Improper Restriction of Operations within the Bounds of a Memory Buffer
In Tensorflow 2.3.0rc0 before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
CWE-119 - Buffer Overflow
Buffer overflow attacks involve data transit and operations exceeding the restricted memory buffer, thereby corrupting or overwriting data in adjacent memory locations. Such overflow allows the attacker to run arbitrary code or manipulate the existing code to cause privilege escalation, data breach, denial of service, system crash and even complete system compromise. Given that languages such as C and C++ lack default safeguards against overwriting or accessing data in their memory, applications utilizing these languages are most susceptible to buffer overflows attacks.