CVE-2026-3111 (GCVE-0-2026-3111)
Vulnerability from cvelistv5 – Published: 2026-03-16 09:37 – Updated: 2026-03-16 18:57
VLAI
EPSS
VEX
Title
Multiple vulnerabilities on the Educativa Campus
Summary
Insecure Direct Object Reference (IDOR) vulnerability in Campus Educativa specifically at the endpoint '/archivos/usuarios/[ID]/[username]/thumb_AAxAA.jpg' (translated as 80x90 and 40x45). Successful exploitation of this vulnerability could allow an unauthenticated attacker to access the profile photos of all users via a manipulated URL, enabling them to collect user photos en masse. This could lead to these photos being used maliciously to impersonate identities, perform social engineering, link identities across platforms using facial recognition, or even carry out doxxing.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-03-16 18:56 UTC
CWE
- CWE-284 - Improper Access Control
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://www.incibe.es/en/incibe-cert/notices/avis… | patch |
Impacted products
Date Public
2026-03-16 09:30
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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Vulnerability timeline
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How durations are calculated
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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.
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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.