CVE-2024-1741 (GCVE-0-2024-1741)
Vulnerability from cvelistv5 – Published: 2024-04-10 17:08 – Updated: 2025-01-31 11:05
VLAI
EPSS
VEX
Title
Improper Authorization in lunary-ai/lunary
Summary
lunary-ai/lunary version 1.0.1 is vulnerable to improper authorization, allowing removed members to read, create, modify, and delete prompt templates using an old authorization token. Despite being removed from an organization, these members can still perform operations on prompt templates by sending HTTP requests with their previously captured authorization token. This issue exposes organizations to unauthorized access and manipulation of sensitive template data.
Severity
9.1 (Critical)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-04-15 21:09 UTC
CWE
- CWE-863 - Incorrect Authorization
Assigner
References
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| lunary-ai | lunary-ai/lunary |
Affected:
unspecified , < 1.2.8
(custom)
|
guessed | |
| lunary-ai | lunary |
Affected:
1.0.1 , < 1.2.8
(custom)
cpe:2.3:a:lunary-ai:lunary:1.0.1:*:*:*:*:*:*:* |
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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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