MAGESH-K21 Online-College-Event-Hall-Reservation-System 1.0 /admin/users.php user_id sql injection

CVSS Meta Temp Score
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Current Exploit Price (≈)
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CTI Interest Score
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7.3$0-$5k0.00

Summaryinfo

A vulnerability, which was classified as critical, has been found in MAGESH-K21 Online-College-Event-Hall-Reservation-System 1.0. Affected by this vulnerability is an unknown functionality of the file /admin/users.php. Performing a manipulation of the argument user_id results in sql injection. This vulnerability is identified as CVE-2024-2534. The attack can be initiated remotely. Additionally, an exploit exists. The vendor was contacted early about this disclosure but did not respond in any way.

Detailsinfo

A vulnerability, which was classified as critical, was found in MAGESH-K21 Online-College-Event-Hall-Reservation-System 1.0. This affects an unknown functionality of the file /admin/users.php. The manipulation of the argument user_id with an unknown input leads to a sql injection vulnerability. CWE is classifying the issue as CWE-89. The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. This is going to have an impact on confidentiality, integrity, and availability.

The weakness was released by Joshua Lictan (Hua Tong). It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2024-2534. The exploitability is told to be easy. It is possible to initiate the attack remotely. Technical details and a public exploit are known. The attack technique deployed by this issue is T1505 according to MITRE ATT&CK.

The exploit is shared for download at github.com. It is declared as proof-of-concept. The vendor was contacted early about this disclosure but did not respond in any way. By approaching the search of inurl:admin/users.php it is possible to find vulnerable targets with Google Hacking.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Vendor

Name

Version

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 7.5
VulDB Meta Temp Score: 7.3

VulDB Base Score: 6.3
VulDB Temp Score: 5.7
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 9.8
NVD Vector: 🔍

CNA Base Score: 6.3
CNA Vector (VulDB): 🔍

CVSSv2info

AVACAuCIA
💳💳💳💳💳💳
💳💳💳💳💳💳
💳💳💳💳💳💳
VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍

NVD Base Score: 🔍

Exploitinginfo

Class: Sql injection
CWE: CWE-89 / CWE-74 / CWE-707
CAPEC: 🔍
ATT&CK: 🔍

Physical: No
Local: No
Remote: Yes

Availability: 🔍
Access: Public
Status: Proof-of-Concept
Download: 🔍
Google Hack: 🔍

EPSS Score: 🔍
EPSS Percentile: 🔍

Price Prediction: 🔍
Current Price Estimation: 🔍

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔍

Timelineinfo

03/15/2024 🔍
03/15/2024 +0 days 🔍
03/15/2024 +0 days 🔍
03/03/2025 +353 days 🔍

Sourcesinfo

Advisory: github.com
Researcher: Joshua Lictan (Hua Tong)
Status: Not defined

CVE: CVE-2024-2534 (🔍)
GCVE (CVE): GCVE-0-2024-2534
GCVE (VulDB): GCVE-100-256971
scip Labs: https://www.scip.ch/en/?labs.20161013

Entryinfo

Created: 03/15/2024 17:34
Updated: 03/03/2025 20:10
Changes: 03/15/2024 17:34 (41), 03/15/2024 17:36 (1), 03/15/2024 20:34 (2), 05/01/2024 08:25 (16), 05/01/2024 08:28 (18), 03/03/2025 20:10 (20)
Complete: 🔍
Submitter: nochizplz
Committer: nochizplz
Cache ID: 216::103

Submitinfo

Accepted

  • Submit #295401: MAGESH-K21 Online-College-Event-Hall-Reservation-System 1.0 SQL Injection (by nochizplz)

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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