CVE-2025-9653 (GCVE-0-2025-9653)
Vulnerability from cvelistv5 – Published: 2025-08-29 14:32 – Updated: 2025-08-29 21:04
VLAI
EPSS
VEX
Title
Portabilis i-Educar Cadastrar projeto educar_projeto_cad.php cross site scripting
Summary
A vulnerability was identified in Portabilis i-Educar up to 2.10. Affected by this vulnerability is an unknown functionality of the file /intranet/educar_projeto_cad.php of the component Cadastrar projeto Page. Such manipulation of the argument nome/observacao leads to cross site scripting. It is possible to launch the attack remotely. The exploit is publicly available and might be used.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-08-29 14:49 UTC
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.321861 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.321861 | signaturepermissions-required |
| https://vuldb.com/?submit.636957 | third-party-advisory |
| https://karinagante.github.io/cve-2025-9653/ | related |
| https://karinagante.github.io/cve-2025-9653/#proo… | exploit |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Portabilis | i-Educar |
Affected:
2.0
Affected: 2.1 Affected: 2.2 Affected: 2.3 Affected: 2.4 Affected: 2.5 Affected: 2.6 Affected: 2.7 Affected: 2.8 Affected: 2.9 Affected: 2.10 |
guessed |
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"time": "2025-08-29T02:00:00.000Z",
"value": "VulDB entry created"
},
{
"lang": "en",
"time": "2025-08-29T23:06:33.000Z",
"value": "VulDB entry last update"
}
],
"title": "Portabilis i-Educar Cadastrar projeto educar_projeto_cad.php cross site scripting"
}
},
"cveMetadata": {
"assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"assignerShortName": "VulDB",
"cveId": "CVE-2025-9653",
"datePublished": "2025-08-29T14:32:08.649Z",
"dateReserved": "2025-08-29T06:54:18.967Z",
"dateUpdated": "2025-08-29T21:04:29.224Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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