CVE-2026-84546

An out-of-bounds write issue was addressed with improved bounds checking. This issue is fixed in iOS 26.7 and iPadOS 26.7, iOS 27 and iPadOS 27, macOS Golden Gate 27, macOS Sequoia 15.8, macOS Tahoe 26.7, tvOS 27, visionOS 27, watchOS 27. Processing a maliciously crafted 3D model may lead to memo...

CVE-2026-84546

Apple has addressed an out-of-bounds write vulnerability in several operating systems, including iOS , iPadOS , macOS , tvOS , visionOS , and watchOS . The root cause involves insufficient bounds checking when processing a maliciously crafted 3D model , which can lead to memory corruption . This ...

EUVD-2026-78011

An out-of-bounds write issue was addressed with improved bounds checking. This issue is fixed in iOS 26.7 and iPadOS 26.7, iOS 27 and iPadOS 27, macOS Golden Gate 27, macOS Sequoia 15.8, macOS Tahoe 26.7, tvOS 27, visionOS 27, watchOS 27. Processing a maliciously crafted 3D model may lead to memo...

CVE-2026-84632

The issue was addressed with improved memory handling. This issue is fixed in iOS 26.7 and iPadOS 26.7, iOS 27 and iPadOS 27, macOS Golden Gate 27, macOS Sequoia 15.8, macOS Tahoe 26.7, tvOS 27, visionOS 27, watchOS 27. Processing a maliciously crafted 3D model may lead to memory corruption...

CVE-2026-84632

Processing a maliciously crafted 3D model can lead to memory corruption in several Apple products. This vulnerability was addressed with improved memory handling and is fixed in iOS 26.7 , iPadOS 26.7 , iOS 27 , iPadOS 27 , macOS Golden Gate 27 , macOS Sequoia 15.8 , macOS Tahoe 26.7 , tvOS 27 , ...

CVE-2026-84632

The issue was addressed with improved memory handling. This issue is fixed in iOS 26.7 and iPadOS 26.7, iOS 27 and iPadOS 27, macOS Golden Gate 27, macOS Sequoia 15.8, macOS Tahoe 26.7, tvOS 27, visionOS 27, watchOS 27. Processing a maliciously crafted 3D model may lead to memory corruption...

EUVD-2026-78095

The issue was addressed with improved memory handling. This issue is fixed in iOS 26.7 and iPadOS 26.7, iOS 27 and iPadOS 27, macOS Golden Gate 27, macOS Sequoia 15.8, macOS Tahoe 26.7, tvOS 27, visionOS 27, watchOS 27. Processing a maliciously crafted 3D model may lead to memory corruption...

EUVD-2026-78082

IBM Business Automation Workflow containers and traditional may use programming model artifacts that are vulnerable to XML Entity Injection attacks by default...

CVE-2026-13107 Multiple secuirty vulnerabilies addressed with IBM Business Automation Workflow August 2026

IBM Business Automation Workflow containers and traditional may use programming model artifacts that are vulnerable to XML Entity Injection attacks by default...

CVE-2026-13107

IBM Business Automation Workflow (containers and traditional) versions 24.0.0-IF009, 24.0.1-IF008, 25.0.0-IF005, and 26.0.0-IF001 may use programming model artifacts in Advanced custom applications that are vulnerable to XML External Entity (XXE) injection by default (CWE-611). A remote authentic...

CVE-2026-13107 Multiple secuirty vulnerabilies addressed with IBM Business Automation Workflow August 2026

IBM Business Automation Workflow containers and traditional may use programming model artifacts that are vulnerable to XML Entity Injection attacks by default...

CVE-2026-54559

PocketSphinx is a small speech recognizer. Prior to 5.1.1, the trie language-model loaders in src/lm/ngrammodeltrie.c do not adequately validate boundary conditions in ARPA, DMP, and binary format headers, and the acoustic-model loaders in src/mdef.c and src/util/bio.c use sscanf with unbounded...

CVE-2026-54559 PocketSphinx: Buffer overflows in language and acoustic model loading code

PocketSphinx is a small speech recognizer. Prior to 5.1.1, the trie language-model loaders in src/lm/ngrammodeltrie.c do not adequately validate boundary conditions in ARPA, DMP, and binary format headers, and the acoustic-model loaders in src/mdef.c and src/util/bio.c use sscanf with unbounded...

EUVD-2026-78066

PocketSphinx is a small speech recognizer. Prior to 5.1.1, the trie language-model loaders in src/lm/ngrammodeltrie.c do not adequately validate boundary conditions in ARPA, DMP, and binary format headers, and the acoustic-model loaders in src/mdef.c and src/util/bio.c use sscanf with unbounded...

CVE-2026-54559

PocketSphinx (a lightweight speech recognizer, including its Python bindings) versions 5prealpha through 5.1.0 are affected by buffer overflow vulnerabilities in its model-loading code. The trie language-model loaders in src/lm/ngram_model_trie.c fail to validate boundary conditions in ARPA, DMP,...

CVE-2026-54559 PocketSphinx: Buffer overflows in language and acoustic model loading code

PocketSphinx is a small speech recognizer. Prior to 5.1.1, the trie language-model loaders in src/lm/ngrammodeltrie.c do not adequately validate boundary conditions in ARPA, DMP, and binary format headers, and the acoustic-model loaders in src/mdef.c and src/util/bio.c use sscanf with unbounded...

CVE-2026-54559 PocketSphinx: Buffer overflows in language and acoustic model loading code

PocketSphinx is a small speech recognizer. Prior to 5.1.1, the trie language-model loaders in src/lm/ngrammodeltrie.c do not adequately validate boundary conditions in ARPA, DMP, and binary format headers, and the acoustic-model loaders in src/mdef.c and src/util/bio.c use sscanf with unbounded...

EUVD-2026-77721

Tract is a tiny, no-nonsense, self-contained TensorFlow and ONNX inference toolkit. Prior to 0.21.17, 0.22.3, and 0.23.2, the tract-onnx crate passes the attacker-controlled externaldata location from an ONNX model through onnx/src/tensor.rs getexternalresources and joins the value to the model...

CVE-2026-55832

Tract (tract-onnx crate, a Rust inference toolkit for TensorFlow/ONNX) is vulnerable to arbitrary local file read when loading an untrusted ONNX model. The external_data location field is joined to the model directory via Path::join without rejecting absolute paths or .. components, so the defaul...

CVE-2026-55832 Tract: Arbitrary file read via unsanitized ONNX external_data `location` (path traversal) on model load in tract-onnx

Tract is a tiny, no-nonsense, self-contained TensorFlow and ONNX inference toolkit. Prior to 0.21.17, 0.22.3, and 0.23.2, the tract-onnx crate passes the attacker-controlled externaldata location from an ONNX model through onnx/src/tensor.rs getexternalresources and joins the value to the model...