--- name: detecting-modbus-protocol-anomalies-79dc25a2c8c9 description: Detect anomalies in Modbus/TCP and Modbus RTU industrial traffic via function code monitoring, register range validation, timing analysis, and deep packet inspection, using Zeek's Modbus analyzer, Suricata IDS with OT rules, and Python Markov chain models of normal transaction sequences. Use for deploying Modbus IDS in OT environments, baselining polling patterns, investigating suspicious Modbus traffic, or building function code allowlists. domain: cybersecurity subdomain: ot-ics-security tags: - ot-security - ics - scada - industrial-control - iec62443 - modbus - protocol-anomaly version: 1.0.0 author: mahipal license: Apache-2.0 nist_ai_rmf: - MEASURE-2.7 - MAP-5.1 - MANAGE-2.4 atlas_techniques: - AML.T0070 - AML.T0066 - AML.T0082 nist_csf: - PR.IR-01 - DE.CM-01 - ID.AM-05 - GV.OC-02 mitre_attack: - T1078 - T1190 - T1059 - T0816 - T0836 --- # Detecting Modbus Protocol Anomalies ## When to Use - When deploying Modbus-specific intrusion detection in an OT environment - When building baseline models for deterministic Modbus polling patterns - When investigating suspicious Modbus traffic flagged by OT monitoring tools - When implementing function code allowlisting on industrial firewalls - When detecting unauthorized Modbus write commands that could manipulate process setpoints **Do not use** for securing Modbus communications end-to-end (Modbus has no native security; see implementing-network-segmentation-for-ot for firewall-based controls), for non-Modbus protocol monitoring (see detecting-anomalies-in-industrial-control-systems for multi-protocol), or for active fuzzing of Modbus implementations (see performing-plc-firmware-security-analysis). ## Prerequisites - Network SPAN/TAP access to monitor Modbus/TCP traffic (port 502) - Zeek (formerly Bro) with Modbus protocol analyzer or Suricata with OT rulesets - Python 3.9+ with scapy and pymodbus for custom analysis - Baseline capture of normal Modbus traffic (minimum 1-2 weeks) - Documentation of authorized Modbus clients, function codes, and register maps ## Workflow ### Step 1: Capture and Parse Modbus Traffic Deploy passive monitoring to capture all Modbus/TCP traffic and parse it into structured records for analysis. ```python #!/usr/bin/env python3 """Modbus Protocol Anomaly Detection System. Monitors Modbus/TCP traffic for anomalies including unauthorized function codes, unusual register access, timing deviations, and rogue client devices. """ import json import struct import sys import time from collections import defaultdict, deque from dataclasses import dataclass, field from datetime import datetime from statistics import mean, stdev try: from scapy.all import sniff, rdpcap, IP, TCP except ImportError: print("Install scapy: pip install scapy") sys.exit(1) MODBUS_FUNCTION_CODES = { 1: ("Read Coils", "read"), 2: ("Read Discrete Inputs", "read"), 3: ("Read Holding Registers", "read"), 4: ("Read Input Registers", "read"), 5: ("Write Single Coil", "write"), 6: ("Write Single Register", "write"), 7: ("Read Exception Status", "diagnostic"), 8: ("Diagnostics", "diagnostic"), 11: ("Get Comm Event Counter", "diagnostic"), 12: ("Get Comm Event Log", "diagnostic"), 15: ("Write Multiple Coils", "write"), 16: ("Write Multiple Registers", "write"), 17: ("Report Slave ID", "diagnostic"), 22: ("Mask Write Register", "write"), 23: ("Read/Write Multiple Registers", "read_write"), 43: ("Encapsulated Interface Transport", "diagnostic"), } @dataclass class ModbusAnomaly: timestamp: str anomaly_type: str severity: str src_ip: str dst_ip: str unit_id: int func_code: int detail: str mitre_technique: str = "" @dataclass class ModbusSession: """Tracks state for a Modbus master-slave session.""" src_ip: str dst_ip: str func_codes_seen: dict = field(default_factory=lambda: defaultdict(int)) register_ranges: set = field(default_factory=set) intervals: list = field(default_factory=lambda: deque(maxlen=500)) last_timestamp: float = 0 request_count: int = 0 write_count: int = 0 class ModbusAnomalyDetector: """Detects anomalies in Modbus/TCP traffic.""" def __init__(self): self.sessions = {} self.baseline_sessions = {} self.anomalies = [] self.authorized_clients = set() self.authorized_func_codes = {} # per-session allowed FCs self.packet_count = 0 def set_authorized_clients(self, clients): """Set list of authorized Modbus client IPs.""" self.authorized_clients = set(clients) def set_authorized_func_codes(self, session_key, func_codes): """Set allowed