Wireshark MCP Server

# 🦈 Wireshark Advanced Tools Implementation Guide ## 📋 Complete Implementation Roadmap ### 1. **PCAP Time Slicer** 🕐 #### Research Findings: - **Tool**: `editcap` with `-A` (start time) and `-B` (stop time) options - **Time Format**: `YYYY-MM-DDThh:mm:ss[.nnnnnnnnn][Z|+-hh:mm]` or Unix epoch - **Capabilities**: Extract exact time windows from large captures #### Design Architecture: ```python class WiresharkPCAPTimeSlicer: """Extract specific time windows from PCAP files""" def __init__(self): self.tool = "editcap" self.supported_formats = ["pcap", "pcapng"] async def slice_by_time_range( self, input_file: str, start_time: str, # ISO format or epoch end_time: str, output_file: str = None, preserve_comments: bool = True ) -> Dict[str, Any]: """Extract packets within time range""" async def slice_by_duration( self, input_file: str, start_time: str, duration_seconds: int, output_file: str = None ) -> Dict[str, Any]: """Extract packets for specific duration""" async def slice_relative_time( self, input_file: str, start_offset: float, # Seconds from first packet end_offset: float, output_file: str = None ) -> Dict[str, Any]: """Extract using relative time offsets""" ``` #### Implementation Requirements: - Time format validation and conversion - Progress tracking for large files - Multi-file time range extraction - Timezone handling ### 2. **PCAP Splitter** 📦 #### Research Findings: - **Options**: - `-c <packets per file>`: Split by packet count - `-i <seconds per file>`: Split by time intervals - `-C`: Split by file size (with choplen) - **Output**: Creates numbered files (e.g., output_00001.pcap) #### Design Architecture: ```python class WiresharkPCAPSplitter: """Split PCAP files by various criteria""" async def split_by_packets( self, input_file: str, packets_per_file: int, output_prefix: str = None ) -> Dict[str, Any]: """Split by packet count""" async def split_by_time( self, input_file: str, seconds_per_file: int, output_prefix: str = None ) -> Dict[str, Any]: """Split by time intervals""" async def split_by_size( self, input_file: str, mb_per_file: int, output_prefix: str = None ) -> Dict[str, Any]: """Split by file size""" async def split_by_protocol( self, input_file: str, output_prefix: str = None ) -> Dict[str, Any]: """Advanced: Split by protocol type""" ``` ### 3. **PCAP Merger** 🔄 #### Research Findings: - **Tool**: `mergecap` - **Modes**: - Default: Merge chronologically by timestamp - `-a`: Append/concatenate mode (ignore timestamps) - **Features**: Handles different encapsulation types #### Design Architecture: ```python class WiresharkPCAPMerger: """Intelligently merge multiple PCAP files""" async def merge_chronological( self, input_files: List[str], output_file: str = None, remove_duplicates: bool = False ) -> Dict[str, Any]: """Merge files in timestamp order""" async def merge_append( self, input_files: List[str], output_file: str = None ) -> Dict[str, Any]: """Concatenate files sequentially""" async def merge_with_filter( self, input_files: List[str], filter_expression: str, output_file: str = None ) -> Dict[str, Any]: """Merge only packets matching filter""" ``` ### 4. **Hex-to-PCAP Converter** 🔢 #### Research Findings: - **Tool**: `text2pcap` - **Input Formats**: Hex dumps, od output, tcpdump hex - **Options**: - `-e`: Ethernet header - `-i`: IP header - `-u`: UDP header - `-t`: TCP header - `-s`: SCTP header #### Design Architecture: ```python class WiresharkHexToPCAP: """Convert hex dumps to analyzable PCAP format""" async def convert_hex_dump( self, hex_input: str, # File path or hex string output_file: str = None, encapsulation: str = "ethernet", add_fake_headers: bool = True ) -> Dict[str, Any]: """Convert hex to PCAP with appropriate headers""" async def convert_log_file( self, log_file: str, pattern: str, # Regex for hex extraction output_file: str = None ) -> Dict[str, Any]: """Extract hex from logs and convert""" ``` ### 5. **HTTP Deep Analyzer** 🌐 #### Research Findings: - **Tool**: `tshark` with HTTP filters - **Statistics**: `-z http,stat`, `-z http,tree` - **Fields**: http.request, http.response, http.file_data #### Design Architecture: ```python class WiresharkHTTPAnalyzer: """Deep HTTP/HTTPS transaction analysis""" async def extract_http_flows( self, input_file: str, include_bodies: bool = True, decode_gzip: bool = True ) -> Dict[str, Any]: """Extract complete HTTP transactions""" async def analyze_http_performance( self, input_file: str ) -> Dict[str, Any]: """HTTP timing and performance metrics""" async def extract_http_objects( self, input_file: str, output_dir: str = None ) -> Dict[str, Any]: """Extract files transferred over HTTP""" ``` ### 6. **DNS Query Analyzer** 🔍 #### Research Findings: - **Tool**: `tshark` with DNS statistics - **Options**: `-z dns,tree`, `-Y