CVE-2026-1801C

CVE-2026-1801C QUANTUM-SHIFT / CVE-2026-180A7 BAL-JUMP: Source 2（server.dll）における移動入力ヒューリスティックの静的解析 概要 本稿では、Counter-Strike 2 エンジン（server.dll）に実装された2つのクライアント側移動検証ルーチン、すなわち入力自動化 / SOCD 評価器（sub1801C6B30、CVE-2026-1801C / QUANTUM-SHIFT と指定）およびジャンプ要求レートリミッタ（sub180A7EDB0、CVE-2026-180A7 / BAL-JUMP...

CVE-2026-7482

CVE-2026-7482: Ollama GGUF ヒープ領域外読み取りの再現 このリポジトリには、脆弱性のある Ollama GGUF 読み込みおよび量子化パスにおけるヒープ領域外読み取り（CVE-2026-7482）のローカル再現スクリプトが含まれています。 この作業で重要な結果は限定的です。ヒープ領域外（OOB）状態を確実に発生させ、OOB の影響を受けた量子化 GGUF アーティファクトを生成することはできました。しかし、平文シークレットの確実な復元や、生成されたアーティファクトからのカナリア文字列の直接抽出など、明確なブラックボックス的な影響を示すことはできませんでした。 こ...

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...

PYSEC-2026-3234 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...

PYSEC-2026-3306 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 ...

PYSEC-2026-3291 TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions

Impact When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process. python import tensorflow as tf class QuantConv2DTransposedtf.keras.layers.Layer: def buildself, inputshape: self.kernel = self.addweight"kernel", 3, 3,...

PT-2026-59952

Impact When tf.quantization.fake quant with min max vars per channel gradient 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 arg 0=tf.random.uniformshape=1,1, dtype=tf.float32, maxval=None arg...

CVE-2026-55687

CVE-2026-55687 describes a stack-based out-of-bounds write in the Espressif ESF-IDF JPEG decoder marker parsing (jpeg_parse_dqt_marker). The attack uses the attacker-controlled DQT marker Tq nibble as an index into the qt_tbl array without validating it is within 0..3, enabling malformed JPEG inp...

PYSEC-2026-3141 Core dump when loading TFLite models with quantization in TensorFlow

Impact Certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling...

PYSEC-2026-3299 Core dump when loading TFLite models with quantization in TensorFlow

Impact Certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling...

CVE-2026-5757

A flaw was found in Ollama's model quantization engine. An unauthenticated remote attacker can exploit this vulnerability to read and exfiltrate the server's heap memory. This could lead to sensitive data exposure, further compromise of the system, and allow for stealthy persistence within the...

PYSEC-2026-1031 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...

PYSEC-2026-965 TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions

Impact When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process. python import tensorflow as tf class QuantConv2DTransposedtf.keras.layers.Layer: def buildself, inputshape: self.kernel = self.addweight"kernel", 3, 3,...

PYSEC-2026-972 Core dump when loading TFLite models with quantization in TensorFlow

Impact Certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling...

CVE-2026-5757

Unauthenticated remote information disclosure vulnerability in Ollama's model quantization engine allows an attacker to read and exfiltrate the server's heap memory, potentially leading to sensitive data exposure, further compromise, and stealthy persistence...

CVE-2026-5757

Unauthenticated remote information disclosure vulnerability in Ollama's model quantization engine allows an attacker to read and exfiltrate the server's heap memory, potentially leading to sensitive data exposure, further compromise, and stealthy persistence...

CVE-2026-5757

CVE-2026-5757 concerns Ollama’s model quantization engine. The CERT entry describes an unauthenticated remote information-disclosure vulnerability triggered via the model upload interface. Root cause: three factors—no bounds checking on user-supplied GGUF header metadata, unsafe memory access usi...

CVE-2026-5757 There exists an unauthenticated remote information disclosure vulnerability in Ollama's model quantization engine

Unauthenticated remote information disclosure vulnerability in Ollama's model quantization engine allows an attacker to read and exfiltrate the server's heap memory, potentially leading to sensitive data exposure, further compromise, and stealthy persistence...

EUVD-2026-39786

Unauthenticated remote information disclosure vulnerability in Ollama's model quantization engine allows an attacker to read and exfiltrate the server's heap memory, potentially leading to sensitive data exposure, further compromise, and stealthy persistence...

CVE-2026-5757 There exists an unauthenticated remote information disclosure vulnerability in Ollama's model quantization engine

Unauthenticated remote information disclosure vulnerability in Ollama's model quantization engine allows an attacker to read and exfiltrate the server's heap memory, potentially leading to sensitive data exposure, further compromise, and stealthy persistence...