CVE-2021-32677 (GCVE-0-2021-32677)
Vulnerability from cvelistv5 – Published: 2021-06-09 17:30 – Updated: 2024-08-03 23:25
VLAI
EPSS
VEX
Title
Cross-Site Request Forgery (CSRF) in FastAPI
Summary
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.
Severity
8.2 (High)
CWE
- CWE-352 - Cross-Site Request Forgery (CSRF)
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/tiangolo/fastapi/security/advi… | x_refsource_CONFIRM |
| https://github.com/tiangolo/fastapi/commit/fa7e3c… | x_refsource_MISC |
| https://lists.fedoraproject.org/archives/list/pac… | vendor-advisoryx_refsource_FEDORA |
Impacted products
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"redhat_vex": {
"current_release_date": "2025-11-21T16:15:31+00:00",
"cve": "CVE-2021-32677",
"id": "CVE-2021-32677",
"initial_release_date": "2021-06-09T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "python-fastapi: Cross-Site Request Forgery attack",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2021/cve-2021-32677.json",
"version": "3"
}
}
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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