code-projects Vehicle Management System 1.0 SQL Database Backup File /vehicle_management.sql information disclosure

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
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CTI Interest Score
Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
4.8$0-$5k1.29+

Summaryinfo

A vulnerability has been found in code-projects Vehicle Management System 1.0 and classified as problematic. This affects an unknown function of the file /vehicle_management.sql of the component SQL Database Backup File Handler. The manipulation leads to information disclosure. This vulnerability is documented as CVE-2026-85517. The attack can be initiated remotely. Additionally, an exploit exists.

Detailsinfo

A vulnerability was found in code-projects Vehicle Management System 1.0. It has been rated as problematic. This issue affects an unknown part of the file /vehicle_management.sql of the component SQL Database Backup File Handler. The manipulation with an unknown input leads to a information disclosure vulnerability. Using CWE to declare the problem leads to CWE-200. The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information. Impacted is confidentiality.

The advisory is shared at github.com. The identification of this vulnerability is CVE-2026-85517. The exploitation is known to be easy. The attack may be initiated remotely. No form of authentication is needed for a successful exploitation. Technical details as well as a public exploit are known. MITRE ATT&CK project uses the attack technique T1592 for this issue.

The exploit is available at github.com. It is declared as proof-of-concept. By approaching the search of inurl:vehicle_management.sql 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.

Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

Productinfo

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Vendor

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Version

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Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 5.3
VulDB Meta Temp Score: 4.8

VulDB Base Score: 5.3
VulDB Temp Score: 4.8
VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv2info

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

Exploitinginfo

Class: Information disclosure
CWE: CWE-200 / CWE-284 / CWE-266
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

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

09/04/2026 Advisory disclosed
09/04/2026 +0 days VulDB entry created
09/04/2026 +0 days VulDB entry last update

Sourcesinfo

Vendor: code-projects.org

Advisory: github.com
Status: Not defined

CVE: CVE-2026-85517 (🔒)
GCVE (CVE): GCVE-0-2026-85517
GCVE (VulDB): GCVE-100-398681
scip Labs: https://www.scip.ch/en/?labs.20161013

Entryinfo

Created: 09/04/2026 08:03
Changes: 09/04/2026 08:03 (56)
Complete: 🔍
Submitter: AhmadMarzook
Cache ID: 216::103

Submitinfo

Accepted

  • Submit #895113: code-projects Vehicle Management System In PHP With Source Code 1.0 Information Disclosure (by AhmadMarzook)

Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

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