We live in a world that depends on embedded software. It’s in the cars we drive, the elevators we use and the planes we travel in. As these systems become increasingly complex, the security and functionality of embedded software systems is becoming integral to software development. However, due to the nature of embedded systems, many traditional testing methods fall short of providing adequate security for them. In this article, we will explore some of the challenges of embedded software security testing and look into testing approaches that can address them.
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Table of Contents
- Remote Hardware Access
- The Variety of Potential Attack Vectors
- Time and Resource Constraints
- Lack of Standardization in Embedded Software Systems
- The Need for Real-Time Testing
- Lack of Test Automation
- The "Security vs Safety" Tradeoff
What Makes Embedded Software Testing So Complex?
Although many embedded systems are already designed with security in mind, it’s a no-brainer that no system can be 100% secure. Many attack vectors can be exploited in embedded software, such as Buffer Overflows, Memory Corruption, and Code Injection. A successful attack can result in the compromise of the device, data theft, or remote control. Embedded systems must also be fail-safe, especially in automotive, aviation and other areas where human lives depend on their functionality.
7 Challenges of Embedded Software Security Testing
For the reasons described above, identifying potential vulnerabilities in embedded systems is essential. However, testing them can be quite challenging due to the unique interaction of hardware and software within embedded systems. Here are 7 of the main challenges of embedded software security testing.
1. Remote Hardware Access
One of the main challenges in embedded software testing is the reliance on hardware, which can be difficult to access due to limited physical availability, especially in the early stages of testing. Testing is often done using remote servers, preventing the testing team from having direct access to the hardware. Emulators and simulators are commonly used to mock embedded systems. However, there is always the risk of mimicking the actual device inaccurately.
2. The Variety of Potential Attack Vectors
There are a wide variety of potential attack vectors that can be exploited in an embedded system. These include:
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Buffer Overflows: A buffer overflow occurs when more data is written to a buffer than it is designed to hold. This can result in overwriting other data in memory, leading to a crash or allowing an attacker to take control of the system.
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Memory Corruption: Memory-Corruption occurs when data is written to memory in an unintended way. This can corrupt other data in memory, leading to a crash or allowing an attacker to take control of the system.
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Code Injection: Injection vulnerabilities happen when malicious code is injected into a program, allowing an attacker to take control of the system or cause it to crash.
And many more...
It can be difficult to identify all the possible ways an attacker could exploit a system because of the sheer number of potential vulnerabilities.
3. Time and Resource Constraints
There are established and proven test approaches for the different stages of embedded software development (unit tests, integration tests, regression tests, hardware/software integration, etc.). Due to time and resource constraints, teams are often forced to leave out some of these testing efforts or to run them on a reduced scale. Nonetheless, accurately simulating real-world usage requires testing a system under various conditions and with different input types. Automated testing tools can help to ensure that testing gets the attention it needs in time-constrained projects.
4. Lack of Standardization in Embedded Software Systems
The uniqueness of embedded software systems makes it hard to standardize testing methods across use cases. Each system and each domain (e.g., automotive, avionics, medical, etc.) has its own set of requirements and constraints. As such, it can be challenging to identify the type of testing approach that is necessary. Norms such as ISO/SAE 21434 in automotive or DO-178C in avionics are enforcing more standardization throughout their respective industries. In many instances, these norms require dev teams to adjust their development processes.
5. The Need for Real-Time Testing
Many embedded systems need to react in real time. Often, a delay in response to an external event is considered a failure. This requires the system to be tested under conditions that are representative of its actual usage. A huge challenge of embedded software testing is simulating these conditions. Advanced mocking is one approach that is proven effective in achieving this.
6. Lack of Test Automation
Testing embedded systems manually can be time-consuming. Automated testing can help to speed up the testing process and improve accuracy. However, it can be difficult to automate tests for embedded systems due to the unique nature of each system. Especially in automotive, many embedded development teams, therefore, opt for CI/CD-integrated fuzz testing to automatically test positive and negative criteria at each pull request. Automated testing can also help explore the application and find security vulnerabilities that developers may not have considered.
7. The "Security vs Safety" Tradeoff
Many embedded systems need to be designed with both security and safety in mind. However, these two goals can often be at odds with each other. Safety mainly refers to fail-safe behavior and reliability, while security mainly refers to preventing unauthorized access to sensitive data. For example, adding security features to a system can make it more complex and difficult to test, impacting its safety. As such, embedded software teams require adequate tooling to uncover security and safety issues all the same.
Our Recommendation: Mocking Embedded Systems With Fuzz Data
A particularly effective approach to deal with the complexity of embedded software testing is mocking with fuzz data. During mocking, an embedded software module is tested in isolation and hardware dependencies are simulated. By enhancing a mocking setup with fuzz data, it can dynamically generate return values for mocked functions. This allows the tester to realistically simulate the behavior of external dependencies while covering positive and negative test criteria.
CI/CD-Integrated Fuzz Testing for Embedded Software
Integrating fuzzing-based testing tools into CI/CD pipelines enables embedded software teams to test their codebase continuously. Such a testing setup alleviates many of the above-mentioned challenges, such as the lack of real-time testing, lack of automation and the safety vs security tradeoff as fuzzing can find both security and safety bugs.
By implementing continuous fuzz testing in the early stages of software development, bugs can be found and fixed before they become an issue. This not only makes embedded systems more secure but also speeds up the development process. If you want to learn more about how CI/CD-integrated fuzz testing can fit into your development process, you can book a demo with one of our colleagues.