function codes for a specific session.""" self.authorized_func_codes[session_key] = set(func_codes) def load_baseline(self, baseline_file): """Load baseline profiles from previous capture analysis.""" with open(baseline_file) as f: baseline = json.load(f) for key, data in baseline.get("modbus_baselines", {}).items(): self.baseline_sessions[key] = data self.authorized_func_codes[key] = set(data.get("allowed_function_codes", [])) print(f"[*] Loaded {len(self.baseline_sessions)} Modbus baselines") def process_packet(self, pkt): """Process a single packet for Modbus anomaly detection.""" if not pkt.haslayer(TCP) or not pkt.haslayer(IP): return # Check for Modbus/TCP (port 502) if pkt[TCP].dport != 502 and pkt[TCP].sport != 502: return payload = bytes(pkt[TCP].payload) if len(payload) < 8: return self.packet_count += 1 timestamp = float(pkt.time) ts_str = datetime.fromtimestamp(timestamp).isoformat() # Parse MBAP header try: trans_id = struct.unpack(">H", payload[0:2])[0] proto_id = struct.unpack(">H", payload[2:4])[0] length = struct.unpack(">H", payload[4:6])[0] unit_id = payload[6] func_code = payload[7] except (IndexError, struct.error): return # Determine direction if pkt[TCP].dport == 502: src_ip = pkt[IP].src dst_ip = pkt[IP].dst is_request = True else: src_ip = pkt[IP].dst dst_ip = pkt[IP].src is_request = False if not is_request: return # Only analyze requests session_key = f"{src_ip}->{dst_ip}" # Get or create session if session_key not in self.sessions: self.sessions[session_key] = ModbusSession(src_ip=src_ip, dst_ip=dst_ip) session = self.sessions[session_key] session.request_count += 1 session.func_codes_seen[func_code] += 1 # ── Anomaly Detection Rules ── # Rule 1: Unauthorized Modbus client if self.authorized_clients and src_ip not in self.authorized_clients: self.anomalies.append(ModbusAnomaly( timestamp=ts_str, anomaly_type="UNAUTHORIZED_CLIENT", severity="critical", src_ip=src_ip, dst_ip=dst_ip, unit_id=unit_id, func_code=func_code, detail=f"Modbus request from unauthorized client {src_ip}", mitre_technique="T0886 - Remote Services", )) # Rule 2: Unauthorized function code allowed_fcs = self.authorized_func_codes.get(session_key) if allowed_fcs and func_code not in allowed_fcs: fc_info = MODBUS_FUNCTION_CODES.get(func_code, (f"Unknown FC{func_code}", "unknown")) severity = "critical" if fc_info[1] == "write" else "high" self.anomalies.append(ModbusAnomaly( timestamp=ts_str, anomaly_type="UNAUTHORIZED_FUNCTION_CODE", severity=severity, src_ip=src_ip, dst_ip=dst_ip, unit_id=unit_id, func_code=func_code, detail=f"FC {func_code} ({fc_info[0]}) not in allowlist {sorted(allowed_fcs)}", mitre_technique="T0855 - Unauthorized Command Message", )) # Rule 3: Write operation detection if func_code in (5, 6, 15, 16, 22, 23): session.write_count += 1 fc_name = MODBUS_FUNCTION_CODES.get(func_code, ("Unknown", ""))[0] # Extract register address if len(payload) >= 10: register_addr = struct.unpack(">H", payload[8:10])[0] session.register_ranges.add((func_code, register_addr)) self.anomalies.append(ModbusAnomaly( timestamp=ts_str, anomaly_type="WRITE_OPERATION", severity="high", src_ip=src_ip, dst_ip=dst_ip, unit_id=unit_id, func_code=func_code, detail=f"Write: {fc_name} to register {register_addr} from {src_ip}", mitre_technique="T0836 - Modify Parameter", )) # Rule 4: Timing anomaly if session.last_timestamp > 0: interval = (timestamp - session.last_timestamp) * 1000 # ms session.intervals.append(interval) baseline = self.baseline_sessions.get(session_key) if baseline and len(session.intervals) > 10: expected_interval = baseline.get("polling_interval_avg_sec", 0) * 1000 expected_std = baseline.get("polling_interval_stddev", 0) * 1000 if expected_std > 0: z_score = abs(interval - expected_interval) / expected_std if z_score > 5.0: self.anomalies.append(ModbusAnomaly( timestamp=ts_str, anomaly_type="TIMING_ANOMALY", severity="medium", src_ip=src_ip, dst_ip=dst_ip, unit_id=unit_id, func_code=func_code, detail=( f"Interval {interval:.0f}ms vs baseline " f"{expected_interval:.0f}ms (z={z_score:.1f})" ), mitre_technique="T0831 - Manipulation of Control", )) # Rule 5: Protocol violation - invalid protocol ID if proto_id != 0: self.anomalies.append(ModbusAnomaly( timestamp=ts_str, anomaly_type="PROTOCOL_VIOLATION", severity="high", src_ip=src_ip, dst_ip=dst_ip, unit_id=unit_id, func_code=func_code, detail=f"Non-standard protocol ID {proto_id} (expected 0)", mitre_technique="T0830 - Man in the Middle", )) # Rule 6: Broadcast write (unit ID 0) if unit_id == 0 and func_code in (5, 6, 15, 16): self.anomalies.append(ModbusAnomaly( timestamp=ts_str, anomaly_type="BROADCAST_WRITE", severity="critical", src_ip=src_ip, dst_ip=dst_ip, unit_id=unit_id, func_code=func_code, detail="Broadcast write command (unit ID 0) affects ALL slaves", mitre_technique="T0855 - Unauthorized Command Message", )) session.last_timestamp = timestamp def analyze_pcap(self, pcap_file): """Analyze pcap file for Modbus anomalies.""" print(f"[*] Analyzing {pcap_file}...") packets = rdpcap(pcap_file) for pkt in packets: self.process_packet(pkt) print(f"[*] Processed {self.packet_count} Modbus packets") def generate_report(self): """Generate anomaly detection report.""" print(f"\n{'='*70}") print("MODBUS PROTOCOL ANOMALY DETECTION REPORT") print(f"{'='*70}") print(f"Packets analyzed: {self.packet_count}") print(f"Sessions tracked: {len(self.sessions)}") print(f"Anomalies detected: {len(self.anomalies)}") severity_counts = defaultdict(int) type_counts = defaultdict(int) for a in self.anomalies: severity_counts[a.severity] += 1 type_counts[a.anomaly_type] += 1 print(f"\nBy Severity:") for sev in ["critical", "high", "medium", "low"]: if severity_counts[sev]: print(f" {sev.upper()}: {severity_counts[sev]}") print(f"\nBy Type:") for atype, count in sorted(type_counts.items(), key=lambda x: -x[1]): print(f" {atype}: {count}") print(f"\nTop Anomalies:") for a in self.anomalies[:15]: print(f" [{a.severity.upper()}] {a.anomaly_type}: {a.detail}") if __name__ == "__main__": detector = ModbusAnomalyDetector() if len(sys.argv) > 1: # Load baseline if provided if len(sys.argv) > 2: detector.load_baseline(sys.argv[2]) detector.analyze_pcap(sys.argv[1]) detector.generate_report() else: print("Usage: python modbus_detector.py [baseline.json]") ``` ## Key Concepts | Term | Definition | |------|------------| | Modbus/TCP | Industrial protocol running on TCP port 502, consisting of an MBAP header and PDU with function code and data | | Function Code | Modbus command identifier (FC1-4: reads, FC5-6/15-16: writes, FC8: diagnostics) determining the operation type | | MBAP Header | Modbus Application Protocol header containing transaction ID, protocol ID (0x0000), length, and unit ID | | Unit ID | Modbus address (0-247) identifying the target slave device; unit ID 0 is broadcast to all slaves | | Register Map | Vendor-specific mapping of Modbus register addresses to process variables (e.g., register 40001 = reactor temperature) | | Function Code Allowlist | Security policy defining which Modbus function codes are permitted from each source IP to each target device | ## Tools & Systems - **Zeek Modbus Analyzer**: Network security monitor with built-in Modbus/TCP protocol analysis and logging - **Suricata with ET Open ICS rules**: IDS/IPS with Modbus-specific detection rules for command injection and anomalies - **Wireshark Modbus Dissector**: Protocol analyzer with full Modbus/TCP and Modbus RTU decoding - **PyModbus**: Python Modbus library for building custom monitoring and testing tools ## Output Format ``` Modbus Protocol Anomaly Detection Report ========================================== Capture Period: YYYY-MM-DD to YYYY-MM-DD Packets Analyzed: [N] Sessions: [N] ANOMALIES: [N] UNAUTHORIZED_CLIENT: [N] UNAUTHORIZED_FUNCTION_CODE: [N] WRITE_OPERATION: [N] TIMING_ANOMALY: [N] BROADCAST_WRITE: [N] ``` --- Source attribution: costrict-plugins-repo Original project: https://github.com/costrict-plugins-repo/mukul975-anthropic-cybersecurity-skills-cybersecurity-skills/blob/1b344d155f00bae5cf27d8eba9508e8f5050d904/skills/detecting-modbus-protocol-anomalies/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Dave AI. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. 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See the License for the specific language governing permissions and limitations under the License. # Dave AI resource metadata Creator / publisher: costrict-plugins-repo Original project: https://github.com/costrict-plugins-repo/mukul975-anthropic-cybersecurity-skills-cybersecurity-skills/blob/1b344d155f00bae5cf27d8eba9508e8f5050d904/skills/detecting-modbus-protocol-anomalies/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Development & Engineering, Operations Roles: Data Analyst, Data Scientist, ML / AI Engineer, Operations Manager, Security Engineer Specialties: Specialty not specified Tools: Python, Suricata, Zeek Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: cb13cc6cc42e1f4978f99d3e4c1078d9219d79210c2d0ea60be3a9b4591f9d1c