[Feature] Advanced Security and Safety Mechanisms System

[Avtrkrb]

Description

Implement comprehensive security and safety mechanisms to enhance Nanocoder's protection against malicious inputs, dangerous operations, and unsafe tool execution. Currently, Nanocoder has basic security with simple command injection prevention and basic tool approval systems, but lacks comprehensive security validation, context-aware safety analysis, and advanced risk assessment capabilities. The system needs multi-layered security validation, dynamic security rules, advanced tool risk assessment, and adaptive safety enforcement to match industry-leading CLI coding agentic tools.

The feature will implement:

• Multi-layered security validation with context-aware analysis
• Dynamic security rule engine with pattern recognition
• Advanced tool risk assessment with context-aware constraints
• Adaptive safety enforcement with multi-factor permission system
• Comprehensive safety framework with risk monitoring

Use Case

Current Problem:

• Basic command injection prevention without comprehensive security
• Simple input validation without advanced sanitization
• Limited tool safety checking without comprehensive risk assessment
• Static security rules without dynamic analysis
• No comprehensive safety framework with ad-hoc mechanisms

Target Scenarios:

1. Multi-layered Security: Comprehensive validation across multiple security layers
2. Context-aware Analysis: Dynamic security based on conversation and tool context
3. Advanced Risk Assessment: Comprehensive tool risk evaluation with context factors
4. Adaptive Safety: Dynamic safety enforcement based on risk levels
5. Pattern Recognition: Security pattern detection and learning

Proposed Solution

Phase 1: Foundation - Comprehensive Security Validation (2-3 weeks)

• Implement multi-layered security validation system
• Add context-aware security analysis capabilities
• Create SecurityValidator with layered validation
• Create ContextAwareSecurityAnalyzer for dynamic analysis
• Maintain backward compatibility with existing security patterns

Phase 2: Security Management - Dynamic Security Rules (3-4 weeks)

• Implement dynamic security rule engine
• Add security pattern recognition system
• Create DynamicSecurityRuleEngine for rule evaluation
• Create SecurityPatternRecognizer for pattern matching
• Enhance multi-factor validation capabilities

Phase 3: Safety Foundation - Advanced Tool Risk Assessment (4-5 weeks)

• Implement comprehensive tool risk assessment
• Add context-aware safety constraints
• Create ToolRiskAssessor for risk evaluation
• Create SafetyConstraintSystem for constraint management
• Enhance multi-factor permission system

Phase 4: Advanced Safety - Adaptive Safety Enforcement (3-4 weeks)

• Implement adaptive safety enforcement
• Add safety success monitoring
• Create AdaptiveSafetyEnforcer for dynamic enforcement
• Create SafetySuccessMonitor for trend analysis
• Enhance context-aware permission system

Technical Implementation

Core Components

// Security validation framework
export class SecurityValidator {
  private validationLayers: SecurityValidationLayer[];

  validateInput(input: string, context: ValidationContext): SecurityResult {
    for (const layer of this.validationLayers) {
      const result = layer.validate(input, context);
      if (!result.valid) {
        return result;
      }
    }

    return { valid: true };
  }

  addValidationLayer(layer: SecurityValidationLayer): void {
    this.validationLayers.push(layer);
  }
}

// Context-aware security analyzer
export class ContextAwareSecurityAnalyzer {
  analyzeSecurityContext(
    input: string,
    context: SecurityContext
  ): SecurityAnalysis {
    const baseAnalysis = this.performBaseAnalysis(input);
    const contextAnalysis = this.analyzeContext(context);

    return {
      ...baseAnalysis,
      contextRisk: contextAnalysis.riskLevel,
      contextFactors: contextAnalysis.factors
    };
  }
}

// Dynamic security rule engine
export class DynamicSecurityRuleEngine {
  private rules: SecurityRule[];
  private context: SecurityContext;

  evaluateRules(input: string): RuleEvaluationResult {
    const results = this.rules.map(rule =>
      rule.evaluate(input, this.context)
    );

    return this.aggregateResults(results);
  }

  updateContext(context: SecurityContext): void {
    this.context = context;
  }

  addRule(rule: SecurityRule): void {
    this.rules.push(rule);
  }
}

// Security pattern recognizer
export class SecurityPatternRecognizer {
  private patterns: SecurityPattern[];

  recognizePatterns(input: string): PatternRecognitionResult {
    const matchedPatterns = this.patterns.filter(
      pattern => this.matchesPattern(input, pattern)
    );

    return {
      patterns: matchedPatterns,
      riskScore: this.calculateRiskScore(matchedPatterns)
    };
  }

  learnPattern(pattern: SecurityPattern): void {
    this.patterns.push(pattern);
  }
}

// Tool risk assessor
export class ToolRiskAssessor {
  private riskFactors: RiskFactor[];

  assessToolRisk(
    tool: Tool,
    context: SafetyContext
  ): ToolRiskAssessment {
    const baseRisk = this.calculateBaseRisk(tool);
    const contextRisk = this.calculateContextRisk(context);

    return {
      toolId: tool.name,
      baseRisk,
      contextRisk,
      totalRisk: baseRisk + contextRisk,
      riskLevel: this.determineRiskLevel(baseRisk + contextRisk)
    };
  }
}

