This Python script performs IoT device (or embedded system) firmware analysis on a given binary file (.bin). It provides a comprehensive set of functions to extract valuable information and insights from the firmware, aiding in reverse engineering and vulnerability analysis.
Bakhshi T, Ghita B, Kuzminykh I. A Review of IoT Firmware Vulnerabilities and Auditing Techniques. Sensors. 2024; 24(2):708. https://doi.org/10.3390/s24020708.
https://github.com/attify/firmware-analysis-toolkit
https://www.thyrasec.com/blog/firmware-reversing-and-analysis-tools/
https://github.com/alexandreborges/malwoverview
- Calculates file size and MD5 hash of the firmware
- Detects file format (ELF, PE, or unknown)
- Extracts strings with a minimum length of 5 characters
- Detects URLs and IP addresses within the firmware
- Identifies potential packing algorithms used in the firmware
- Detects the architecture of the firmware (ARM, MIPS, x86, or unknown)
- Calculates the entropy of the firmware to determine the presence of encrypted or compressed data
- Extracts firmware metadata such as version, build date, and developer information
- Analyzes user interface resources (images and fonts) within the firmware
- Detects the presence of cryptographic algorithms (AES, DES, RSA, SHA-1, SHA-256, MD5) and provides descriptions of their usage
- Identifies potential passwords based on length, entropy, and specific patterns
Firmware analysis plays a crucial role in reverse engineering and vulnerability assessment of embedded systems. By examining the firmware, security researchers and developers can:
- Understand the functionality and inner workings of the device
- Identify potential security vulnerabilities and weaknesses
- Detect the presence of backdoors or hidden functionalities
- Assess the use of cryptographic algorithms and their implementations
- Recover sensitive information such as hardcoded credentials or encryption keys
- Analyze the attack surface and potential entry points for exploitation
Firmware analysis allows for a deeper understanding of the device's behavior and helps in identifying and mitigating security risks associated with the firmware.
The script generates a table summarizing the analysis results.
The script provides various parameters that you can customize based on your specific requirements:
min_length: The minimum length of strings to be detected (default is 5).min_entropy: The minimum entropy required for a string to be considered a potential password (default is 3.0).top_n: The number of top potential passwords to display (default is 10).
Feel free to modify these parameters in the analyze_firmware() function to suit your needs.
This script is provided for educational and research purposes only. The use of this tool should comply with all applicable laws and ethical guidelines. The authors and contributors are not responsible for any misuse or damage caused by this script.
Contributions to this project are welcome. If you find any bugs, have suggestions for improvements, or want to add new features, please open an issue or submit a pull request on the GitHub repository.
This project is licensed under the MIT License.