CVE-2026-5558
SQL Injection in PHPGurukul /pending-orders.php Enables Remote Attack
Publication date: 2026-04-05
Last updated on: 2026-04-29
Assigner: VulDB
Description
Description
CVSS Scores
EPSS Scores
| Probability: | |
| Percentile: |
Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| phpgurukul | online_shopping_portal_project | to 2.1 (inc) |
Helpful Resources
Exploitability
| CWE ID | Description |
|---|---|
| CWE-74 | The product constructs all or part of a command, data structure, or record using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify how it is parsed or interpreted when it is sent to a downstream component. |
| 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. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data. |
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?
CVE-2026-5558 is a critical SQL injection vulnerability found in the PHPGurukul Online Shopping Portal Project version 2.1, specifically in the /pending-orders.php file. The flaw arises because the "id" parameter is improperly handled and directly included in SQL queries without proper sanitization or validation.
This allows an attacker to inject malicious SQL code remotely, manipulating the database queries executed by the application.
A proof-of-concept demonstrates a time-based blind SQL injection attack that exploits this vulnerability by causing delays in the database response to confirm the injection.
How can this vulnerability impact me? :
This SQL injection vulnerability can have severe impacts including unauthorized access to the database, leakage of sensitive data, tampering with data, full system compromise, and potential disruption of services.
Attackers can exploit this flaw remotely to manipulate SQL queries, which may lead to exposing confidential information or damaging the integrity and availability of the system.
How can this vulnerability be detected on my network or system? Can you suggest some commands?
This vulnerability can be detected by testing the 'id' parameter in the /pending-orders.php file for SQL injection flaws. A proof-of-concept involves a time-based blind SQL injection payload that causes a delay to confirm the vulnerability.
An example payload to test is: id=1' RLIKE (SELECT 9266 FROM (SELECT(SLEEP(5)))XGXl)-- ndWd
You can use the sqlmap tool to automate detection with a command like:
- python sqlmap.py -r C:\Users\lenovo\Desktop\test.txt --level 3 -p "id" --dbs
This command uses a request file and targets the 'id' parameter to enumerate databases, indicating if the injection is successful.
What immediate steps should I take to mitigate this vulnerability?
Immediate mitigation steps include:
- Implement prepared statements with parameter binding to separate SQL code from user input, preventing injection.
- Enforce strict input validation and filtering to ensure inputs conform to expected formats and block malicious data.
- Minimize database user permissions by avoiding the use of high-privilege accounts (such as root or admin) for routine operations.
How does this vulnerability affect compliance with common standards and regulations (like GDPR, HIPAA)?:
The SQL injection vulnerability in the PHPGurukul Online Shopping Portal Project allows unauthorized database access, data leakage, and data tampering. Such impacts can lead to violations of data protection standards and regulations like GDPR and HIPAA, which require the protection of personal and sensitive data against unauthorized access and breaches.
Failure to prevent SQL injection attacks may result in non-compliance with these regulations due to potential exposure of personal data, lack of adequate security controls, and insufficient protection of data integrity and confidentiality.