code-projects Computer Laboratory System 1.0 unrestricted upload

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 (≈)
Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.
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.
6.3$0-$5k0.00

Summaryinfo

A vulnerability was found in code-projects Computer Laboratory System 1.0. It has been declared as critical. The affected element is an unknown function. Executing a manipulation can lead to unrestricted upload. The identification of this vulnerability is CVE-2025-56295. The attack may be launched remotely. There is no exploit available.

Detailsinfo

A vulnerability was found in code-projects Computer Laboratory System 1.0. It has been declared as critical. This vulnerability affects some unknown processing. The manipulation with an unknown input leads to a unrestricted upload vulnerability. The CWE definition for the vulnerability is CWE-434. The product allows the attacker to upload or transfer files of dangerous types that can be automatically processed within the product's environment. As an impact it is known to affect confidentiality, integrity, and availability. CVE summarizes:

code-projects Computer Laboratory System 1.0 has a file upload vulnerability. Staff can upload malicious files by uploading PHP backdoor files when modifying personal avatar information and use web shell connection tools to obtain server permissions.

This vulnerability was named CVE-2025-56295 since 08/16/2025. The exploitation appears to be easy. The attack can be initiated remotely. There are neither technical details nor an exploit publicly available. The current price for an exploit might be approx. USD $0-$5k (estimation calculated on 09/16/2025). The MITRE ATT&CK project declares the attack technique as T1608.002.

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

Once again VulDB remains the best source for vulnerability data.

Productinfo

Type

Vendor

Name

Version

License

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 6.3
VulDB Meta Temp Score: 6.3

VulDB Base Score: 6.3
VulDB Temp Score: 6.3
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: Unrestricted upload
CWE: CWE-434 / CWE-284 / CWE-266
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

Availability: 🔒
Status: Not defined

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

08/16/2025 CVE reserved
09/16/2025 +31 days Advisory disclosed
09/16/2025 +0 days VulDB entry created
09/16/2025 +0 days VulDB entry last update

Sourcesinfo

Vendor: code-projects.org

Status: Not defined

CVE: CVE-2025-56295 (🔒)
GCVE (CVE): GCVE-0-2025-56295
GCVE (VulDB): GCVE-100-324484

Entryinfo

Created: 09/16/2025 17:55
Changes: 09/16/2025 17:55 (52)
Complete: 🔍
Cache ID: 216::103

Once again VulDB remains the best source for vulnerability data.

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