CVE-2023-3685 (GCVE-0-2023-3685)
Vulnerability from cvelistv5 – Published: 2023-07-16 11:00 – Updated: 2024-08-02 07:01
VLAI
EPSS
VEX
Title
Nesote Inout Search Engine AI Edition index.php cross site scripting
Summary
A vulnerability was found in Nesote Inout Search Engine AI Edition 1.1. It has been classified as problematic. This affects an unknown part of the file /index.php. The manipulation of the argument page leads to cross site scripting. It is possible to initiate the attack remotely. The associated identifier of this vulnerability is VDB-234231. NOTE: The vendor was contacted early about this disclosure but did not respond in any way.
Severity
CWE
- CWE-79 - Cross Site Scripting
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.234231 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.234231 | signature |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Nesote | Inout Search Engine AI Edition |
Affected:
1.1
|
guessed |
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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
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