GCVE-1-2026-0006
Vulnerability from gna-1 – Published: 2026-01-13 15:37 – Updated: 2026-01-13 15:37
VLAI
EPSS
VEX
Title
Improper Access Control in Cerebrate AuthKey and EncryptionKey Entities Allows Modification of Sensitive Fields
Summary
Multiple mass assignment vulnerabilities exist in the AuthKey and EncryptionKey entities of Cerebrate prior to the fixed version, where insufficient protection of sensitive fields allowed attackers to modify security-critical attributes. Due to missing or overly permissive $_accessible configurations, attackers could set protected fields such as authentication keys, UUIDs, and primary identifiers, potentially leading to credential manipulation, impersonation, and compromise of cryptographic material.
Severity
CWE
Assigner
GNA-1
This instance
References
1 reference
| URL | Tags |
|---|---|
| https://github.com/cerebrate-project/cerebrate/co… | patch |
Impacted products
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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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