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CVE Vulnerability Database
Vulnerability Database/CVE-2019-25504

CVE-2019-25504: NCrypted Jobgator SQLi Vulnerability

CVE-2019-25504 is an SQL injection flaw in NCrypted Jobgator that lets unauthenticated attackers manipulate database queries via the experience parameter. This article covers technical details, impact, and mitigation.

Published: March 6, 2026

CVE-2019-25504 Overview

NCrypted Jobgator contains a critical SQL injection vulnerability that allows unauthenticated attackers to manipulate database queries by injecting malicious SQL code through the experience parameter. This vulnerability enables attackers to send specially crafted POST requests to the agents/Find-Jobs endpoint with malicious experience values, potentially extracting sensitive database information including user credentials, personal data, and other confidential records stored in the application's database.

Critical Impact

Unauthenticated attackers can exploit this SQL injection vulnerability to extract sensitive database information, potentially compromising all data stored in the NCrypted Jobgator application.

Affected Products

  • NCrypted Jobgator (all versions without security patches)

Discovery Timeline

  • 2026-03-04 - CVE-2019-25504 published to NVD
  • 2026-03-05 - Last updated in NVD database

Technical Details for CVE-2019-25504

Vulnerability Analysis

This SQL injection vulnerability (CWE-89: Improper Neutralization of Special Elements used in an SQL Command) exists in the NCrypted Jobgator job portal application. The vulnerability stems from improper input validation on the experience parameter within the agents/Find-Jobs endpoint. When processing job search requests, the application fails to properly sanitize user-supplied input before incorporating it into SQL queries, allowing attackers to inject arbitrary SQL commands.

The network-accessible nature of this vulnerability means it can be exploited remotely without any authentication requirements. Successful exploitation could lead to unauthorized access to sensitive database contents, including user credentials, personal information, and job application data. Depending on database permissions, attackers may also be able to modify or delete data.

Root Cause

The root cause of this vulnerability is improper input validation and lack of parameterized queries (prepared statements) in the application's database interaction layer. The experience parameter value submitted via POST requests is directly concatenated into SQL query strings without proper sanitization or escaping. This allows attackers to break out of the intended query context and inject malicious SQL statements that are then executed against the backend database.

Attack Vector

The attack is delivered over the network via HTTP POST requests to the agents/Find-Jobs endpoint. An attacker crafts a malicious request containing SQL injection payloads in the experience parameter field. Since no authentication is required to access this endpoint, any network-accessible attacker can exploit this vulnerability.

The attack follows a classic SQL injection pattern where the injected payload manipulates the structure of the original SQL query. Attackers can use techniques such as UNION-based injection to extract data from other tables, error-based injection to enumerate database structure, or time-based blind injection to infer data character by character.

For detailed technical exploitation information, refer to the Exploit-DB #46663 and the VulnCheck Advisory on SQL Injection.

Detection Methods for CVE-2019-25504

Indicators of Compromise

  • Unusual POST requests to the agents/Find-Jobs endpoint containing special SQL characters such as single quotes, double dashes, UNION keywords, or SELECT statements in the experience parameter
  • Database error messages appearing in application logs or responses indicating malformed SQL queries
  • Abnormal database query execution times suggesting time-based blind SQL injection attempts
  • Unexpected data exfiltration or database access patterns from the web application

Detection Strategies

  • Implement Web Application Firewall (WAF) rules to detect and block SQL injection patterns in POST request parameters
  • Configure database activity monitoring to alert on suspicious query patterns including UNION SELECT statements and unusual WHERE clause conditions
  • Enable application-level logging for all requests to the agents/Find-Jobs endpoint with full parameter capture
  • Deploy intrusion detection systems (IDS) with SQL injection signature rules targeting job portal endpoints

Monitoring Recommendations

  • Monitor web server access logs for repeated requests to agents/Find-Jobs with varying experience parameter values
  • Set up alerts for database error rates exceeding normal thresholds, which may indicate injection attempts
  • Track outbound data transfers from the database server for potential data exfiltration
  • Review application logs for authentication bypass indicators or privilege escalation attempts following initial SQL injection

How to Mitigate CVE-2019-25504

Immediate Actions Required

  • Implement input validation on the experience parameter to accept only expected numeric or predefined values
  • Deploy a Web Application Firewall (WAF) with SQL injection protection rules in front of the NCrypted Jobgator application
  • Restrict database user permissions to minimum required privileges for the web application
  • Enable database auditing to track and alert on suspicious query activity
  • Consider temporarily disabling or restricting access to the agents/Find-Jobs endpoint until a proper fix is implemented

Patch Information

No vendor patch information is currently available in the CVE data. Organizations should contact NCrypted directly for security updates or implement the workarounds below. Monitor the VulnCheck Advisory for updated remediation guidance.

Workarounds

  • Implement parameterized queries (prepared statements) at the application level to prevent SQL injection
  • Deploy input validation middleware that strictly validates the experience parameter against a whitelist of acceptable values
  • Use a reverse proxy or WAF to filter requests containing SQL injection patterns before they reach the application
  • Implement network segmentation to limit database access only from authorized application servers
  • Consider using stored procedures with limited permissions for job search functionality
bash
# Example WAF rule for ModSecurity to block SQL injection in experience parameter
SecRule ARGS:experience "@detectSQLi" \
    "id:1001,\
    phase:2,\
    block,\
    msg:'SQL Injection attempt detected in experience parameter',\
    logdata:'Matched Data: %{MATCHED_VAR}',\
    severity:'CRITICAL'"

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

  • Vulnerability Details
  • TypeSQLI

  • Vendor/TechN/A

  • SeverityHIGH

  • CVSS Score8.8

  • EPSS Probability0.06%

  • Known ExploitedNo
  • CVSS Vector
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:L/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
  • Impact Assessment
  • ConfidentialityLow
  • IntegrityNone
  • AvailabilityNone
  • CWE References
  • CWE-89
  • Technical References
  • Exploit-DB #46663

  • VulnCheck Advisory on SQL Injection
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