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PYSEC-2026-3160
No affected components available
Impact
The implementation of OpLevelCostEstimator::CalculateTensorSize is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements:
int64_t OpLevelCostEstimator::CalculateTensorSize(
const OpInfo::TensorProperties& tensor, bool* found_unknown_shapes) {
int64_t count = CalculateTensorElementCount(tensor, found_unknown_shapes);
int size = DataTypeSize(BaseType(tensor.dtype()));
VLOG(2) << "Count: " << count << " DataTypeSize: " << size;
return count * size;
}
Here, count and size can be large enough to cause count * size to overflow.
Patches
We have patched the issue in GitHub commit fcd18ce3101f245b083b30655c27b239dc72221e.
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.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker needs basic access or low-level privileges. No user interaction is needed for the attacker to exploit this vulnerability. The impact is confined to the system where the vulnerability exists. There is a high impact on the availability of the system.
Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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