维基百科列出了以下内存安全问题的示例:
Access errors: invalid read/write of a pointer
Buffer overflow - out-of-bound writes can corrupt the content of adjacent objects, or internal data (like bookkeeping information for the heap) or return addresses.
Buffer over-read - out-of-bound reads can reveal sensitive data or help attackers bypass address space layout randomization.
Python至少试图防止这些。
Race condition - concurrent reads/writes to shared memory
在具有可变数据结构的语言中,这实际上并不难。(函数式编程和不可变数据结构的倡导者经常使用这一事实作为支持他们的论据)。
Invalid page fault - accessing a pointer outside the virtual memory space. A null pointer dereference will often cause an exception or program termination in most environments, but can cause corruption in operating system kernels or systems without memory protection, or when use of the null pointer involves a large or negative offset.
Use after free - dereferencing a dangling pointer storing the address of an object that has been deleted.
Uninitialized variables - a variable that has not been assigned a value is used. It may contain an undesired or, in some languages, a corrupt value.
Null pointer dereference - dereferencing an invalid pointer or a pointer to memory that has not been allocated
Wild pointers arise when a pointer is used prior to initialization to some known state. They show the same erratic behaviour as dangling pointers, though they are less likely to stay undetected.
没有真正的方法可以阻止某人尝试访问空指针。在 C# 和 Java 中,这会导致异常。在 C++ 中,这会导致未定义的行为。
Memory leak - when memory usage is not tracked or is tracked incorrectly
Stack exhaustion - occurs when a program runs out of stack space, typically because of too deep recursion. A guard page typically halts the program, preventing memory corruption, but functions with large stack frames may bypass the page.
C#、Java 和 Python 等语言中的内存泄漏与手动管理内存的 C 和 C++ 等语言中的内存泄漏具有不同的含义。在 C 或 C++ 中,由于未能释放分配的内存而导致内存泄漏。在具有托管内存的语言中,您不必显式地取消分配内存,但仍然可以通过在某处意外维护对它的引用来做一些非常相似的事情。
对于 C# 中的事件处理程序和长期存在的集合类,这实际上很容易做到;尽管我们使用的是托管内存,但我实际上曾参与过存在内存泄漏的项目。从某种意义上说,使用托管内存的环境实际上会使这些问题更加危险,因为程序员可能有一种错误的安全感。根据我的经验,即使是经验丰富的工程师也经常无法进行内存分析或编写测试用例来检查这一点(可能是由于环境给了他们错误的安全感)。
堆栈耗尽在 Python 中也很容易实现。
Heap exhaustion - the program tries to allocate more memory than the amount available. In some languages, this condition must be checked for manually after each allocation.
仍然很有可能 - 我很尴尬地承认我个人已经在 C# 中完成了该操作(尽管还没有在 Python 中)。
Double free - repeated calls to free may prematurely free a new object at the same address. If the exact address has not been reused, other corruption may occur, especially in allocators that use free lists.
Invalid free - passing an invalid address to free can corrupt the heap.
Mismatched free - when multiple allocators are in use, attempting to free memory with a deallocation function of a different allocator[20]
Unwanted aliasing - when the same memory location is allocated and modified twice for unrelated purposes.
在 Python 中,不需要的别名实际上很容易实现。这是Java中的一个例子(完全披露:我写了接受的答案);你可以很容易地在 Python 中做一些非常相似的事情。其他由 Python 解释器本身管理。
因此,内存安全似乎是相对的。根据您所认为的“内存安全问题”,实际上很难完全预防。Java、C# 和 Python 等高级语言可以防止其中许多最严重的错误,但还有其他问题很难或不可能完全防止。