CVE-2026-10204
SQL Injection in OFCMS 1.1.3 JSON Query Interface
Publication date: 2026-06-01
Last updated on: 2026-06-01
Assigner: VulDB
Description
Description
CVSS Scores
EPSS Scores
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Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| ofsoft | ofcms | 1.1.3 |
Helpful Resources
Exploitability
| CWE ID | Description |
|---|---|
| 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. |
| 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. |
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?
This vulnerability is an SQL injection flaw found in OFCMS version 1.1.3, specifically in the SysUserController.java file within the query() method. The issue arises because the 'field' and 'sort' parameters, which are user-controlled, are directly concatenated into the ORDER BY clause of SQL queries without proper validation or sanitization.
Attackers can exploit this by crafting malicious SQL expressions, including nested subqueries and Boolean logic, to perform blind SQL injection attacks. This allows them to extract sensitive information, such as admin passwords, by sending specially crafted requests.
The root cause is the lack of input filtering and the absence of a whitelist for allowed fields in SQL statements.
How can this vulnerability impact me? :
This vulnerability can allow remote attackers to perform blind SQL injection attacks on the affected system.
By exploiting this flaw, attackers can extract sensitive data such as administrator passwords, potentially leading to unauthorized access to the system.
Such unauthorized access can result in data breaches, loss of data integrity, and disruption of services.
How can this vulnerability be detected on my network or system? Can you suggest some commands?
This vulnerability can be detected by testing the /admin/system/user/getData.json interface, specifically targeting the 'field' and 'sort' parameters which are vulnerable to SQL injection.
You can attempt to exploit the blind SQL injection by sending specially crafted requests that inject SQL expressions into these parameters and observe the responses for anomalies or data extraction.
For example, you might use curl or similar HTTP request tools to send payloads that test for SQL injection, such as:
- curl -G 'http://<target>/admin/system/user/getData.json' --data-urlencode "field=1' OR (SELECT SUBSTRING(password,1,1) FROM users WHERE username='admin')='a'--"
- curl -G 'http://<target>/admin/system/user/getData.json' --data-urlencode "sort=1' OR 1=1--"
By analyzing the responses to such requests, you can detect if the system is vulnerable to SQL injection.
What immediate steps should I take to mitigate this vulnerability?
Immediate mitigation steps include filtering user input data and implementing a whitelist of allowed fields that can be used in SQL statements, especially for the 'field' and 'sort' parameters in the /admin/system/user/getData.json interface.
Restricting these parameters to only accept predefined safe values prevents attackers from injecting malicious SQL code.
Additionally, monitor and block suspicious requests targeting these parameters and consider applying web application firewall (WAF) rules to detect and prevent SQL injection attempts.
How does this vulnerability affect compliance with common standards and regulations (like GDPR, HIPAA)?:
The SQL injection vulnerability in OFCMS 1.1.3 allows attackers to extract sensitive data such as admin passwords by exploiting improper input validation in the query() method. This exposure of sensitive information can lead to unauthorized access and data breaches.
Such data breaches and unauthorized access incidents can negatively impact compliance with common standards and regulations like GDPR and HIPAA, which require protection of personal and sensitive data. Failure to secure systems against such vulnerabilities may result in violations of these regulations, leading to legal and financial consequences.