Vulnerability-Lookup

GSD-2020-29233

Vulnerability from gsd - Updated: 2023-12-13 01:22

Details

WonderCMS 3.1.3 is affected by cross-site scripting (XSS) in the Page description component. This vulnerability can allow an attacker to inject the XSS payload in the Page description and each time any user will visits the website, the XSS triggers and attacker can steal the cookie according to the crafted payload.

Aliases

CVE-2020-29233

Aliases

CVE-2020-29233

JSON

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    "description": "WonderCMS 3.1.3 is affected by cross-site scripting (XSS) in the Page description component. This vulnerability can allow an attacker to inject the XSS payload in the Page description and each time any user will visits the website, the XSS triggers and attacker can steal the cookie according to the crafted payload.",
    "id": "GSD-2020-29233"
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}

CVE-2020-29233 (GCVE-0-2020-29233)

Vulnerability from cvelistv5 – Published: 2020-12-30 14:48 – Updated: 2024-08-04 16:48

Summary

Severity

No CVSS data available.

CWE

Assigner

mitre CNA under the mitre root

CNA scorecard E 28/100 over 2316 records in the last 180 days details

References

1 reference

URL	Tags
https://www.exploit-db.com/exploits/49085	x_refsource_MISC

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.

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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.

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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