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Improper input validation [1] or unchecked user input is a type of vulnerability in computer software that may be used for security exploits. [2] This vulnerability is caused when "[t]he product does not validate or incorrectly validates input that can affect the control flow or data flow of a program." [1] Examples include: Buffer overflow
Code injection is a computer security exploit where a program fails to correctly process external data, such as user input, causing it to interpret the data as executable commands. An attacker using this method "injects" code into the program while it is running.
A code sanitizer is a programming tool that detects bugs in the form of undefined or suspicious behavior by a compiler inserting instrumentation code at runtime. The class of tools was first introduced by Google's AddressSanitizer (or ASan) of 2012, which uses directly mapped shadow memory to detect memory corruption such as buffer overflows or accesses to a dangling pointer (use-after-free).
The function will result in undefined behavior when the input is over 1000 characters. Some programmers may not feel that this is a problem, supposing that no user will enter such a long input. This particular bug demonstrates a vulnerability which enables buffer overflow exploits. Here is a solution to this example:
Software validation checks that the software product satisfies or fits the intended use (high-level checking), i.e., the software meets the user requirements, not as specification artifacts or as needs of those who will operate the software only; but, as the needs of all the stakeholders (such as users, operators, administrators, managers ...
Translation validation can be used even with a compiler that sometimes generates incorrect code, as long as this incorrect does not manifest itself for a given program. Depending on the input program the translation validation can fail (because the generated code is wrong or the translation validation technique is too weak to show correctness).
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]
An example of a proactive approach is the free code audit service offered by GooApps, which aims to identify and mitigate vulnerabilities early in the development process to ensure the success of mobile applications.