Traffic-Aware Randomized Smoothing for LLM-Based Network Intrusion Detection

Large language model LLM-based intrusion detection systems IDS are increasingly studied for security monitoring, yet their robustness against feasible traffic manipulation remains largely empirical. We present Traffic-Aware Randomized Smoothing TA-RS, a classifier-agnostic certified defense that...

EUVD-2026-43923

Improper access control in Windows System allows an unauthorized attacker to bypass a security feature locally...

CVE-2026-62194

OpenClaw versions 2026.5.20 before 2026.6.9 contain a privilege escalation vulnerability in plugin install commands that allows lower-trust callers to execute or persist actions beyond their intended authorization. Attackers can exploit misconfigured input paths or enabled features to escalate...

CVE-2026-62194

OpenClaw versions 2026.5.20 before 2026.6.9 contain a privilege escalation vulnerability in plugin install commands that allows lower-trust callers to execute or persist actions beyond their intended authorization. Attackers can exploit misconfigured input paths or enabled features to escalate...

CVE-2026-62194 OpenClaw 2026.5.20 < 2026.6.9 Privilege Escalation via Plugin Install

OpenClaw versions 2026.5.20 before 2026.6.9 contain a privilege escalation vulnerability in plugin install commands that allows lower-trust callers to execute or persist actions beyond their intended authorization. Attackers can exploit misconfigured input paths or enabled features to escalate...

`CHECK` fail via inputs in `SdcaOptimizer`

ImpactInputs densefeatures or examplestatedata not of rank 2 will trigger a CHECK fail in SdcaOptimizer.pythonimport tensorflow as tftf.rawops.SdcaOptimizer sparseexampleindices=4 tf.random.uniform5,5,5,3, dtype=tf.dtypes.int64, maxval=100, sparsefeatureindices=4 tf.random.uniform5,5,5,3,...

PYSEC-2026-3086 `CHECK` fail via inputs in `SdcaOptimizer`

Impact Inputs densefeatures or examplestatedata not of rank 2 will trigger a CHECK fail in SdcaOptimizer. python import tensorflow as tf tf.rawops.SdcaOptimizer sparseexampleindices=4 tf.random.uniform5,5,5,3, dtype=tf.dtypes.int64, maxval=100, sparsefeatureindices=4 tf.random.uniform5,5,5,3,...

PYSEC-2026-3264 `CHECK` fail via inputs in `SdcaOptimizer`

Impact Inputs densefeatures or examplestatedata not of rank 2 will trigger a CHECK fail in SdcaOptimizer. python import tensorflow as tf tf.rawops.SdcaOptimizer sparseexampleindices=4 tf.random.uniform5,5,5,3, dtype=tf.dtypes.int64, maxval=100, sparsefeatureindices=4 tf.random.uniform5,5,5,3,...

`CHECK` fail via inputs in `SdcaOptimizer`

ImpactInputs densefeatures or examplestatedata not of rank 2 will trigger a CHECK fail in SdcaOptimizer.pythonimport tensorflow as tftf.rawops.SdcaOptimizer sparseexampleindices=4 tf.random.uniform5,5,5,3, dtype=tf.dtypes.int64, maxval=100, sparsefeatureindices=4 tf.random.uniform5,5,5,3,...

PYSEC-2026-3245 TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`

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. python import tensorflow as tf outtype = tf.quint8 features = tf.constant28, shape=4,2, dtype=tf.quint8 minfeatures...

TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`

ImpactIf 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.pythonimport tensorflow as tfouttype = tf.quint8features = tf.constant28, shape=4,2, dtype=tf.quint8minfeatures =...

PYSEC-2026-3372 TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`

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. python import tensorflow as tf outtype = tf.quint8 features = tf.constant28, shape=4,2, dtype=tf.quint8 minfeatures...

PT-2026-59986

Impact If QuantizedRelu or QuantizedRelu6 are given nonscalar inputs for min features or max features, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf out type = tf.quint8 features = tf.constant28, shape=4,2, dtype=tf.quint8 min...

PT-2026-59860

Impact If QuantizedRelu or QuantizedRelu6 are given nonscalar inputs for min features or max features, it results in a segfault that can be used to trigger a denial of service attack. python import tensorflow as tf out type = tf.quint8 features = tf.constant28, shape=4,2, dtype=tf.quint8 min...

PT-2026-57896

OpenClaw versions 2026.5.20 before 2026.6.9 contain a privilege escalation vulnerability in plugin install commands that allows lower-trust callers to execute or persist actions beyond their intended authorization. Attackers can exploit misconfigured input paths or enabled features to escalate...

PT-2026-59879

Impact Inputs dense features or example state data not of rank 2 will trigger a CHECK fail in SdcaOptimizer. python import tensorflow as tf tf.raw ops.SdcaOptimizer sparse example indices=4 tf.random.uniform5,5,5,3, dtype=tf.dtypes.int64, maxval=100, sparse feature indices=4...

CVE-2026-15286 Gutenberg Blocks with AI by Kadence WP – Page Builder Features <= 3.5.32 - Incorrect Authorization to Authenticated (Contributor+) Post Publication

The Gutenberg Blocks with AI by Kadence WP – Page Builder Features plugin for WordPress is vulnerable to unauthorized post publication in all versions up to, and including, 3.5.32 due to a misconfigured capability check on the 'getitemspermissioncheck' function permission callback of the...

CVE-2026-15286: Incorrect Authorization

The Gutenberg Blocks with AI by Kadence WP – Page Builder Features plugin for WordPress is vulnerable to unauthorized post publication in all versions up to, and including, 3.5.32 due to a misconfigured capability check on the 'getitemspermissioncheck' function permission callback of the...

Wireshark Analyzer 4.6.7

Wireshark is a GTK+-based network protocol analyzer that lets you capture and interactively browse the contents of network frames. The goal of the project is to create a commercial-quality analyzer for Unix and Win32 and to give Wireshark features that are missing from closed-source sniffers. Thi...

A Bootiful Podcast: Spring Boot legend Moritz Halbritter on the latest and greatest in Spring Boot 4 and 4.1

Hi Spring fans! Spring Boot 4.1 is here and with it a ton of amazing features. I'm delighted to have had the opportunity to sit down with Moritz Halbritter, of Spring Boot and Spring Initializr fame, to talk about some of the amazing features...