PT-2026-98813

Name of the Vulnerable Software and Affected Versions Linux kernel affected versions not specified Description An issue exists in the BPF Berkeley Packet Filter subsystem where a register invariants violation occurs during speculative pointer arithmetic. When processing instructions in adjust ptr...

CVE-2026-84499 Automation-controller: automation-controller-container: automation-controller: write-only survey password recovered in plaintext via schedule/workflowjobtemplatenode survey min/max validation error message

A flaw was found in Red Hat Ansible Automation Platform's automation- controller. Survey questions of type password are write-only and stored encrypted, displayed only as a placeholder on read. When a schedule or workflow job template node is revalidated against a tightened survey specification,...

EUVD-2026-46353

Data::SortedSet::Shared versions before 0.03 for Perl allow an out-of-bounds read via unvalidated node indices in the rank and min/max query paths. The attach-time validator ssvalidateheader bounds only the root index against the node pool nodecapacity. The order-statistics and min/max queries th...

CVE-2026-59140

Data::SortedSet::Shared versions before 0.03 for Perl allow an out-of-bounds read via unvalidated node indices in the rank and min/max query paths. The attach-time validator ssvalidateheader bounds only the root index against the node pool nodecapacity. The order-statistics and min/max queries th...

CVE-2026-59140 Data::SortedSet::Shared versions before 0.03 for Perl allow an out-of-bounds read via unvalidated node indices in the rank and min/max query paths

Data::SortedSet::Shared versions before 0.03 for Perl allow an out-of-bounds read via unvalidated node indices in the rank and min/max query paths. The attach-time validator ssvalidateheader bounds only the root index against the node pool nodecapacity. The order-statistics and min/max queries th...

CVE-2026-59140

The Data::SortedSet::Shared Perl module (versions before 0.03 ) is vulnerable to an out-of-bounds read . The issue stems from the ss_validate_header validator only checking the root index against the node pool capacity, while the rank , min , and max query paths read children[], leftmost, and rig...

CVE-2026-59140 Data::SortedSet::Shared versions before 0.03 for Perl allow an out-of-bounds read via unvalidated node indices in the rank and min/max query paths

Data::SortedSet::Shared versions before 0.03 for Perl allow an out-of-bounds read via unvalidated node indices in the rank and min/max query paths. The attach-time validator ssvalidateheader bounds only the root index against the node pool nodecapacity. The order-statistics and min/max queries th...

CVE-2026-59140: Out-of-bounds Read

Data::SortedSet::Shared versions before 0.03 for Perl allow an out-of-bounds read via unvalidated node indices in the rank and min/max query paths. The attach-time validator ssvalidateheader bounds only the root index against the node pool nodecapacity. The order-statistics and min/max queries th...

TensorFlow vulnerable to segfault in `QuantizedMatMul`

ImpactIf QuantizedMatMul is given nonscalar input for: - mina - maxa - minb - maxbIt gives a segfault that can be used to trigger a denial of service attack.pythonimport tensorflow as tfToutput = tf.qint32transposea = Falsetransposeb = FalseTactivation = tf.quint8a = tf.constant7, shape=3,4,...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVars`

ImpactIf 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.pythonimport tensorflow as tfnumbits = 8narrowrange = Falseinputs = tf.constant0, shape=2,3, dtype=tf.float32min = tf.constant0,...

PYSEC-2026-3338 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

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. python import tensorflow as tf arg0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

ImpactWhen 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.pythonimport tensorflow as tfarg0=tf.random.uniformshape=1,1, dtype=tf.float32,...

PYSEC-2026-3199 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

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. python import tensorflow as tf arg0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient`

ImpactWhen 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.pythonimport tensorflow as tfarg0=tf.random.uniformshape=1,1, dtype=tf.float32,...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsGradient`

ImpactWhen tf.quantization.fakequantwithminmaxvarsgradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2,...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsGradient`

ImpactWhen tf.quantization.fakequantwithminmaxvarsgradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack.pythonimport tensorflow as tfimport numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2,...

PYSEC-2026-3364 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsGradient`

Impact When tf.quantization.fakequantwithminmaxvarsgradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf import numpy as np arg0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2, dtype=tf.float...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`

ImpactIf FakeQuantWithMinMaxVarsPerChannel is given min or max tensors of a rank other than one, it results in a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfnumbits = 8narrowrange = Falseinputs = tf.constant0, shape=4, dtype=tf.float32min =...

TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`

ImpactIf FakeQuantWithMinMaxVarsPerChannel is given min or max tensors of a rank other than one, it results in a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfnumbits = 8narrowrange = Falseinputs = tf.constant0, shape=4, dtype=tf.float32min =...

PYSEC-2026-3152 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`

Impact If FakeQuantWithMinMaxVarsPerChannel is given min or max tensors of a rank other than one, it results in a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf numbits = 8 narrowrange = False inputs = tf.constant0, shape=4, dtype=tf.float32 min ...