Denial Of Service (DOS)

TensorFlow is vulnerable to a denial of service. The vulnerability is due to the improper handling of the dimensionality of the output tensor in TensorFlow Lite's segment sum implementation,where the code uses the last element of the tensor holding segment IDs to determine the output tensor's siz...

Out-Of-Bounds Writes

TensorFlow is vulnerable to out-of-bounds writes. The vulnerability is due to the improper handling of negative elements in the segment ids tensor, allowing negative values that result in out-of-bounds memory writes during the segment sum operation...

Out-of-bounds Write

tensorflow, tensorflow-cpu and tensorflowgpu is vulnerable to Out-of-bounds Write. The vulnerability is due to improper handling of tensors when a model uses the same tensor for both an input and output of an operator, which can result in data loss and memory corruption...

Out-of-bounds Read

Overview Affected versions of this package are vulnerable to Out-of-bounds Read through the rpctensor structure. An attacker can read arbitrary memory addresses by manipulating the data pointer. PoC from pwn import ALLOCBUFFER = 0 GETALIGNMENT = 1 GETMAXSIZE = 2 BUFFERGETBASE = 3 FREEBUFFER = 4...

Write-what-where Condition

Overview Affected versions of this package are vulnerable to Write-what-where Condition through the rpctensor structure. An attacker can write to arbitrary memory addresses by manipulating the data pointer. PoC from pwn import ALLOCBUFFER = 0 GETALIGNMENT = 1 GETMAXSIZE = 2 BUFFERGETBASE = 3...

Out-of-bounds Read

Overview Affected versions of this package are vulnerable to Out-of-bounds Read via the rpctensor structure. An attacker can cause memory data leakage by exploiting the unsafe type member. PoC from pwn import ALLOCBUFFER = 0 GETALIGNMENT = 1 GETMAXSIZE = 2 BUFFERGETBASE = 3 FREEBUFFER = 4...

llama.cpp 安全漏洞

llama.cpp is a multimodal model. llama.cpp suffers from a remote code execution vulnerability that originates in the data pointer in the rpctensor structure, which can be exploited by an attacker to cause an arbitrary address to be read...

PT-2024-29975 · Llama.Cpp · Llama.Cpp

Name of the Vulnerable Software and Affected Versions: llama.cpp versions prior to b3561 Description: The issue is related to the rpc tensor structure in llama.cpp, which provides LLM inference in C/C++. The unsafe data pointer member can cause arbitrary address writing, potentially leading to...

PT-2024-29973

Name of the Vulnerable Software and Affected Versions llama.cpp version b3561 and earlier Description The issue arises from the unsafe type member in the rpc tensor structure, which can cause a global-buffer-overflow. This may lead to memory data leakage. Recommendations For versions prior to...

SUSE CVE-2023-33976

TensorFlow is an end-to-end open source platform for machine learning. arrayops.upperbound causes a segfault when not given a rank 2 tensor. The fix will be included in TensorFlow 2.13 and will also cherrypick this commit on TensorFlow 2.12...

Integer Overflow or Wraparound

Overview Affected versions of this package are vulnerable to Integer Overflow or Wraparound due to the arrayops.upperbound function. An attacker can cause a denial of service by providing input that is not a rank 2 tensor. Remediation Upgrade tensorflow-lite to version 2.15.0 or higher. Reference...

TensorFlow 输入验证错误漏洞

TensorFlow is a suite of end-to-end open source platforms for machine learning open-sourced by TensorFlow. An input validation error vulnerability exists in TensorFlow versions prior to 2.13.0, which stems from arrayops.upperbound causing a segmentation error when a 2nd order tensor is not...

llvm-project commit a0138390 was discovered to contain a segmentation fault via the component matchAndRewriteSortOp<mlir::sparse_tensor::SortOp>(mlir::sparse_tensor::SortOp.

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MAL-2024-6101 Malicious code in tensor-processor-learning (PyPI)

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Malicious code in tensor-processor-learning (PyPI)

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BIT-TENSORFLOW-2020-15190 Segfault in Tensorflow

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.rawops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. Howeve...

BIT-TENSORFLOW-2020-15198 Heap buffer overflow in Tensorflow

In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed...

BIT-TENSORFLOW-2020-15199 Denial of Service in Tensorflow

In Tensorflow before version 2.3.1, the RaggedCountSparseOutput does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the splits tensor has the minimum required number of elements. Code uses this quantity to initialize a different data...

BIT-TENSORFLOW-2020-15213 Denial of service in tensorflow-lite

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor,...

BIT-TENSORFLOW-2021-29516 Null pointer dereference via invalid Ragged Tensors

TensorFlow is an end-to-end open source platform for machine learning. Calling tf.rawops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference. The implementation of RaggedTensorToVariant...