Improper Restriction of Operations within the Bounds of a Memory Buffer
In tensorflow-lite before versions 1.15.4, 2.0.x before 2.0.3, 2.1.x before 2.1.2, 2.2.x before 2.2.1 and 2.3.x before 2.3.1, to mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. The issue is patched in commit 2d88f470dea2671b430884260f3626b1fe99830a, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 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.