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Threat Model Analysis for dapperlib/dapper

Threat: SQL Injection via String Concatenation

Description: An attacker exploits vulnerabilities arising from developers constructing SQL queries by directly concatenating user-supplied input strings when using Dapper's query execution methods (like Query, Execute, etc.). The attacker injects malicious SQL code within the input, which is then executed by the database. This can be done through any input field that is incorporated into a SQL query without proper parameterization. Impact:

  • Data Breach: Unauthorized access to sensitive data.
  • Data Modification/Deletion: Attackers can modify or delete critical data.
  • Account Takeover: Attackers can gain control of user accounts.
  • Denial of Service (DoS): Malicious queries can overload the database.
  • Remote Code Execution (in severe cases): Attackers might execute arbitrary commands on the database server. Dapper Component Affected: Query, Execute, QueryFirstOrDefault, and other query execution methods when used without parameterization by the developer. Risk Severity: Critical Mitigation Strategies:
  • Mandatory Parameterized Queries: Always use parameterized queries with Dapper's @parameterName syntax or anonymous objects for user inputs.
  • Code Reviews: Conduct thorough code reviews to identify and eliminate string concatenation in SQL query construction.
  • Static Analysis Security Testing (SAST): Use SAST tools to detect potential SQL injection vulnerabilities.
  • Developer Training: Train developers on secure coding practices and SQL injection prevention with Dapper.

Threat: Blind SQL Injection via Timing Attacks

Description: An attacker exploits subtle differences in application response times when using Dapper, based on the execution of injected SQL code. By sending numerous crafted requests and analyzing response times, the attacker can infer database schema, data, or application logic. This is often achieved by injecting time-delaying SQL commands (e.g., WAITFOR DELAY) and observing the application's response time variations when Dapper executes these queries. Impact:

  • Database Schema Discovery: Attackers can map out the database structure.
  • Data Exfiltration (slow and incremental): Attackers can slowly extract data bit by bit.
  • Information Disclosure: Subtle application behavior changes can leak sensitive information. Dapper Component Affected: Query, Execute, QueryFirstOrDefault, and other query execution methods in terms of their performance and response behavior when executing attacker-controlled queries. Risk Severity: High Mitigation Strategies:
  • Normalize Response Times: Design the application to have consistent response times, minimizing timing differences based on query outcomes.
  • Rate Limiting and Request Throttling: Limit requests from a single source to hinder automated blind SQL injection attempts.
  • Web Application Firewall (WAF): Deploy a WAF to detect and block suspicious SQL injection attempts, including timing-based attacks.
  • Database Monitoring and Intrusion Detection Systems (IDS): Monitor database activity for unusual patterns indicative of blind SQL injection.
  • Secure Error Handling: Ensure error messages are generic and do not reveal database or query execution details.