Search results
Results from the WOW.Com Content Network
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).
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.
Example 1: legacy code may have been designed for ASCII input but now the input is UTF-8. Example 2 : legacy code may have been compiled and tested on 32-bit architectures, but when compiled on 64-bit architectures, new arithmetic problems may occur (e.g., invalid signedness tests, invalid type casts, etc.).
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 simplest kind of data type validation verifies that the individual characters provided through user input are consistent with the expected characters of one or more known primitive data types as defined in a programming language or data storage and retrieval mechanism.
Automated input minimization (or test case reduction) is an automated debugging technique to isolate that part of the failure-inducing input that is actually inducing the failure. [ 56 ] [ 57 ] If the failure-inducing input is large and mostly malformed, it might be difficult for a developer to understand what exactly is causing the bug.
If data sanitization methods are unsuccessful at removing all sensitive information, it poses the risk of leaking this information to attackers. [26] Numerous studies have been conducted to optimize ways of preserving sensitive information. Some data sanitization methods have a high sensitivity to distinct points that have no closeness to data ...