Impact
TensorFlow's type inference can cause a heap OOB read as the bounds checking is done in a DCHECK (which is a no-op during production):
if (node_t.type_id() != TFT_UNSET) {
int ix = input_idx[i];
DCHECK(ix < node_t.args_size())
<< "input " << i << " should have an output " << ix
<< " but instead only has " << node_t.args_size()
<< " outputs: " << node_t.DebugString();
input_types.emplace_back(node_t.args(ix));
// ...
} An attacker can control input_idx such that ix would be larger than the number of values in node_t.args.
Patches
We have patched the issue in GitHub commit c99d98cd189839dcf51aee94e7437b54b31f8abd.
The fix will be included in TensorFlow 2.8.0. This is the only affected version.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
References
Impact
TensorFlow's type inference can cause a heap OOB read as the bounds checking is done in a
DCHECK(which is a no-op during production):An attacker can control
input_idxsuch thatixwould be larger than the number of values innode_t.args.Patches
We have patched the issue in GitHub commit c99d98cd189839dcf51aee94e7437b54b31f8abd.
The fix will be included in TensorFlow 2.8.0. This is the only affected version.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
References