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CVE-2025-13970: OpenPLC_V3 CSRF Flaw Lets Attackers Trigger Unauthorized Actions via the Web Interface (Urgent Mitigation Guide)
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OpenPLC, Node-RED, BLRAT, and FUXA: A Complete Industrial Automation Workflow from Hardware Control to Visual Monitoring
The combination of OpenPLC, Node-RED, BLRAT, and FUXA enables a lightweight, open-source, end-to-end automation solution. It covers hardware control, logic orchestration, data processing, visualization, and remote maintenance—all without commercial software licensing. This makes the solution ideal for small and medium automation projects, remote operations, education, and secondary development.
Key Application Scenarios
1) EdgePLC Industrial Equipment Monitoring & Control
Goal: Real-time device monitoring, remote control, and automated alarms. Use Cases: Conveyors, motors, temperature/humidity regulation, auxiliary machine control.
Workflow:
OpenPLC: Collects sensor data (temperature, current) and drives actuators (relays, VFDs).
Node-RED: Implements logic such as “If temperature exceeds limit → shut down device → trigger alarm.”
BLRAT: Provides secure remote access and maintenance.
FUXA: Displays real-time charts, device status, alarms, and manual control buttons.
2) ARMxy Smart Home / Laboratory Automation
Goal: Low-cost automation and environment control without commercial smart-home platforms. Use Cases: Lighting control, HVAC, smart curtains, incubators, irrigation systems.
Workflow:
OpenPLC: Using ARMxy X23 (RS485), Y24 (relays), Y01 (DI/DO) to connect sensors and actuators.
Node-RED: Example logic: “Humidity < 40% → start humidifier” or “After 7 PM → open-door triggers auto-light.”
BLRAT: Remote device access.
FUXA: Mobile/PC interface for real-time values and manual control.
3) ARMxy Small-Scale Production Data Traceability
Goal: Capture production counts, runtime, and generate real-time and historical reports. Use Cases: Packaging lines, small assembly machines, product counters.
Workflow:
OpenPLC: Reads count pulses and equipment runtime.
Node-RED: Stores data to MySQL/InfluxDB and calculates metrics (hourly output, failure rate).
BLRAT: Ensures remote maintenance.
FUXA: Displays daily/weekly trends and supports historical queries.
System Architecture
A standard three-layer structure ensures modularity, flexibility, and easy expansion.LayerComponentRoleProtocolsHardware ControlOpenPLCI/O control and sensor acquisitionModbus TCP, MQTTLogic LayerNode-REDAutomation logic, event handling, DB integrationMQTT, HTTP, DB connectorsVisualization LayerFUXAHMI dashboard, data display, manual control, reportingMQTT, WebSocketRemote MaintenanceBLRATSecure remote access for all modulesEncrypted tunnel
The combination of OpenPLC, Node-RED, BLRAT, and FUXA makes it ideal for small to medium-sized automation projects, remote operation, educat
Industrial ARM Edge Gateway with OpenPLC for PID Control
Case Details
The ARM Edge Gateway is the core of data acquisition and control in industrial settings, integrating the open-source OpenPLC control platform. It supports multiple programming methods such as Ladder Diagram (LD), Function Block Diagram (FBD), and Structured Text (ST), with built-in PID control algorithms. The gateway enables local closed-loop control and seamless communication with upper-level systems or cloud platforms via Ethernet, 4G, or WiFi, balancing real-time performance and flexibility.
System Architecture and Functions
Hardware Layer
Sensors: Collect signals such as temperature, pressure, liquid level, flow, and speed (supporting analog/digital inputs).
Actuators: Control devices like motors, valves, heaters, and pumps (supporting analog/relay outputs).
ARM Edge Gateway ARMxy series:
CPU: Cortex-A7/A53/A55, delivering robust performance.
Interfaces: optional RS485/RS121, Ethernet, IO, 4G/WiFi.
Functions: Real-time data acquisition from the field, supporting multiple industrial protocols.
Control Layer
OpenPLC Platform (Running on ARM Gateway):
Complies with IEC 61131-3 standards, supporting multiple programming languages.
Built-in PID function blocks, supporting proportional (Kp), integral (Ki), and derivative (Kd) parameter tuning, with flexible sampling cycle settings.
Supports multi-loop PID control, suitable for complex industrial scenarios.
