An attacker can craft a TFLite model that would cause an integer overflow in TfLiteIntArrayCreate
:
TfLiteIntArray* TfLiteIntArrayCreate(int size) {
int alloc_size = TfLiteIntArrayGetSizeInBytes(size);
// ...
TfLiteIntArray* ret = (TfLiteIntArray*)malloc(alloc_size);
// ...
}
The TfLiteIntArrayGetSizeInBytes
returns an int
instead of a size_t
:
int TfLiteIntArrayGetSizeInBytes(int size) {
static TfLiteIntArray dummy;
int computed_size = sizeof(dummy) + sizeof(dummy.data[0]) * size;
#if defined(_MSC_VER)
// Context for why this is needed is in http://b/189926408#comment21
computed_size -= sizeof(dummy.data[0]);
#endif
return computed_size;
}
An attacker can control model inputs such that computed_size
overflows the size of int
datatype.
We have patched the issue in GitHub commit a1e1511dde36b3f8aa27a6ec630838e7ea40e091.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by Wang Xuan of Qihoo 360 AIVul Team.