feat(agents-api): Prevent SQL injection attacks

[creatorrr]

PR Type

Bug fix, Enhancement

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Description

• Implement comprehensive SQL injection prevention system

• Add SafeQueryBuilder class for secure dynamic query construction

• Replace string formatting with parameterized queries across modules

• Add extensive test coverage for SQL security mechanisms

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Changes walkthrough 📝

	Relevant files
Bug fix	5 files list_agents.py Replace format() with safe string replacement                        +3/-4      bulk_delete_docs.py Remove f-string usage for safe query building                        +7/-2      list_docs.py Implement SafeQueryBuilder for secure query construction  +16/-15  list_entries.py Add safe_format_query for ORDER BY validation                        +8/-2      list_files.py Replace manual query building with SafeQueryBuilder            +12/-14
Enhancement	1 files sql_utils.py Create comprehensive SQL injection prevention utilities    +298/-0
Documentation	7 files sql_injection_prevention_demo.py Add demonstration script for SQL safety features                  +158/-0  AGENTS.md Add SQL safety patterns and guidelines                                      +23/-0    CONTRIBUTING.md Add security guidelines for SQL injection prevention          +21/-0    AGENTS.md Add SQL safety requirements and examples                                  +32/-0    README.md Document queries module SQL safety utilities                          +4/-0      AGENTS.md Add comprehensive SQL safety documentation                              +51/-0    SQL_INJECTION_PREVENTION.md Create detailed SQL injection prevention guide                      +164/-0
Tests	1 files test_sql_injection_prevention.py Add comprehensive SQL injection prevention tests                  +260/-0

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[claude]

Claude finished @creatorrr's task —— View job

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Pull Request Review: SQL Injection Prevention

I've completed a thorough review of this security-focused PR. This is an excellent implementation that addresses critical SQL injection vulnerabilities across the agents-api codebase.

Review Tasks:

• Analyze the new SQL utilities module
• Review refactored query files for security improvements
• Evaluate documentation and examples
• Check test coverage
• Assess performance implications
• Provide comprehensive feedback

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🔒 Security Assessment: EXCELLENT

Critical Vulnerabilities Fixed

✅ SQL Injection in ORDER BY clauses - Previously used f-strings/.format() for dynamic sorting
✅ Dynamic query building - Metadata filters and conditions now properly parameterized
✅ Identifier validation - Table/column names validated against regex patterns and SQL keywords

Security Strengths

• Whitelist-based validation for sort fields prevents unauthorized column access
• Parameterized queries ($1, $2, etc.) eliminate value-based injection vectors
• SQL keyword blocking prevents reserved word exploitation
• Length limits (63 chars) prevent buffer overflow attempts
• Clear error messages don't expose internal structure

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📋 Code Quality Review: VERY GOOD

New SQL Utilities Module (sql_utils.py)

Excellent design with clear separation of concerns:

• sanitize_identifier(): Robust validation with regex, keyword blocking, and length limits
• SafeQueryBuilder: Clean builder pattern for complex queries
• safe_format_query(): Safe alternative to string formatting
• Type safety: Proper use of beartype decorators and return types

Refactored Query Files

Consistent implementation across all affected files:

list_docs.py:712-118 - Excellent SafeQueryBuilder usage for metadata filtering
list_entries.py:102-108 - Clean safe_format_query implementation
list_files.py:66-84 - Proper conditional query building

Code Pattern Consistency

✅ All files follow the same security pattern
✅ Proper parameter ordering and naming
✅ Consistent error handling

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🧪 Test Coverage: COMPREHENSIVE

The test suite (test_sql_injection_prevention.py) covers all critical attack vectors:

• Identifier validation: Empty strings, special chars, SQL keywords, length limits
• SQL injection attempts: Classic attacks like ; DROP TABLE users;--
• Whitelist validation: Custom allowed fields, invalid field rejection
• Query building: Complex scenarios with multiple conditions
• Edge cases: Table prefixes, parameter counting, direction validation

260 lines of thorough testing - this is exemplary test coverage for a security feature.

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⚡ Performance Considerations: GOOD

Positive Impacts

• Parameterized queries are more efficient (query plan caching)
• Single-pass validation avoids repeated checks
• Builder pattern prevents string concatenation overhead

Potential Concerns (Minor)

• Regex validation adds small overhead, but negligible for typical loads
• HTTPException creation for validation errors is appropriate

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📚 Documentation: OUTSTANDING

SQL_INJECTION_PREVENTION.md

• Clear vulnerability explanation with affected files listed
• Comprehensive usage examples for all utilities
• Migration guide for future development
• Security considerations well documented

Code Comments

• AIDEV-NOTE anchors properly placed for AI context
• Inline documentation explains security rationale
• Function docstrings follow Google style

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🔍 Issues Found

Minor Issues

1. agents_api/queries/docs/list_docs.py:100-104 - Commented validation code should be removed:

   # if direction.lower() not in ["asc", "desc"]:
   #     raise HTTPException(status_code=400, detail="Invalid sort direction")

2. SQL_UTILS_PATTERN_CONSISTENCY - Consider using constants for repeated patterns:

   # Current: Multiple files use {"created_at", "updated_at"}
   # Suggest: Define COMMON_SORT_FIELDS constant

Suggestions for Enhancement

1. Expand SQL keyword list - Consider adding more keywords like GRANT, REVOKE, TRUNCATE
2. Add security logging - Log blocked injection attempts for monitoring
3. Query complexity limits - Consider adding limits on condition count for SafeQueryBuilder

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🎯 Recommendations

Before Merge

• Remove commented validation code in list_docs.py:100-104
• Consider adding a few more SQL keywords to the blocklist

Post-Merge

• Monitor for any performance impacts in production
• Consider adding security event logging for blocked attempts
• Update team documentation/training on these patterns

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✅ Overall Assessment

This PR represents a significant security improvement with minimal performance impact. The implementation is well-architected, thoroughly tested, and properly documented. The consistent application across all vulnerable files demonstrates excellent attention to detail.