Application Logic
Typical Control Loops:
Temperature Control: Sensor collects temperature → OpenPLC processes → Adjusts heater.
Pressure Control: Pressure sensor collects data → OpenPLC processes → Controls regulating valve.
Speed Control: Encoder feeds back speed → OpenPLC processes → Adjusts variable frequency drive.
Upper-Level Management
Local Management: Communicates with HMI/SCADA systems via Modbus TCP or MQTT protocols for real-time data monitoring.
Cloud Platform Integration: Supports historical data storage, remote parameter tuning, and trend analysis.
Alarm Mechanism: Automatically triggers alarms when control errors exceed set thresholds.
Typical Application Scenarios
Building HVAC: Precisely regulates room temperature.
Water Treatment Systems: Maintains constant water level or flow control.
Boilers/Kilns: Achieves closed-loop regulation of combustion temperature.
Motor Speed Regulation: Ensures constant speed or pressure operation.
Food & Beverage/Fermentation Industry: Accurately controls temperature and humidity to enhance production quality.
Solution Advantages
Open-Source and Customization: OpenPLC’s open-source nature provides high flexibility and low development costs.
Edge Computing Capability: The ARM gateway supports local computation, reducing dependency on cloud systems and minimizing network latency.
Strong Real-Time Performance: Local PID closed-loop control ensures fast response and high reliability.
High Scalability: Supports multiple industrial protocols (Modbus, OPC UA, MQTT), facilitating integration with cloud platforms or other systems.
Summary
This solution, centered on the ARM Edge Gateway and integrated with the OpenPLC open-source platform, builds an efficient, flexible, and cost-effective industrial control and data acquisition system. It achieves real-time performance through local PID closed-loop control and scalability through multi-protocol support and cloud integration, making it suitable for various industrial scenarios. Leveraging open-source features and edge computing capabilities, this solution offers robust customization and real-time control while reducing costs, making it an ideal choice for industrial automation.
ARM Edge Gateway is integrated with the OpenPLC open source platform for local PID closed-loop control to achieve real-time performance.
ARM Embedded Controller with OpenPLC and OpenCV/YOLO for Product Quality Inspection
Case Details
The ARMxy BL450 Series, an industrial-grade ARM embedded computer is designed for flexible and robust industrial applications. By integrating OpenPLC and OpenCV/YOLO, the BL450 becomes a powerful platform for automated product quality inspection on production lines, detecting defects such as scratches, stains, or dimensional deviations. This article outlines the technical implementation, communication methods, visual system selection, and PLC logic design for such applications, with case studies in electronic component soldering and pharmaceutical packaging inspection.
Application Scenario
In modern manufacturing, ensuring product quality is critical. The BL450, combined with OpenPLC and OpenCV/YOLO, enables real-time defect detection and automated sorting on production lines. Typical use cases include:
Electronic Component Soldering Quality Inspection: Detecting incomplete solder joints, excess solder, or misalignments.
Pharmaceutical Packaging Integrity Check: Identifying damaged, misprinted, or incomplete packaging.
The system uses a vision-based approach to detect defects and communicates results to a PLC, which controls mechanical arms to remove defective items or redirect them to a separate line.
Technical Implementation
Hardware Setup
The BL450’s flexible I/O configuration and robust hardware make it ideal for industrial environments. Key hardware features include:
Processor: Rockchip RK3588 (based on datasheet), offering high computational power for running OpenCV/YOLO and OpenPLC.
Interfaces:
Ethernet ports (1–3, 10/100/1000M) for industrial communication protocols.
USB ports (2) for connecting cameras.
I/O slots (X and Y boards) for direct I/O signals or RS485 communication.
Dimensions: Compact design (e.g., 42×83×110mm for single Ethernet port models) suitable for production line integration.
Optional Modules: WiFi (BL450W) or 4G (BL450L) for enhanced connectivity.
Example Configuration:
Model: BL450-SOM450-X10 (1 Ethernet port, 32GB eMMC, 4GB LPDDR4X, 2 RS485 ports).
Camera: 2D industrial camera for surface defect detection or 3D camera for depth-based inspection (e.g., bin picking).
Communication Methods
The BL450 supports multiple communication methods to integrate the vision system with the PLC and mechanical systems:
Direct I/O Signal:
Used for simple scenarios, such as sending OK/NG (pass/fail) signals.
Configured via the BL450’s 6-pin I/O slot (X board) for direct connection to OpenPLC.
