CVE-2026-1801C

CVE-2026-1801C QUANTUM-SHIFT / CVE-2026-180A7 BAL-JUMP: Source 2 server.dll의 이동 입력 휴리스틱에 대한 정적 분석 초록 본 논문은 Counter-Strike 2 엔진server.dll에 구현된 두 개의 클라이언트 측 이동 검증 루틴에 대한 정적 리버스 엔지니어링 분석을 제시한다: 입력 자동화 / SOCD 평가기sub1801C6B30, CVE-2026-1801C / QUANTUM-SHIFT 로 지정 및 점프 요청 속도 제한기sub180A7EDB0,...

CVE-2026-7482

CVE-2026-7482: Ollama GGUF 힙 OOB 읽기 재현 이 저장소는 취약한 Ollama GGUF 로딩 및 양자화 경로에서 발생하는 힙 out-of-bounds 읽기인 CVE-2026-7482에 대한 로컬 재현 스크립트를 포함합니다. 이 작업의 중요한 결과는 좁은 범위에 한정됩니다: 힙 OOB 조건을 안정적으로 발생시키고 OOB의 영향을 받는 양자화된 GGUF 아티팩트를 생성할 수 있었습니다. 그러나 평문 비밀 복구나 결과 아티팩트에서 카나리 문자열의 직접 추출과 같은 명확한 블랙박스 영향은 입증하지 못했습니다. ...

Improper Validation of Specified Quantity in Input

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Improper Validation of Specified Quantity in Input in allreducermsfusion.py when registering pattern replacements for mixed-dtype allreduce RMSNorm...

PT-2026-95545

Name of the Vulnerable Software and Affected Versions LMDeploy versions 0.12.1 through 0.12.2 Description Code injection is possible when loading a malicious HuggingFace model. The issue occurs because the quant dtype value from the model's quantization config is passed to the eval function in...

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...

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...

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 segfault TFLite converter on per-channel quantized transposed convolutions

ImpactWhen converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process.pythonimport tensorflow as tfclass QuantConv2DTransposedtf.keras.layers.Layer: def buildself, inputshape: self.kernel = self.addweight"kernel", 3, 3,...

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,...

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 ...

TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions

ImpactWhen converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process.pythonimport tensorflow as tfclass QuantConv2DTransposedtf.keras.layers.Layer: def buildself, inputshape: self.kernel = self.addweight"kernel", 3, 3,...

PT-2026-59905

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, input shape: self.kernel = self.add weight"kernel", 3, 3,...

PT-2026-59978

Impact When tf.quantization.fake quant with min max vars gradient 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 arg 0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2,...

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...

PT-2026-59850

Impact When tf.quantization.fake quant with min max vars gradient 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 arg 0=tf.constantvalue=np.random.randomsize=2, 2, shape=2, 2,...

PT-2026-59745

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, input shape: self.kernel = self.add weight"kernel", 3, 3,...

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...

PT-2026-57221

ESF-IDF is the Espressif Internet of Things IOT Development Framework. Versions 6.0.1, 5.5.4, 5.4.4, 5.3.5, and possibly prior contain an out-of-bounds write in jpeg parse dqt marker in components/esp driver jpeg/jpeg parse marker.c because the attacker-controlled DQT marker Tq nibble is used as ...

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...