CVE-2024-5063 (GCVE-0-2024-5063)
Vulnerability from cvelistv5 – Published: 2024-05-17 18:31 – Updated: 2024-08-01 21:03
VLAI
EPSS
VEX
Title
PHPGurukul Online Course Registration System index.php sql injection
Summary
A vulnerability was found in PHPGurukul Online Course Registration System 3.1. It has been declared as critical. This vulnerability affects unknown code of the file /admin/index.php. The manipulation of the argument username/password leads to sql injection. The attack can be initiated remotely. The exploit has been disclosed to the public and may be used. VDB-264922 is the identifier assigned to this vulnerability.
Severity
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-05-24 14:55 UTC
CWE
- CWE-89 - SQL Injection
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.264922 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.264922 | signaturepermissions-required |
| https://vuldb.com/?submit.336236 | third-party-advisory |
| https://github.com/BurakSevben/CVEs/blob/main/Onl… | exploit |
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| PHPGurukul | Online Course Registration System |
Affected:
3.1
|
guessed | |
| phpgurukul | online_course_registration_system |
Affected:
3.1
cpe:2.3:a:phpgurukul:online_course_registration_system:3.1:*:*:*:*:*:*:* |
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"orgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"shortName": "VulDB"
},
"references": [
{
"name": "VDB-264922 | PHPGurukul Online Course Registration System index.php sql injection",
"tags": [
"vdb-entry",
"technical-description"
],
"url": "https://vuldb.com/?id.264922"
},
{
"name": "VDB-264922 | CTI Indicators (IOB, IOC, TTP, IOA)",
"tags": [
"signature",
"permissions-required"
],
"url": "https://vuldb.com/?ctiid.264922"
},
{
"name": "Submit #336236 | PHPGurukul Online Course Registration System 3.1 Authentication Bypass via SQL Injection",
"tags": [
"third-party-advisory"
],
"url": "https://vuldb.com/?submit.336236"
},
{
"tags": [
"exploit"
],
"url": "https://github.com/BurakSevben/CVEs/blob/main/Online%20Course%20Registration%20System/Online%20Course%20Registration%20System%20-%20Authentication%20Bypass.md"
}
],
"timeline": [
{
"lang": "en",
"time": "2024-05-17T00:00:00.000Z",
"value": "Advisory disclosed"
},
{
"lang": "en",
"time": "2024-05-17T02:00:00.000Z",
"value": "VulDB entry created"
},
{
"lang": "en",
"time": "2024-05-17T15:31:22.000Z",
"value": "VulDB entry last update"
}
],
"title": "PHPGurukul Online Course Registration System index.php sql injection"
}
},
"cveMetadata": {
"assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
"assignerShortName": "VulDB",
"cveId": "CVE-2024-5063",
"datePublished": "2024-05-17T18:31:04.690Z",
"dateReserved": "2024-05-17T13:26:04.350Z",
"dateUpdated": "2024-08-01T21:03:10.441Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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