Example: A high/low signal indicates whether a product passes inspection.
Industrial Communication Protocols:
Ethernet/IP, Profinet, Modbus TCP: Suitable for complex data interactions, such as transmitting defect coordinates or confidence scores from YOLO.
The BL450’s Ethernet port supports these protocols, enabling seamless integration with industrial networks.
Example: Modbus TCP transmits defect type and location to OpenPLC for precise mechanical arm control.
3. Selection of Visual System
The vision system is critical for defect detection. The BL450 supports both traditional and deep learning-based approaches:
Traditional Algorithms (OpenCV):
Techniques: Threshold segmentation, contour detection, edge detection.
Use Case: Suitable for regular objects with predictable defects (e.g., scratches or stains on flat surfaces).
Implementation: OpenCV runs on the BL450’s Debian or Ubuntu OS, processing images from a 2D camera to identify defects based on predefined thresholds.
Advantages: Fast, computationally efficient, and suitable for well-defined inspection tasks.
Deep Learning (YOLO):
Techniques: YOLO (You Only Look Once) for real-time object detection and classification.
Use Case: Complex defect detection (e.g., irregular solder joints or varied packaging defects).
Implementation: YOLO models are deployed on the BL450’s Cortex-A53 cores, leveraging the NPU for accelerated inference. Pre-trained models can be fine-tuned for specific defects.
Advantages: High accuracy for complex patterns, adaptable to diverse defect types.
Camera Selection:
2D Camera: Used for surface-level defect detection (e.g., scratches, stains). Connected via USB or Ethernet.
3D Camera: Used for depth-based inspection (e.g., bin picking or dimensional verification). Provides depth data for complex geometries.
PLC Logic Design (OpenPLC)
OpenPLC, running on the BL450’s Linux-based OS, handles control logic for mechanical systems based on vision system outputs.
Trigger Mechanism:
The vision system (OpenCV/YOLO) processes images and sends a pulse signal to OpenPLC upon completing defect detection.
Example: A detected defect triggers a high signal on a designated I/O pin, which OpenPLC interprets to actuate a mechanical arm.
Safety Redundancy:
Timeout Detection: If the vision system fails to send a signal within a specified time (e.g., 2 seconds), OpenPLC assumes a failure and halts the production line.
Exception Handling: OpenPLC monitors for vision system errors (e.g., camera disconnection) and executes fallback actions, such as redirecting products to a manual inspection station.
Implementation: OpenPLC ladder logic includes timers and error-checking routines to ensure robust operation.
Software Integration
The BL450’s development environment supports seamless integration of OpenPLC and OpenCV/YOLO:
Operating System: Debian or Ubuntu, with pre-installed libraries for OpenCV and Python for YOLO.
Development Examples (from datasheet):
OpenCV development cases for image processing.
Node-RED for IoT integration and data visualization.
Docker containers for deploying YOLO models.
MQTT for communication between vision and PLC systems.
Customization: The BL450’s flexible SOM and I/O board design allows tailored configurations for specific inspection needs.
Case Studies
Case 1: Electronic Component Soldering Quality Inspection
Setup: BL450-SOM450-X10 with a 2D camera and OpenCV for contour detection.
Process:
The camera captures images of solder joints.
OpenCV applies edge detection to identify irregularities (e.g., incomplete joints).
Results (OK/NG) are sent via Modbus TCP to OpenPLC.
OpenPLC controls a mechanical arm to remove defective components.
Outcome: Achieves high-speed inspection with minimal latency, suitable for high-throughput lines.
Case 2: Pharmaceutical Packaging Integrity Check
Setup: BL450W-SOM450-X10 with a 3D camera and YOLO for defect classification.
Process:
The 3D camera captures depth and surface data of packaging.
YOLO classifies defects (e.g., dents, misprints) with high accuracy.
Defect coordinates are sent via Ethernet/IP to OpenPLC.
OpenPLC directs defective packages to a reject line.
Outcome: Robust detection of complex defects, with WiFi enabling remote monitoring via BLiotLink.
Conclusion
The ARMxy BL450, combined with OpenPLC and OpenCV/YOLO, offers a versatile and powerful solution for product quality inspection. Its flexible hardware, support for industrial protocols, and rich development ecosystem make it ideal for automating defect detection and sorting in manufacturing. Whether using traditional OpenCV algorithms for simple tasks or YOLO for complex defect classification, the BL450 ensures reliable performance in demanding industrial environments.
