Dynamic analysis is used to identify potential security vulnerabilities, memory leaks, and other issues that may not be apparent through static code analysis alone. By running applications in a controlled environment, security professionals can observe how software behaves under different conditions, including attempts to exploit potential vulnerabilities.
Dynamic analysis can be performed on different software and systems. Still, it is precious to identify complex runtime security problems like race conditions, buffer overflows, and other issues with how the software logically handles data and operations. Tools for dynamic analysis may include automated fuzzing tools, debuggers, and other utilities that monitor the system’s operations while the software runs.
Implementing dynamic analysis as part of a security strategy allows for the identification and mitigation of risks that could compromise system integrity, lead to data breaches, or cause system unavailability if exploited. It’s a critical component of a thorough testing regime, complementing static analysis for a comprehensive understanding of an application’s security posture.
What is Dynamic Code Analysis?
Dynamic code analysis is a debugging method that examines an application during or after a program has been run. It is a fluid form of analysis because the source code can run with a wide variety of differing inputs, meaning that there are no strict rules to this approach.
Dynamic analysis works by simulating malicious inputs to look for vulnerabilities. Using DAST tools, you can perform dynamic analysis to simulate an end user’s actions. The analysis will probe links, forms, and other functions to replicate real threats. An example would be submitting a form that contains malicious data that would then exploit the app. It is important to note that dynamic analysis does not locate exactly where a bug is and cannot fix the issues found.
How does it work?
Dynamic analysis involves tools and techniques that monitor the software during execution. Here’s how it typically works:
- The software is run in a test environment that mimics real-world conditions without risking actual systems.
- The software is fed various inputs, including edge cases and potentially malicious data, to see how it handles them.
- Tools track the software’s behavior, resource usage, and interactions with the system.
- The data collected is analysed to identify any issues, vulnerabilities, or performance bottlenecks.
Why does Dynamic Analysis matter?
Dynamic Analysis is best thought of as a detection method. It allows developers and security professionals to:
- Identify bugs: Some problems only appear when the software is running, like a car that makes a funny noise only on the highway.
- Identify software flaws: By simulating attacks or unexpected inputs, dynamic analysis can reveal vulnerabilities that hackers might exploit.
- Improve performance: It helps fine-tune the software by monitoring resource usage and optimising performance.
What is the difference between Static and Dynamic Analysis?
The main difference between static and dynamic analysis is that static code analysis does not require code execution to operate, whereas dynamic analysis does. Another difference is that static analysis works at the code level, whereas dynamic analysis works at the compiled system level. This means that static code analysis searches for poor coding and patterns in known vulnerabilities, and dynamic analysis scans systems for known risks.
Key Characteristics:
- Involves executing the program to observe its real-time behaviour
- Detects problems only apparent during program execution
- Useful for uncovering runtime vulnerabilities
- Often employs various tools like fuzzers and debuggers
Examples:
- Real-World Example: An ethical hacker uses dynamic analysis tools to test a web application’s resilience to SQL injection attacks by simulating attack vectors and observing how the application handles malicious inputs.
- Hypothetical Scenario: A security engineer running a dynamic analysis tool against a new messaging app finds a buffer overflow vulnerability that occurs only when a message contains a specific set of characters, which could be exploited by an attacker.
Related Terms:
- Static Analysis: A method of computer program debugging done by examining the code without executing the program, a complement to dynamic analysis.
- Fuzzing: An automated software testing technique that involves providing invalid, unexpected, or random data as input to an application during dynamic analysis.
- Buffer Overflow: A common software coding mistake that dynamic analysis tools can help identify, where a program writes data beyond the allocated memory boundaries.
- Debugging: A part of dynamic analysis involving finding and resolving software defects or problems within a program while it is in execution.
