatible media type like application/geo+json. It's best to upgrade to the latest FastAPI, but if updating is not possible then a middleware or a dependency that checks the content-type header and aborts the request if it is not application/json or another JSON compatible content type can act as a mitigating workaround.

    Published:Jun 9, 2021
    Last Modified:Nov 21, 2024
    EPS:Jun 9, 2021
    EPSS Score:0.00119
    CVSS Score:8.2

    Affected Products

    Vendor
    Fedoraproject
    Product
    Fedora
    Vendor
    Tiangolo
    Product
    Fastapi

    Exploits

    No exploit reference

    Related CVEs

    Common Vulnerability Scoring System

    Attack Vector
    Network
    Adjacent
    Local
    Physical
    Privileges Required
    None
    Low
    High
    User Interaction
    None
    Required
    Scope
    Unchanged
    Changed
    Confidentiality
    None
    Low
    High
    Integrity
    None
    Low
    High
    Availability
    None
    Low
    High