ARM Embedded Controller combined with OpenPLC and OpenCV/YOLO, offers a versatile and powerful solution for product quality inspection.
ARM Industrial Computers ARMxy & OpenPLC: Redefining Cost-Efficient Industrial Automation
Case Details
1. Characteristics and Advantages of ARM Industrial Computers
Low Power Consumption, High Performance ARM-based processors (e.g., Cortex-A series) deliver strong computational capabilities with low power consumption, ideal for industrial scenarios requiring continuous operation.
Rich Interface Support Supports industrial communication interfaces such as GPIO, CAN, RS-485, Ethernet, and USB, enabling direct connectivity to sensors, actuators, and industrial bus devices.
Compact and Rugged Design Industrial-grade construction (wide temperature tolerance, vibration resistance, dustproof) ensures reliability in harsh environments, with a small form factor for embedded deployment.
Linux/RTOS Compatibility Runs Linux (e.g., Debian, Ubuntu Core) or real-time operating systems (e.g., FreeRTOS) to meet real-time requirements.
2. Core Features of OpenPLC
Open Source and Cross-Platform Complies with IEC 61131-3 standards, supporting programming languages like Ladder Logic and Structured Text (ST), and runs on Windows/Linux/Raspberry Pi platforms.
Flexible Deployment Compatible with x86/ARM hardware, deployable as a soft PLC (on general-purpose computers) or hard PLC (e.g., Raspberry Pi, ARM industrial PCs).
Protocol Compatibility Built-in support for Modbus TCP/RTU, MQTT, OPC UA, and other protocols, facilitating integration with SCADA, HMI, and cloud systems.
Extensibility Allows custom function blocks via Python/C++ to integrate AI algorithms or third-party libraries.
3. Typical Application Scenarios for ARM + OpenPLC
3.1 Automation of Small to Medium-Sized Production Lines
Example: Food Packaging Machinery Control
ARM industrial PC (e.g., NXP i.MX8) runs OpenPLC to control servo motors and pneumatic cylinders via Modbus RTU.
HMI touchscreens interact with OpenPLC via Modbus TCP for real-time monitoring.
Advantages: Costs 1/3 of traditional PLC solutions, with support for custom algorithms (e.g., visual quality inspection).
3.2 Distributed Energy Management
Example: Photovoltaic Power Station Monitoring
ARM gateway (e.g., Allwinner T507) runs OpenPLC to collect inverter data (RS-485) and upload it to the cloud via MQTT.
Local logic control (e.g., battery charge/discharge strategies) is executed directly by OpenPLC.
Advantages: Edge computing reduces cloud workload and supports offline operation.
3.3 Smart Warehouse Systems
Example: AGV Scheduling Control
Multiple ARM industrial PCs (e.g., Rockchip RK3568) run OpenPLC to coordinate AGV paths via CAN bus.
Integrates ROS nodes for SLAM navigation, with OpenPLC handling motor control and obstacle avoidance.
Advantages: Unified hardware-software design simplifies multi-device coordination. 4. Comparison with Traditional PLC SolutionsAspectARM + OpenPLCTraditional PLC (e.g., Siemens S7-1200)CostHardware cost reduced by over 50%High hardware/licensing feesCustomizationDeep customization (drivers/algorithms)Closed ecosystem, vendor-dependentEcosystemSeamless Python/Node.js integrationLimited to TIA Portal/CODESYSUse CasesSMEs, R&D, rapid prototypingLarge-scale, high-reliability systems5. Challenges and Mitigation Strategies
Real-Time Limitations: ARM + Linux lacks native real-time performance; use kernel patches or FPGA coprocessors.
Long-Term Maintenance: Open-source version updates may cause compatibility issues; lock versions and maintain forks.
Security Risks: Harden Linux systems (e.g., disable default SSH ports, enable SELinux).
6. ConclusionThe combination of ARM industrial computers and OpenPLC offers a cost-effective, lightweight PLC solution for industrial automation, particularly suited to scenarios requiring rapid iteration and customization (e.g., smart agriculture, lab equipment). For mission-critical environments (e.g., nuclear plants, railways), traditional PLC reliability must still be evaluated. As the ARM ecosystem matures (e.g., RISC-V industrial chips), this approach is poised to expand further into industrial markets.
