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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
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).
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.
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:
A directory traversal (or path traversal) attack exploits insufficient security validation or sanitization of user-supplied file names, such that characters representing "traverse to parent directory" are passed through to the operating system's file system API. An affected application can be exploited to gain unauthorized access to the file system
User input (including an XSS vector) would be sent to the server, and then sent back to the user as a web page. The need for an improved user experience resulted in popularity of applications that had a majority of the presentation logic (maybe written in JavaScript) working on the client-side that pulled data, on-demand, from the server using ...
In general, data sanitization techniques use algorithms to detect anomalies and remove any suspicious points that may be poisoned data or sensitive information. Furthermore, data sanitization methods may remove useful, non-sensitive information, which then renders the sanitized dataset less useful and altered from the original.
The concept behind taint checking is that any variable that can be modified by an outside user (for example a variable set by a field in a web form) poses a potential security risk. If that variable is used in an expression that sets a second variable, that second variable is now also suspicious. The taint checking tool can then proceed ...