CVE-2018-25071 (GCVE-0-2018-25071)
Vulnerability from cvelistv5 – Published: 2023-01-07 11:28 – Updated: 2024-08-05 12:33
VLAI
EPSS
VEX
Title
roxlukas LMeve proxy.php insert_log sql injection
Summary
A vulnerability was found in roxlukas LMeve up to 0.1.58. It has been rated as critical. Affected by this issue is the function insert_log of the file wwwroot/ccpwgl/proxy.php. The manipulation of the argument fetch leads to sql injection. Upgrading to version 0.1.59-beta is able to address this issue. The patch is identified as c25ff7fe83a2cda1fcb365b182365adc3ffae332. It is recommended to upgrade the affected component. VDB-217610 is the identifier assigned to this vulnerability.
Severity
5.5 (Medium)
5.5 (Medium)
CWE
- CWE-89 - SQL Injection
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.217610 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.217610 | signaturepermissions-required |
| https://github.com/roxlukas/lmeve/commit/c25ff7fe… | patch |
| https://github.com/roxlukas/lmeve/releases/tag/0.… | patch |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| roxlukas | LMeve |
Affected:
0.1.0
Affected: 0.1.1 Affected: 0.1.2 Affected: 0.1.3 Affected: 0.1.4 Affected: 0.1.5 Affected: 0.1.6 Affected: 0.1.7 Affected: 0.1.8 Affected: 0.1.9 Affected: 0.1.10 Affected: 0.1.11 Affected: 0.1.12 Affected: 0.1.13 Affected: 0.1.14 Affected: 0.1.15 Affected: 0.1.16 Affected: 0.1.17 Affected: 0.1.18 Affected: 0.1.19 Affected: 0.1.20 Affected: 0.1.21 Affected: 0.1.22 Affected: 0.1.23 Affected: 0.1.24 Affected: 0.1.25 Affected: 0.1.26 Affected: 0.1.27 Affected: 0.1.28 Affected: 0.1.29 Affected: 0.1.30 Affected: 0.1.31 Affected: 0.1.32 Affected: 0.1.33 Affected: 0.1.34 Affected: 0.1.35 Affected: 0.1.36 Affected: 0.1.37 Affected: 0.1.38 Affected: 0.1.39 Affected: 0.1.40 Affected: 0.1.41 Affected: 0.1.42 Affected: 0.1.43 Affected: 0.1.44 Affected: 0.1.45 Affected: 0.1.46 Affected: 0.1.47 Affected: 0.1.48 Affected: 0.1.49 Affected: 0.1.50 Affected: 0.1.51 Affected: 0.1.52 Affected: 0.1.53 Affected: 0.1.54 Affected: 0.1.55 Affected: 0.1.56 Affected: 0.1.57 Affected: 0.1.58 |
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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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