CVE-2023-2770 (GCVE-0-2023-2770)
Vulnerability from cvelistv5 – Published: 2023-05-17 18:00 – Updated: 2024-08-02 06:33
VLAI
EPSS
VEX
Title
SourceCodester Online Exam System data sql injection
Summary
A vulnerability classified as critical was found in SourceCodester Online Exam System 1.0. This vulnerability affects unknown code of the file /kelasdosen/data. The manipulation of the argument columns[1][data] leads to sql injection. The attack can be initiated remotely. The exploit has been disclosed to the public and may be used. The identifier of this vulnerability is VDB-229276.
Severity
6.3 (Medium)
6.3 (Medium)
CWE
- CWE-89 - SQL Injection
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.229276 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.229276 | signaturepermissions-required |
| https://github.com/tht1997/CVE_2023/blob/main/onl… | exploit |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| SourceCodester | Online Exam System |
Affected:
1.0
|
guessed |
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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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