Open actionable advisories and recorded vendor fixes. This public package view has no inventory attached and cannot establish whether your deployment is affected. A vendor fix never resolves your finding; verify your installed version and the source guidance.
Open advisories
433 actionable advisories, newest first. Withdrawn advisories and news are excluded. Coverage is partial.
Impact If Save or SaveSlices is run over tensors of an unsupported dtype, it results in a CHECK fail that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 5dd7b86b84a864b834c6fa3d7f9f51c87efa99d4. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Di Jin, Secure Systems Labs, Brown University
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact ParameterizedTruncatedNormal assumes shape is of type int32. A valid shape of type int64 results in a mismatched type CHECK fail that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 72180be03447a10810edca700cbc9af690dfeb51. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Di Jin, Secure Systems Labs, Brown University
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact If LRNGrad is given an outputimage input tensor that is not 4-D, it results in a CHECK fail that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Di Jin, Secure Systems Labs, Brown University
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact If RaggedBincount is given an empty input tensor splits, it results in a segfault that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 7a4591fd4f065f4fa903593bc39b2f79530a74b8. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Di Jin, Secure Systems Labs, Brown University
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact When tf.linalg.matrixrank receives an empty input a, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Kang Hong Jin.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact When MaxPool receives a window size input array ksize with dimensions greater than its input tensor input, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 32d7bd3defd134f21a4e344c8dfd40099aaf6b18. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Jingyi Shi.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact If SparseBincount is given inputs for indices, values, and denseshape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Di Jin, Secure Systems Labs, Brown University
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact FractionalMaxPoolGrad validates its inputs with CHECK failures instead of with returning errors. If it gets incorrectly sized inputs, the CHECK failure can be used to trigger a denial of service attack: Patches We have patched the issue in GitHub commit 8741e57d163a079db05a7107a7609af70931def4. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact If QuantizedRelu or QuantizedRelu6 are given nonscalar inputs for minfeatures or maxfeatures, it results in a segfault that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact If QuantizeDownAndShrinkRange is given nonscalar inputs for inputmin or inputmax, it results in a segfault that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact If QuantizedMatMul is given nonscalar input for: - mina - maxa - minb - maxb It gives a segfault that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact If QuantizedBiasAdd is given mininput, maxinput, minbias, maxbias tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact 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. Patches We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by: - Neophytos Christou, Secure Systems Labs, Brown University. - 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact 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. Patches We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact 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: Patches We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack: Patches We have patched the issue in GitHub commit 3a6ac52664c6c095aa2b114e742b0aa17fdce78f. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact If QuantizedAdd is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact If QuantizedAvgPool is given mininput or maxinput tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact When tf.quantization.fakequantwithminmaxvarsperchannelgradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack. Patches We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. 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 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 - Neophytos Christou, Secure Systems Labs, Brown University
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact When TensorListScatter and TensorListScatterV2 receive an elementshape of a rank greater than one, they give a CHECK fail that can trigger a denial of service attack. Patches We have patched the issue in GitHub commit bb03fdf4aae944ab2e4b35c7daa051068a8b7f61. 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 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.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact If LowerBound or UpperBound is given an emptysortedinputs input, it results in a nullptr dereference, leading to a segfault that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit bce3717eaef4f769019fd18e990464ca4a2efeea. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact When TensorListFromTensor receives an elementshape of a rank greater than one, it gives a CHECK fail that can trigger a denial of service attack. Patches We have patched the issue in GitHub commit 3db59a042a38f4338aa207922fa2f476e000a6ee. 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 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.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact When SetSize receives an input setshape that is not a 1D tensor, it gives a CHECK fails that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit cf70b79d2662c0d3c6af74583641e345fc939467. 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 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.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact The implementation of BlockLSTMGradV2 does not fully validate its inputs. - wci, wcf, wco, b must be rank 1 - w, csprev, hprev must be rank 2 - x must be rank 3 This results in a a segfault that can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 2a458fc4866505be27c62f81474ecb2b870498fa. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.
Impact The implementation of FractionalAvgPoolGrad does not fully validate the input originputtensorshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack. Patches We have patched the issue in GitHub commit 03a659d7be9a1154fdf5eeac221e5950fec07dad. 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 for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Recommended action: Upgrade to 2.9.1, 2.8.1 or 2.7.2 by release line, then redeploy and verify.A vendor fix does not resolve your finding until you verify it in your own systems.