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Advisory Package Curation

CVE-2022-36003

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Advisory Summaries

github_osv/GHSA-cv2p-32v3-vhwq

TensorFlow vulnerable to `CHECK` fail in `RandomPoissonV2` ### Impact When `RandomPoissonV2` receives large input shape and rates, it gives a `CHECK` fail that can trigger a denial of service attack. ```python import tensorflow as tf arg_0=tf.random.uniform(shape=(4,), dtype=tf.int32, maxval=65536) arg_1=tf.random.uniform(shape=(4, 4, 4, 4, 4), dtype=tf.float32, maxval=None) arg_2=0 arg_3=0 arg_4=tf.int32 arg_5=None tf.raw_ops.RandomPoissonV2(shape=arg_0, rate=arg_1, seed=arg_2, seed2=arg_3, dtype=arg_4, name=arg_5) ``` ### Patches We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3 https://github.com/tensorflow/tensorflow/commit/552bfced6ce4809db5f3ca305f60ff80dd40c5a3. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. ### For more information Please consult our security guide https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.

gitlab/pypi/tensorflow/CVE-2022-36003

Reachable Assertion TensorFlow is an open source platform for machine learning. When `RandomPoissonV2` receives large input shape and rates, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

pypa/tensorflow/PYSEC-2026-3162

TensorFlow vulnerable to `CHECK` fail in `RandomPoissonV2` ### Impact When `RandomPoissonV2` receives large input shape and rates, it gives a `CHECK` fail that can trigger a denial of service attack. ```python import tensorflow as tf arg_0=tf.random.uniform(shape=(4,), dtype=tf.int32, maxval=65536) arg_1=tf.random.uniform(shape=(4, 4, 4, 4, 4), dtype=tf.float32, maxval=None) arg_2=0 arg_3=0 arg_4=tf.int32 arg_5=None tf.raw_ops.RandomPoissonV2(shape=arg_0, rate=arg_1, seed=arg_2, seed2=arg_3, dtype=arg_4, name=arg_5) ``` ### Patches We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3 https://github.com/tensorflow/tensorflow/commit/552bfced6ce4809db5f3ca305f60ff80dd40c5a3. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. ### For more information Please consult our security guide https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.

pysec/PYSEC-2026-3162

TensorFlow vulnerable to `CHECK` fail in `RandomPoissonV2` ### Impact When `RandomPoissonV2` receives large input shape and rates, it gives a `CHECK` fail that can trigger a denial of service attack. ```python import tensorflow as tf arg_0=tf.random.uniform(shape=(4,), dtype=tf.int32, maxval=65536) arg_1=tf.random.uniform(shape=(4, 4, 4, 4, 4), dtype=tf.float32, maxval=None) arg_2=0 arg_3=0 arg_4=tf.int32 arg_5=None tf.raw_ops.RandomPoissonV2(shape=arg_0, rate=arg_1, seed=arg_2, seed2=arg_3, dtype=arg_4, name=arg_5) ``` ### Patches We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3 https://github.com/tensorflow/tensorflow/commit/552bfced6ce4809db5f3ca305f60ff80dd40c5a3. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. ### For more information Please consult our security guide https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.