CVE-2023-6023 (GCVE-0-2023-6023)
Vulnerability from cvelistv5 – Published: 2023-11-16 16:03 – Updated: 2024-08-02 08:21
VLAI
EPSS
VEX
Title
ModelDB Local File Include
Summary
An attacker can read any file on the filesystem on the server hosting ModelDB through an LFI in the artifact_path URL parameter.
Severity
8.6 (High)
CWE
- CWE-29 - Path Traversal: '\..\filename'
Assigner
References
1 reference
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| vertaai | vertaai/modeldb |
Affected:
unspecified , ≤ latest
(custom)
|
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"redhat_vex": {
"current_release_date": "2025-05-28T22:38:49+00:00",
"cve": "CVE-2023-6023",
"id": "CVE-2023-6023",
"initial_release_date": "2023-01-01T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "ModelDB Local File Include",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2023/cve-2023-6023.json",
"version": "3"
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}
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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.
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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