Recommendation: APPROVE with minor cleanup suggested above

The SQL injection prevention mechanisms are robust and should effectively protect against the identified vulnerabilities while maintaining code readability and performance.

Security Impact: HIGH - Fixes critical vulnerabilities
Code Quality: EXCELLENT - Clean, consistent implementation
Test Coverage: COMPREHENSIVE - All attack vectors covered
Documentation: OUTSTANDING - Thorough and practical

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[qodo-merge-for-open-source]

PR Reviewer Guide 🔍

Here are some key observations to aid the review process:

⏱️ Estimated effort to review: 4 🔵🔵🔵🔵⚪

🧪 PR contains tests

🔒 No security concerns identified

⚡ Recommended focus areas for review Logic Error The metadata filtering logic appears to be incorrectly implemented. The code iterates through metadata_filter items and adds individual conditions for each key-value pair, but this may not properly handle complex metadata queries or JSON operations that were likely intended. if metadata_filter: for key, value in metadata_filter.items(): builder.add_condition(" AND d.metadata->>{}::text = {}", key, str(value)) Incomplete Validation The SQL keyword blocklist in sanitize_identifier function contains only basic keywords. More comprehensive validation should include additional SQL keywords, functions, and PostgreSQL-specific commands that could be used in injection attacks. sql_keywords = { "select", "insert", "update", "delete", "drop", "create", "alter", "table", "from", "where", "join", "union", "grant", "revoke", } if identifier.lower() in sql_keywords: raise HTTPException( status_code=400, detail=f"Invalid {identifier_type} name: '{identifier}' is a reserved SQL keyword", ) Parameter Mismatch The add_condition method in SafeQueryBuilder counts placeholders but doesn't validate that the condition string is properly formatted or that parameter types are appropriate for the intended SQL operations. def add_condition(self, condition: str, *params: Any) -> "SafeQueryBuilder": """ Add a WHERE condition with parameterized values. Args: condition: The condition string with placeholders (e.g., "user_id = {}" or "date BETWEEN {} AND {}") *params: The parameter values Returns: Self for method chaining """ # Count the number of {} placeholders in the condition placeholder_count = condition.count("{}") if placeholder_count != len(params): msg = f"Expected {placeholder_count} parameters, got {len(params)}" raise ValueError(msg) # Replace each {} with the appropriate parameter placeholder formatted_condition = condition for param in params: self._param_counter += 1 formatted_condition = formatted_condition.replace( "{}", f"${self._param_counter}", 1 ) self.params.append(param) self.query_parts.append(formatted_condition) return self

[ellipsis-dev]

Important

Looks good to me! 👍

Reviewed everything up to 552b5b2 in 1 minute and 5 seconds. Click for details.

• Reviewed 1297 lines of code in 14 files
• Skipped 0 files when reviewing.
• Skipped posting 14 draft comments. View those below.
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1. AGENTS.md:81

• Draft comment:
  Good addition of SQL Safety patterns. The guidelines and examples are clear.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

2. CONTRIBUTING.md:182

• Draft comment:
  Security guidelines for DB interactions and SQL injection prevention are well-documented.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

3. agents-api/AGENTS.md:75

• Draft comment:
  The SQL Safety Requirements section is clear and comprehensive.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

4. agents-api/README.md:15

• Draft comment:
  The new 'Queries' section clearly mentions SQL safety utilities, aiding new contributors.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

5. agents-api/agents_api/queries/AGENTS.md:11

• Draft comment:
  The note to ALWAYS use SQL safety utilities reinforces best practices.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

6. agents-api/agents_api/queries/agents/list_agents.py:92

• Draft comment:
  Using .replace() for inserting the metadata filter query is effective. Ensure consistency with SafeQueryBuilder usage in other modules.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

7. agents-api/agents_api/queries/docs/bulk_delete_docs.py:56

• Draft comment:
  Concatenating metadata_conditions is acceptable if build_metadata_filter_conditions handles sanitization. Consider double-checking its safety.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

8. agents-api/agents_api/queries/docs/list_docs.py:110

• Draft comment:
  Effective use of SafeQueryBuilder for building the query with metadata filters and safe ORDER BY clauses.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

9. agents-api/agents_api/queries/entries/list_entries.py:101

• Draft comment:
  Using safe_format_query for the ORDER BY clause ensures parameter validation; good practice.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

10. agents-api/agents_api/queries/files/list_files.py:67

• Draft comment:
  The use of SafeQueryBuilder for dynamic query construction and filtering is well implemented.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

11. agents-api/agents_api/queries/sql_utils.py:147

• Draft comment:
  The SQL utilities, including sanitize_identifier, validate_sort_field/direction, and SafeQueryBuilder, are well implemented and documented.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

12. agents-api/docs/SQL_INJECTION_PREVENTION.md:1

• Draft comment:
  Comprehensive documentation on SQL injection prevention mechanisms is added. Excellent detail on vulnerabilities and best practices.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

13. agents-api/examples/sql_injection_prevention_demo.py:20

• Draft comment:
  The demo script effectively illustrates various SQL injection prevention techniques.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

14. agents-api/tests/test_sql_injection_prevention.py:18

• Draft comment:
  Comprehensive test coverage for SQL injection prevention ensures all functions behave as expected.
• Reason this comment was not posted:
  Confidence changes required: 0% <= threshold 50% None

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[qodo-merge-for-open-source]

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