dns` - **Fields**: dns.qry.name, dns.resp.time, dns.flags #### Design Architecture: ```python class WiresharkDNSAnalyzer: """DNS traffic intelligence and analysis""" async def analyze_dns_queries( self, input_file: str, group_by_domain: bool = True ) -> Dict[str, Any]: """Analyze DNS query patterns""" async def detect_dns_tunneling( self, input_file: str, entropy_threshold: float = 3.5 ) -> Dict[str, Any]: """Detect potential DNS tunneling""" async def dns_response_analysis( self, input_file: str ) -> Dict[str, Any]: """Analyze DNS response times and failures""" ``` ### 7. **SSL/TLS Inspector** 🔐 #### Research Findings: - **Tool**: `tshark` with SSL/TLS dissectors - **Decryption**: Requires keylog file or RSA keys - **Options**: `-o ssl.keylog_file:path` #### Design Architecture: ```python class WiresharkSSLInspector: """SSL/TLS traffic inspection and analysis""" async def analyze_ssl_handshakes( self, input_file: str ) -> Dict[str, Any]: """Analyze SSL/TLS handshakes""" async def decrypt_ssl_traffic( self, input_file: str, keylog_file: str = None, rsa_key_file: str = None ) -> Dict[str, Any]: """Decrypt SSL/TLS traffic with keys""" async def ssl_certificate_analysis( self, input_file: str ) -> Dict[str, Any]: """Extract and analyze certificates""" ``` ### 8. **Latency Profiler** ⏱️ #### Research Findings: - **Tool**: `tshark` with time analysis - **Fields**: frame.time_delta, tcp.time_relative - **Statistics**: `-z io,stat` #### Design Architecture: ```python class WiresharkLatencyProfiler: """Network latency and performance profiling""" async def analyze_tcp_latency( self, input_file: str, percentiles: List[int] = [50, 90, 95, 99] ) -> Dict[str, Any]: """TCP RTT and latency analysis""" async def analyze_application_latency( self, input_file: str, protocol: str = "http" ) -> Dict[str, Any]: """Application-level latency metrics""" async def generate_latency_heatmap( self, input_file: str, time_bucket_seconds: int = 60 ) -> Dict[str, Any]: """Time-based latency visualization data""" ``` ### 9. **Threat Detector** 🛡️ #### Research Findings: - **Patterns**: Port scans, DDoS, malware signatures - **Integration**: ML models for anomaly detection - **Tools**: Combine multiple tshark filters #### Design Architecture: ```python class WiresharkThreatDetector: """AI-powered network threat detection""" async def detect_port_scans( self, input_file: str, threshold_ports: int = 10, time_window: int = 60 ) -> Dict[str, Any]: """Detect port scanning activity""" async def detect_ddos_patterns( self, input_file: str ) -> Dict[str, Any]: """Identify DDoS attack patterns""" async def ml_anomaly_detection( self, input_file: str, model_path: str = None ) -> Dict[str, Any]: """ML-based anomaly detection""" ``` ### 10. **Remote Capture** 🌍 #### Research Findings: - **Tool**: `sshdump` (if available) or SSH + tcpdump - **Requirements**: SSH access to remote hosts - **Features**: Multi-host synchronization #### Design Architecture: ```python class WiresharkRemoteCapture: """Distributed remote packet capture""" async def capture_single_host( self, host: str, username: str, password: str = None, key_file: str = None, interface: str = "any", filter: str = "", duration: int = 60 ) -> Dict[str, Any]: """Capture from single remote host""" async def capture_multi_host( self, hosts: List[Dict[str, Any]], synchronized: bool = True ) -> Dict[str, Any]: """Synchronized multi-host capture""" ``` ## 🚀 Implementation Strategy ### Phase 1: Core PCAP Manipulation (Week 1) 1. Implement PCAP Time Slicer 2. Implement PCAP Splitter 3. Implement PCAP Merger 4. Implement Hex-to-PCAP Converter ### Phase 2: Protocol Analysis (Week 2) 1. Implement HTTP Deep Analyzer 2. Implement DNS Query Analyzer 3. Implement SSL/TLS Inspector ### Phase 3: Advanced Analysis (Week 3) 1. Implement Latency Profiler 2. Implement Threat Detector 3. Implement Remote Capture ### 📦 Integration with MCP Server Each tool will be integrated as a new MCP endpoint: - `wireshark_pcap_time_slice` - `wireshark_pcap_split` - `wireshark_pcap_merge` - `wireshark_hex_to_pcap` - `wireshark_http_analyze` - `wireshark_dns_analyze` - `wireshark_ssl_inspect` - `wireshark_latency_profile` - `wireshark_threat_detect` - `wireshark_remote_capture` ### 🔧 Testing Strategy 1. **Unit Tests**: Each function with mock data 2. **Integration Tests**: Real PCAP files 3. **Performance Tests**: Large file handling 4. **Security Tests**: Input validation ### 📚 Documentation Requirements 1. **API Documentation**: Each endpoint 2. **Usage Examples**: Common scenarios 3. **Performance Guidelines**: File size limits 4. **Security Considerations**: Safe handling ## 🎯 Success Metrics - All 10 tools implemented and tested - < 3 second response time for most operations - Support for files up to 1GB - 95%+ test coverage - Zero security vulnerabilities