Key Features

Key Features

SigilAI offers a comprehensive set of security scanning capabilities through its Model Context Protocol (MCP) server. This document outlines the key features and capabilities that make SigilAI an essential security tool for AI systems and developers.

URL Security Scanning

SigilAI's URL scanning tool provides in-depth analysis of web addresses to identify and mitigate potential threats.

Core Capabilities

  • Malicious URL Detection: Identify potential phishing attempts, malware distribution sites, and other harmful web resources

  • Domain Analysis: Extract and analyze domain information to assess legitimacy and trustworthiness

  • Blacklist Checking: Check domains against multiple security blacklists

  • Warning Generation: Produce clear warnings for potentially risky URLs

  • GitHub Link Analysis: Special handling for GitHub links that might be used in anonymized URL attacks

  • MD5 Hashing: Generate unique identifiers for scanned domains for reference and tracking

Implementation Highlights

The URL scanning engine employs a modular approach using the UrlScannerService that:

  1. Extracts domains from submitted URLs

  2. Creates a unique hash identifier for each domain

  3. Employs multiple scanning techniques in parallel

  4. Consolidates findings into a comprehensive safety assessment

  5. Provides structured, actionable results

Source Code Security Analysis

SigilAI's file scanning capabilities allow for deep inspection of source code to identify vulnerabilities, potential exploits, and optimization opportunities.

Core Capabilities

  • Vulnerability Detection: Identify common security vulnerabilities in JavaScript and TypeScript code

  • Multiple Analysis Techniques: Employs a variety of advanced analysis techniques, including:

    • Static Application Security Testing (SAST): For pattern-based semantic code analysis to identify vulnerabilities within the code structure.

    • Software Composition Analysis (SCA): For detecting known vulnerabilities in third-party libraries and dependencies.

    • Proprietary & ML-driven Analysis: Utilizes SigilAI's unique proprietary algorithms and machine learning models to uncover complex vulnerabilities and provide deeper security insights.

  • Performance Optimization: Identify inefficient code patterns and suggest improvements

  • Best Practices Enforcement: Flag deviations from security best practices

Implementation Highlights

flowchart TD
    A[Source Code Input] --> B[File Processing]
    B --> C[Analysis Profile Selection]
    C --> D["Static Code Analysis (SAST)"]
    C --> E["Dependency Scanning (SCA)"]
    C --> ML["Proprietary & ML Analysis"]
    D --> F[Results Consolidation]
    E --> F
    ML --> F
    F --> G[Formatted Findings]

The file scanning system:

  1. Processes source files with path and content information

  2. Supports configurable analysis profiles (e.g., focusing on static analysis, dependency checks, or a comprehensive scan)

  3. Handles file content efficiently

  4. Manages large file transfers with maximum body length settings

  5. Returns structured JSON results for easy interpretation

MCP Server Integration

SigilAI implements the Model Context Protocol to make its security scanning capabilities available to Large Language Models (LLMs) and AI assistants.

Core Capabilities

  • Standardized Tool Interface: Well-defined tool specifications with clear parameter definitions

  • Rich Parameter Validation: Zod schema validation ensures proper inputs

  • Comprehensive Documentation: Built-in instructions and tool descriptions

  • Event-Driven Architecture: Connection and disconnection events for session management

  • SSE Transport Support: Server-Sent Events transport for efficient communication

Implementation Highlights

The SigilAI MCP server:

  1. Provides a consistent interface for all security scanning tools

  2. Includes detailed descriptions and instructions for each tool

  3. Implements robust error handling and logging

  4. Supports real-time connection management

  5. Uses standard transport protocols for wide compatibility

Testing & Diagnostics

SigilAI includes comprehensive testing capabilities to ensure system reliability and provide diagnostic information.

Core Capabilities

  • Test Tool: Simple verification mechanism to confirm server functionality

  • Structured Responses: Consistent JSON formatting with status, message, and timestamp

  • Logging: Detailed logging for system operations and troubleshooting

  • Error Handling: Comprehensive error management with informative messages

Security & Performance Features

Security

  • Input Validation: Strict parameter validation using Zod schemas

  • Error Isolation: Contained error handling to prevent system disruption

  • Logging Controls: Careful management of sensitive information in logs

Performance

  • Efficient Processing: Optimized handling of scanning requests

  • Parallelized Scanning: Multiple scanning engines can run concurrently

  • Scalable Architecture: Design supports growth in scanning capabilities

Future Roadmap

SigilAI is continuously evolving with planned features including:

  • Expanded File Type Support: Additional language and file format scanning

  • Enhanced AI Integration: Deeper integration with AI systems for predictive security

  • Advanced Visualization: Improved result formatting and visualization

  • Entire Codebase Scanning: Support for analyzing complete repositories

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