Vulnerability-Lookup

GSD-2021-32670

Vulnerability from gsd - Updated: 2023-12-13 01:23

Details

Datasette is an open source multi-tool for exploring and publishing data. The `?_trace=1` debugging feature in Datasette does not correctly escape generated HTML, resulting in a [reflected cross-site scripting](https://owasp.org/www-community/attacks/xss/#reflected-xss-attacks) vulnerability. This vulnerability is particularly relevant if your Datasette installation includes authenticated features using plugins such as [datasette-auth-passwords](https://datasette.io/plugins/datasette-auth-passwords) as an attacker could use the vulnerability to access protected data. Datasette 0.57 and 0.56.1 both include patches for this issue. If you run Datasette behind a proxy you can workaround this issue by rejecting any incoming requests with `?_trace=` or `&_trace=` in their query string parameters.

Aliases

CVE-2021-32670

Aliases

CVE-2021-32670

JSON

To clipboard

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    "description": "Datasette is an open source multi-tool for exploring and publishing data. The `?_trace=1` debugging feature in Datasette does not correctly escape generated HTML, resulting in a [reflected cross-site scripting](https://owasp.org/www-community/attacks/xss/#reflected-xss-attacks) vulnerability. This vulnerability is particularly relevant if your Datasette installation includes authenticated features using plugins such as [datasette-auth-passwords](https://datasette.io/plugins/datasette-auth-passwords) as an attacker could use the vulnerability to access protected data. Datasette 0.57 and 0.56.1 both include patches for this issue. If you run Datasette behind a proxy you can workaround this issue by rejecting any incoming requests with `?_trace=` or `\u0026_trace=` in their query string parameters.",
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}

CVE-2021-32670 (GCVE-0-2021-32670)

Vulnerability from cvelistv5 – Published: 2021-06-07 21:20 – Updated: 2024-08-03 23:25

Title

Reflected cross-site scripting issue in Datasette

Summary

Severity

7.2 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:N

CWE

CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')

Assigner

GitHub_M mitre root

References

5 references

URL	Tags
https://github.com/simonw/datasette/security/advi…	x_refsource_CONFIRM
https://github.com/simonw/datasette/issues/1360	x_refsource_MISC
https://datasette.io/plugins/datasette-auth-passwords	x_refsource_MISC
https://owasp.org/www-community/attacks/xss/#refl…	x_refsource_MISC
https://pypi.org/project/datasette/	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
simonw	datasette	Affected: < 0.56.1

Show details on NVD website

JSON

To clipboard

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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.

Detection rules are retrieved from Rulezet.

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.

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.