PYSEC-2026-3267 Missing validation causes denial of service via `LSTMBlockCell`

Impact The implementation of tf.rawops.LSTMBlockCell does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf tf.rawops.LSTMBlockCell x=tf.constant0.837607, shape=28,29, dtype=tf.float32,...

Missing validation causes denial of service via `GetSessionTensor`

ImpactThe implementation of tf.rawops.GetSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfhandle = tf.constant"", shape=0,...

Missing validation causes denial of service via `GetSessionTensor`

ImpactThe implementation of tf.rawops.GetSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfhandle = tf.constant"", shape=0,...

Missing validation causes denial of service via `DeleteSessionTensor`

ImpactThe implementation of tf.rawops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tfhandle = tf.constant"", shape=0,...

Missing validation crashes `QuantizeAndDequantizeV4Grad`

ImpactThe implementation of tf.rawops.QuantizeAndDequantizeV4Grad does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:pythonimport tensorflow as tftf.rawops.QuantizeAndDequantizeV4Grad gradients=tf.constant1,...

PYSEC-2026-3179 Missing validation causes denial of service via `GetSessionTensor`

Impact The implementation of tf.rawops.GetSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf handle = tf.constant"", shape=0, dtype=tf.string...

PYSEC-2026-3197 Missing validation causes denial of service via `DeleteSessionTensor`

Impact The implementation of tf.rawops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf handle = tf.constant"", shape=0, dtype=tf.string...

PYSEC-2026-3324 Missing validation causes denial of service via `GetSessionTensor`

Impact The implementation of tf.rawops.GetSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf handle = tf.constant"", shape=0, dtype=tf.string...

Missing validation causes `TensorSummaryV2` to crash

ImpactThe implementation of tf.rawops.TensorSummaryV2 does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:pythonimport numpy as npimport tensorflow as tftf.rawops.TensorSummaryV2 tag=np.array'test', tensor=np.array3,...

PYSEC-2026-3265 Missing validation causes `TensorSummaryV2` to crash

Impact The implementation of tf.rawops.TensorSummaryV2 does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import numpy as np import tensorflow as tf tf.rawops.TensorSummaryV2 tag=np.array'test',...

Integer overflow in Tensorflow

ImpactThe implementation of OpLevelCostEstimator::CalculateTensorSize is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements:ccint64t OpLevelCostEstimator::CalculateTensorSize const OpInfo::TensorProperties&...

`CHECK`-failures in `TensorByteSize` in Tensorflow

ImpactA malicious user can cause a denial of service by altering a SavedModel such that TensorByteSize would trigger CHECK failures.ccint64t TensorByteSizeconst TensorProto& t // numelements returns -1 if shape is not fully defined. int64t numelems = TensorShapet.tensorshape.numelements; return...

Division by zero in Tensorflow

Impact The implementation of FractionalMaxPool can be made to crash a TensorFlow process via a division by 0:pythonimport tensorflow as tfimport numpy as nptf.rawops.FractionalMaxPool value=tf.constantvalue=1, 4, 2, 3, dtype=tf.int64, poolingratio=1.0, 1.44, 1.73, 1.0, pseudorandom=False,...

PYSEC-2026-3108 `CHECK`-failures during Grappler's `SafeToRemoveIdentity` in Tensorflow

Impact The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a SavedModel such that SafeToRemoveIdentity would trigger CHECK failures. Patches We have patched the issue in GitHub commit 92dba16749fae36c246bec3f9ba474d9ddeb7662. The fix will be included in...

PYSEC-2026-3160 Integer overflow in Tensorflow

Impact The implementation of OpLevelCostEstimator::CalculateTensorSize is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements: cc int64t OpLevelCostEstimator::CalculateTensorSize const OpInfo::TensorProperties&...

Out of bounds write in Tensorflow

ImpactTensorFlow is vulnerable to a heap OOB write in Grappler:ccStatus SetUnknownShapeconst NodeDef node, int outputport shapeinference::ShapeHandle shape = GetUnknownOutputShapenode, outputport; InferenceContext ctx = GetContextnode; if ctx == nullptr return errors::InvalidArgument"Missing...

PYSEC-2026-3109 Out of bounds write in Tensorflow

Impact TensorFlow is vulnerable to a heap OOB write in Grappler: cc Status SetUnknownShapeconst NodeDef node, int outputport shapeinference::ShapeHandle shape = GetUnknownOutputShapenode, outputport; InferenceContext ctx = GetContextnode; if ctx == nullptr return errors::InvalidArgument"Missing...

PYSEC-2026-3158 Memory exhaustion in Tensorflow

Impact The implementation of ThreadPoolHandle can be used to trigger a denial of service attack by allocating too much memory: python import tensorflow as tf y = tf.rawops.ThreadPoolHandlenumthreads=0x60000000,displayname='tf' This is because the numthreads argument is only checked to not be...

Memory exhaustion in Tensorflow

Impact The implementation of ThreadPoolHandle can be used to trigger a denial of service attack by allocating too much memory:pythonimport tensorflow as tfy = tf.rawops.ThreadPoolHandlenumthreads=0x60000000,displayname='tf'This is because the numthreads argument is only checked to not be negative...

PYSEC-2026-3145 Memory exhaustion in Tensorflow

Impact The implementation of StringNGrams can be used to trigger a denial of service attack by causing an OOM condition after an integer overflow: python import tensorflow as tf tf.rawops.StringNGrams data='123456', datasplits=0,1, separator='a'15, ngramwidths=, leftpad='', rightpad='',...