// Safety constraint system
export class SafetyConstraintSystem {
  private constraints: SafetyConstraint[];

  evaluateConstraints(
    tool: Tool,
    context: SafetyContext
  ): ConstraintEvaluationResult {
    const results = this.constraints.map(constraint =>
      constraint.evaluate(tool, context)
    );

    return this.aggregateConstraintResults(results);
  }
}

// Adaptive safety enforcer
export class AdaptiveSafetyEnforcer {
  private enforcementStrategies: SafetyEnforcementStrategy[];

  enforceSafety(
    tool: Tool,
    context: SafetyContext
  ): SafetyEnforcementResult {
    const strategy = this.selectEnforcementStrategy(tool, context);
    return strategy.enforce(tool, context);
  }

  selectEnforcementStrategy(
    tool: Tool,
    context: SafetyContext
  ): SafetyEnforcementStrategy {
    const suitableStrategies = this.enforcementStrategies.filter(
      strategy => strategy.isApplicable(tool, context)
    );

    return this.predictBestStrategy(suitableStrategies, tool, context);
  }
}

// Safety success monitor
export class SafetySuccessMonitor {
  private successMetrics: SafetySuccessMetrics;

  monitorEnforcement(
    result: SafetyEnforcementResult,
    context: SafetyContext
  ): void {
    this.updateMetrics(result, context);
    this.analyzeSafetyTrends();
  }

  getSafetyRecommendations(): SafetyRecommendation[] {
    return this.generateRecommendations();
  }
}

Integration Points

• Tool Execution: Enhance source/hooks/chat-handler/conversation/tool-executor.tsx with security validation
• Conversation Loop: Integrate with source/hooks/chat-handler/conversation/conversation-loop.tsx
• Input Validation: Enhance source/tools/file-tools-path-validation.spec.ts
• Command Execution: Integrate with source/tools/execute-bash.tsx
• Approval System: Enhance source/hooks/chat-handler/utils/needs-approval.spec.tsx
• Mode Context: Integrate with source/context/mode-context.ts

Files to Modify/Create

• source/security/security-validator.ts (new) - Multi-layered validation
• source/security/context-analyzer.ts (new) - Context-aware analysis
• source/security/rule-engine.ts (new) - Dynamic rule engine
• source/security/pattern-recognizer.ts (new) - Pattern recognition
• source/safety/risk-assessor.ts (new) - Risk assessment
• source/safety/safety-constraints.ts (new) - Safety constraints
• source/safety/adaptive-enforcer.ts (new) - Adaptive enforcement
• source/safety/safety-monitor.ts (new) - Safety monitoring
• source/hooks/chat-handler/conversation/tool-executor.tsx (modify) - Enhanced validation
• source/tools/execute-bash.tsx (enhance) - Advanced command validation
• source/hooks/chat-handler/utils/needs-approval.spec.tsx (enhance) - Risk-based approval
• source/context/mode-context.ts (enhance) - Context-aware permissions

Alternatives Considered

1. Simple Security Layer: Considered but rejected for limited validation scope
2. Static Rule Engine: Rejected for inability to adapt to context
3. Basic Risk Assessment: Rejected for lack of comprehensive analysis
4. Monolithic Security System: Rejected for poor maintainability and scalability

Additional Context

• I have searched existing issues to ensure this is not a duplicate
• This feature aligns with the project's goals (local-first AI assistance)
• The implementation considers local LLM performance constraints
• Security is prioritized for local usage

Performance Considerations

• Lightweight validation algorithms for local LLM constraints
• Efficient data structures for security management
• Incremental validation to minimize memory usage
• Optimized rule evaluation performance

Local LLM Adaptations

• Memory-optimized security context storage
• Efficient pattern matching algorithms
• Lightweight rule representation
• Resource-aware validation limits

Security Enhancement Benefits

• Comprehensive multi-layered security validation
• Context-aware analysis with dynamic rules
• Advanced tool risk assessment with context factors
• Adaptive safety enforcement with monitoring
• Pattern recognition with learning capabilities

Implementation Notes (optional)

Key Integration Points

• Integrate with existing tool execution security
• Connect to conversation loop for validation
• Enhance input validation with security layers
• Add to command execution for advanced validation
• Connect with approval system for risk-based decisions

Testing Strategy

• Unit tests for security validation algorithms
• Integration tests for safety enforcement
• Performance tests for rule engine evaluation
• Memory usage monitoring for security analysis
• Pattern recognition effectiveness testing

Migration Path

• All new features will be optional and backward compatible
• Existing security patterns remain as fallback
• Gradual rollout with feature flags
• User preferences for security validation levels

Success Metrics

• Security Coverage: 95%+ of potential security threats detected
• Validation Performance: <50ms for typical security validation
• Risk Assessment Accuracy: 90%+ accurate risk classification
• Memory Usage: Keep security validation overhead under 15%
• False Positive Rate: <5% false positive security alerts
• User Satisfaction: Positive feedback on security and safety improvements