As part of thinking about updates to my book, if I ever get around to making another revision, I've thought that a chapter on programming security would be good. It is also helpful that part of the requirements to maintain my Security+ certification can be met by writing security-oriented blog posts. Thus, I will start writing a number of posts about programming security in general and how Python deals with some of these issues, if it does. If I ever make a new version of my book, I will include these posts into a new chapter. Hopefully this information will be useful.
The big thing to remember when it comes to programming security is that it just takes one mistake to create a security vulnerability. While Python alleviates a lot of the problems other languages have, e.g. memory allocation, it doesn't mean the Python is invulnerable. In fact, one of the points against Python is the fact that it isn't compiled; because Python programs are frequently provided in their raw .py files, anyone can open them up and view or modify them. Thus, if a person looks at the file for nefarious purposes, it's very easy for him or her to identify vulnerabilities that the programmer left in the code.
Another problem with Python is the incompatibility between Python 2.x and Python 3.x. If a programmer is converting a file from 2.x to 3.x, and not using the 2to3 converter (or doesn't look at the resulting code), there is a chance that vulnerability snuck through.
Secure programming, regardless of the language, involves some assumptions on the part of the programmer. Essentially, the programmer never assumes the system is in a particular state or that functions, methods, libraries, etc. will work as advertised. The programmer attempts to handle all possible errors and conditions within the code.
For example, buffer overflows occur when too much data is put into a buffer (a portion of memory). If the buffer fills up, any additional data spills over into adjacent memory areas, potentially causing system malfunctions, memory corruption, or exploiting the system. C and C++ are famous for buffer overflows, as they have no inherent protection against accessing or overwriting data in any memory location and do not automatically check the input data against the boundaries of a buffer.
As a programmer, you should develop the habit of validating any input data, whether it be ensuring the type of data (character strings vs. numbers), the length of the data (ensuring too much data isn't put into a buffer), allowed characters, etc. Many SQL attacks are performed due to poor or non-existent data checking.
One of the reasons there are so many languages available for programming nowadays is because of the inherent lack of security in C and C++. For decades, those languages dominated programming; they are still the go-to choice for many programmers, especially for low-level work on hardware devices, such as video cards. Newer languages, like Java, Python, Ruby, or the various .NET flavors have some safety features built-in.
One example is garbage collection. Traditional C/C++ programmers have to be aware of memory allocation and ensure that, once a data object is no longer in use, all references to it are removed from memory. If not, the memory remains allocated for that non-existent object and can't be used for another purpose. If this happens too often, eventually there will be no memory available for legitimate data objects and the program fails, the system crashes, or other problems arise. If a malware writer wanted to create a denial of service, simply providing a program that eats up memory will do it; once the system or program crashes, no one can use it until it is reset.