Buffer overflow vulnerabilities occur when memory management goes wrong. Before data can be stored in a chunk of memory, that chunk of memory has to be allocated. This means the program needs to know how much memory to allocate in advance. A buffer overflow occurs when a program tries to copy more data into a particular memory location than is allocated at this location. For this to happen, two things need to go wrong:
Allocating too little space: To be exploitable, a program needs to allocate less space for data than the maximum size of the data. This commonly happens when a developer makes a “reasonable” assumption about the amount of space needed for a particular type of data or when an attacker exploits an integer overflow vulnerability in memory allocation Storing too much data: A buffer overflow vulnerability also requires the program to try to store more data than fits in the allocated space. This can happen when data is copied until a null terminator or if a developer miscalculates the amount of data that can fit in a buffer
If this combination of factors exists, then an application potentially contains an exploitable buffer overflow vulnerability.
Exploiting buffer overflows with Python
Buffer overflows can be exploited for a couple of different purposes. Using a buffer overflow vulnerability to crash a program (like a denial of service attack) is pretty easy while using it to achieve code execution is a bit more difficult. Buffer overflow vulnerabilities can be exploited using almost any programming language. However, Python has a few features that make it especially useful for exploiting these vulnerabilities, including:
Python libraries: The core Python programming language is powerful and easy to use, and the massive number of libraries available makes it even more so. Python’s libraries are valuable for buffer overflow exploitation because they can help to provide any functionality required to make the exploit code interact with the target application Python string multiplication: When exploiting a buffer overflow vulnerability, it is often necessary to create an exploit string of a precise length. This may include sending hundreds or thousands of padding characters to overrun the buffer length. Python’s string multiplication makes building exploit strings easy because a simple command like “A”*500 creates a string of “A” characters to fill a 500-character buffer. This string can cause program crashes for a smaller buffer or act as padding for selective overwrites of values beyond the buffer
Buffer overflows can be exploited manually or with a variety of different programming languages. That said, writing exploit code in Python is often faster and easier than the alternatives.
Python for penetration testing
Python is designed to be a very easy-to-use programming language. Functionality that can be implemented within a few lines of Python code is likely to be much harder to write in other programming languages. Additionally, as an interpreted language, Python development is faster than compiled languages. This, along with its vast library, makes Python a valuable tool for penetration testing and exploit development. Test code and exploits can be automated with minimal overhead, which is essential when iterating rapidly to identify a usable exploit for a vulnerability.
Sources
Buffer overflow, OWASP CWE 119, MITRE How to use Python to multiply strings, Python Central
