CVE-2022-23592High· 8.1▾ TwilightOut of bounds read in Tensorflow
▾ Twilight zone — High severity, or a signal on a lesser flaw
impact 44.6 · likelihood 0.2 · exploitation 0
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Exploit-prediction probability, daily snapshots since Jul 13.
Disclosure to exploitation, from the record and what we observed since indexing it.
Disclosed via OSV
Last analysed / modified upstream
0.9%
0.9% → 0.9%
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.
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.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
tensorflow >= 2.8.0-rc0, < 2.8.0tensorflow-cpu >= 2.8.0-rc0, < 2.8.0tensorflow-gpu >= 2.8.0-rc0, < 2.8.0Upgrade to a patched release:
tensorflow 2.8.0tensorflow-cpu 2.8.0tensorflow-gpu 2.8.0Connected by shared product, vendor, weakness, or advisory.
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