CVE-2023-25673High· 7.5▾ TwilightTensorFlow has Floating Point Exception in TensorListSplit with XLA
▾ Twilight zone — High severity, or a signal on a lesser flaw
impact 41.3 · likelihood 0.1 · exploitation 0
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Exploit-prediction probability, daily snapshots since Jul 8.
Disclosure to exploitation, from the record and what we observed since indexing it.
Disclosed via OSV
0.4%
0.4% → 0.4%
Last analysed / modified upstream
FPE in TensorListSplit with XLA
import tensorflow as tf
func = tf.raw_ops.TensorListSplit
para = {'tensor': [1], 'element_shape': -1, 'lengths': [0]}
@tf.function(jit_compile=True)
def fuzz_jit():
y = func(**para)
return y
print(fuzz_jit())
We have patched the issue in GitHub commit 728113a3be690facad6ce436660a0bc1858017fa.
The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1
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This vulnerability has been reported by r3pwnx
tensorflow < 2.11.1tensorflow-cpu < 2.11.1tensorflow-gpu < 2.11.1Upgrade to a patched release:
tensorflow 2.11.1tensorflow-cpu 2.11.1tensorflow-gpu 2.11.1Connected by shared product, vendor, weakness, or advisory.
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