clip-jax (=0.0.5) potentially affected by CVE-2022-35935 via tensorflow-cpu (=2.9.0)

tensorflow-cpu PYPI version =2.9.0 is affected by a known vulnerability. The following packages have a transitive dependency on tensorflow-cpu and may be impacted: - clip-jax =0.0.5 Source cves: CVE-2022-35935 Source advisory: OSV:GHSA-97P7-W86H-VCF9...

animl (>=1.1.2 <=1.1.4), arekit (>=0.21.0 <=0.22.1) +183 more potentially affected by CVE-2022-35935 via tensorflow-gpu (>=1.10.1 <=2.7.0)

tensorflow-gpu PYPI version =1.10.1, =1.1.2, =0.21.0, =0.23.0, =0.9.2, =1.0.0, =0.1.0, =0.0.1, =0.0.9, =0.1.0, =0.0.1, =1.0.0, =1.0.3 - brainhance =0.0.1 and more Source cves: CVE-2022-35935 Source advisory: OSV:GHSA-97P7-W86H-VCF9...

a62-emotion (>=0.10.12 <=0.11.4), agent-atm (>=0.1.0 <=0.1.1) +103 more potentially affected by CVE-2022-35935 via tensorflow-cpu (>=1.15.0 <=2.7.0)

tensorflow-cpu PYPI version =1.15.0, =0.10.12, =0.1.0, =2.0.0, =2.0.0, =1.0.0, =0.0.5, =0.3.0, =0.0.1, =0.8.1, =0.1.1, =1.3.0, =0.1.0.dev1, =0.1.0.dev202107081840 and more Source cves: CVE-2022-35935 Source advisory: OSV:GHSA-97P7-W86H-VCF9...

125softnlp (=0.0.1), a2 (>=0.10.11 <=0.10.13) +4899 more potentially affected by CVE-2022-35935 via tensorflow (>=1.0.1 <=2.7.1)

tensorflow PYPI version =1.0.1, =0.10.11, =0.1.0, =0.0.0, =0.5.0, =0.1.6, =1.0.0, =2.0.0, =1.0.0, =0.0.1, =0.0.7 and more Source cves: CVE-2022-35935 Source advisory: OSV:GHSA-97P7-W86H-VCF9...

acuity (=6.18.0), acuitypro (=6.18.0) +60 more potentially affected by CVE-2022-35935 via tensorflow (>=2.8.0 <=2.8.0rc1)

tensorflow PYPI version =2.8.0, =1.2.8, =1.0.43, =0.2.2, =0.0.1, =0.0.2, =0.2.8, =0.14.0, =0.1.3, =0.0.9, =0.2.27, =0.2.41 - complaintclassify =0.0.5 - conversational-sentence-encoder =0.0.6 and more Source cves: CVE-2022-35935 Source advisory: OSV:GHSA-97P7-W86H-VCF9...

aliby (>=0.1.18 <=0.1.55), aliby-baby (>=0.1.11 <=0.1.17) +29 more potentially affected by CVE-2022-35935 via tensorflow (>=2.9.0 <=2.9.0rc2)

tensorflow PYPI version =2.9.0, =0.1.18, =0.1.11, =0.30.0, =0.0.0, =1.3.0, =0.3.0, =1.0.1, =1.2.0, =0.0.6, =1.0.12, =0.1.0, =0.1.1 and more Source cves: CVE-2022-35935 Source advisory: OSV:GHSA-97P7-W86H-VCF9...

TensorFlow vulnerable to `CHECK` failure in `SobolSample` via missing validation

Impact The implementation of SobolSampleOp is vulnerable to a denial of service via CHECK-failure assertion failure caused by assuming input0, input1, and input2 to be scalar. python import tensorflow as tf tf.rawops.SobolSampledim=tf.constant1,0, numresults=tf.constant1, skip=tf.constant1 Patche...

GHSA-97P7-W86H-VCF9 TensorFlow vulnerable to `CHECK` failure in `SobolSample` via missing validation

Impact The implementation of SobolSampleOp is vulnerable to a denial of service via CHECK-failure assertion failure caused by assuming input0, input1, and input2 to be scalar. python import tensorflow as tf tf.rawops.SobolSampledim=tf.constant1,0, numresults=tf.constant1, skip=tf.constant1 Patche...

CVE-2022-35971 `CHECK` fail in `FakeQuantWithMinMaxVars` in TensorFlow

TensorFlow is an open source platform for machine learning. If FakeQuantWithMinMaxVars is given min or max tensors of a nonzero rank, it results in a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit...

CVE-2022-35971

CVE-2022-35971 affects TensorFlow: a denial-of-service risk when FakeQuantWithMinMaxVars receives min/max tensors of nonzero rank, causing a CHECK failure. Root cause: input validation in FakeQuantWithMinMaxVars leads to DoS. Known impact: remote attacker could trigger DoS via this path; exploita...

CVE-2022-35971 `CHECK` fail in `FakeQuantWithMinMaxVars` in TensorFlow

TensorFlow is an open source platform for machine learning. If FakeQuantWithMinMaxVars is given min or max tensors of a nonzero rank, it results in a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit...

CVE-2022-35971

TensorFlow is an open source platform for machine learning. If FakeQuantWithMinMaxVars is given min or max tensors of a nonzero rank, it results in a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit...

CVE-2022-35971 `CHECK` fail in `FakeQuantWithMinMaxVars` in TensorFlow

TensorFlow is an open source platform for machine learning. If FakeQuantWithMinMaxVars is given min or max tensors of a nonzero rank, it results in a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit...

CVE-2022-35969

TensorFlow CVE-2022-35969 stems from Conv2DBackpropInput requiring input_sizes to be 4-dimensional; non-conforming input can trigger a CHECK failure that allows denial of service. A fix was committed (50156d547b9a1da0144d7babe665cf690305b33c) and will be included in TensorFlow 2.10.0, with cherry...

CVE-2022-35969 `CHECK` fail in `Conv2DBackpropInput` in TensorFlow

TensorFlow is an open source platform for machine learning. The implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit...

CVE-2022-35969 `CHECK` fail in `Conv2DBackpropInput` in TensorFlow

TensorFlow is an open source platform for machine learning. The implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit...

CVE-2022-35969

TensorFlow is an open source platform for machine learning. The implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit...

CVE-2022-35969 `CHECK` fail in `Conv2DBackpropInput` in TensorFlow

TensorFlow is an open source platform for machine learning. The implementation of Conv2DBackpropInput requires inputsizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit...

CVE-2022-35970 Segfault in `QuantizedInstanceNorm` in TensorFlow

TensorFlow is an open source platform for machine learning. If QuantizedInstanceNorm is given xmin or xmax tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e...

CVE-2022-35970 Segfault in `QuantizedInstanceNorm` in TensorFlow

TensorFlow is an open source platform for machine learning. If QuantizedInstanceNorm is given xmin or xmax tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e...