A Quick Introduction to Symbolic Execution

By analysing the behaviour of programs under various hypothetical inputs represented as symbolic values, this technique allows security professionals to systematically uncover and address potential security flaws that might not be evident during conventional testing.

First Published 1st July 2024

"Depart from me - code, who is cursed."

4 min read  |  Reflare Research Team

The Dark Art

Software security is a critical concern in our increasingly digital world. As cyber threats continue to evolve, cybersecurity professionals are constantly seeking more effective methods to identify and mitigate vulnerabilities. Among these advanced approaches, symbolic execution has emerged as a powerful technique for uncovering hidden flaws in software before they can be exploited.

Symbolic execution is a method of analysing how a program behaves under different conditions. Instead of using specific, real-world inputs like a user might enter, it uses abstract placeholders that can represent any possible input. This approach allows for a comprehensive exploration of various scenarios the software might encounter, revealing potential security issues that might be overlooked by conventional testing methods.

At its core, symbolic execution works by systematically tracking these abstract inputs as they move through the program, with particular emphasis on how they affect decision points such as if-statements. This makes it an invaluable tool for identifying and rectifying security weaknesses, significantly contributing to the development of robust and secure software systems.

Unlike dumb fuzzing, which tests software by bombarding it with random inputs, symbolic execution takes a more structured approach. While dumb fuzzing can effectively uncover certain types of vulnerabilities, it often misses edge cases and deeper logical flaws. Symbolic execution, by contrast, explores all possible paths a program might take, ensuring more thorough coverage.

This comprehensive nature of symbolic execution makes it particularly effective in identifying complex bugs and vulnerabilities that other methods might miss. As software systems become increasingly complex and integral to our daily lives and critical infrastructure, techniques like symbolic execution play a crucial role in enhancing overall cybersecurity.

How Symbolic Execution Works

To understand symbolic execution in more detail, let's break down its key components:

1. Symbolic Values: Instead of using concrete data, the program operates on symbolic inputs. For example, rather than assigning a specific number to a variable, it might use a symbol like 'x' to represent any possible value.
2. Path Constraints: As the program runs, the symbolic execution engine keeps track of constraints on these symbolic values. These constraints are derived from the conditional branches in the code. For instance, if the code contains an if (x > 5) statement, the engine records the constraint x > 5 on the true branch and x <= 5 on the false branch.
3. Exploration of Paths: The symbolic execution engine explores all possible paths the program might take by considering all possible combinations of path constraints. This exhaustive exploration helps identify potential bugs or vulnerabilities.
4. Constraint Solving: To determine if a particular path is feasible, the symbolic execution engine uses a constraint solver. If the solver finds a set of concrete values that satisfy the constraints, the path is considered feasible, and the specific inputs can be derived.

Importance in Cybersecurity

Symbolic execution is particularly valuable in cybersecurity for several reasons:

• Bug Detection: By exploring numerous execution paths, symbolic execution can uncover bugs that might not be evident through conventional testing methods. This includes discovering buffer overflows, null pointer dereferences, and other critical vulnerabilities.
• Automated Testing: It automates the generation of test cases, ensuring comprehensive coverage of different execution paths, including edge cases that are often missed by manual testing.
• Exploit Generation: Symbolic execution can be used to generate exploits by identifying input values that trigger vulnerabilities. This assists security researchers in understanding and demonstrating the impact of discovered vulnerabilities.
• Code Verification: It aids in formal verification of software, ensuring that the code behaves as expected under all possible conditions. This is crucial for software that requires high assurance, such as systems in aerospace, healthcare, and critical infrastructure.

Tools for Symbolic Execution

Several tools have been developed to facilitate symbolic execution, each with its unique features and strengths. Here are some of the most widely used tools in the cybersecurity community:

1. KLEE: A popular symbolic execution engine that works on programs compiled to LLVM bitcode. It aims to automatically generate high-coverage tests for complex systems programs.
2. Z3: A high-performance theorem prover developed by Microsoft Research. While not a symbolic execution engine per se, it is often used in conjunction with symbolic execution tools as a constraint solver.
3. Angr: A powerful and flexible binary analysis framework that includes support for symbolic execution. It is capable of analysing binaries for various architectures and provides a rich set of features for program analysis.
4. SAGE (Scalable, Automated, Guided Execution): A symbolic execution tool developed by Microsoft. It is designed to find security vulnerabilities in software by performing guided whitebox fuzz testing.

Challenges and Limitations

While symbolic execution is a powerful technique, it also has its challenges and limitations:

• Path Explosion: The number of execution paths can grow exponentially with the size of the program, leading to scalability issues.
• Complex Constraints: Solving complex constraints can be computationally expensive, especially for large and intricate programs.
• Environment Modelling: Accurately modelling the program's interaction with its environment (such as file I/O, network communication) can be difficult.
• Handling Loops: Infinite loops or large iterations can cause the symbolic execution to get stuck or take a long time to complete.

Embracing the Faith

Symbolic execution is a sophisticated and highly effective technique in the cybersecurity toolbox. By enabling comprehensive and automated analysis of program behaviour, it helps in identifying and mitigating security vulnerabilities that might otherwise go unnoticed. Tools like KLEE, Z3, Angr, and SAGE are at the forefront of this technology, providing robust platforms for researchers and security professionals to enhance the security of software systems.

Despite its challenges, the benefits of symbolic execution make it an indispensable method for advancing cybersecurity and ensuring the reliability of critical software applications. As cyber threats continue to evolve, techniques like symbolic execution will play a crucial role in developing more robust and secure software systems, protecting critical infrastructure, and safeguarding digital assets across industries.