441 matches found
GHSA-8FXR-QFR9-P34W TorchServe Server-Side Request Forgery vulnerability
Impact Remote Server-Side Request Forgery SSRF Issue: TorchServe default configuration lacks proper input validation, enabling third parties to invoke remote HTTP download requests and write files to the disk. This issue could be taken advantage of to compromise the integrity of the system and...
The software environment for training and deploying deep neural networks, Apache MXNet, has vulnerabilities related to uncontrolled resource consumption. This allows attackers to trigger service failures.
The vulnerability of the Apache MXNet software environment for training and deploying deep neural networks is related to an uncontrolled resource consumption during the loading of models with operator names. Exploiting this vulnerability could allow a malicious actor to cause service failures...
PT-2022-3914
Name of the Vulnerable Software and Affected Versions Apache MXNet versions prior to 1.9.1 Description A regular expression used in Apache MXNet is vulnerable to a potential denial-of-service by excessive resource consumption. The issue could be exploited when loading a model in Apache MXNet that...
Apache MXNet 安全漏洞
Apache MXNet is an open source deep learning software framework from the Apache Apache Foundation in the United States. It is used for training and deploying deep neural networks. A security vulnerability exists in Apache MXNet incubating versions prior to 1.9.1, which stems from the use of regul...
GHSA-H22X-HM8G-RXPG Improper Restriction of XML External Entity Reference in Apache OpenNLP
When loading models or dictionaries that contain XML it is possible to perform an XXE attack, since Apache OpenNLP is a library, this only affects applications that load models or dictionaries from untrusted sources. The versions 1.5.0 to 1.5.3, 1.6.0, 1.7.0 to 1.7.2, 1.8.0 to 1.8.1 of Apache...
GHSA-H67M-XG8F-FXCF Deadlock in mutually recursive `tf.function` objects
Impact The code behind tf.function API can be made to deadlock when two tf.function decorated Python functions are mutually recursive: python import tensorflow as tf @tf.function def fun1num: if num == 1: return printnum fun2num-1 @tf.function def fun2num: if num == 0: return printnum fun1num-1...
PYSEC-2021-820
TensorFlow is an open source platform for machine learning. In affected versions the code behind tf.function API can be made to deadlock when two tf.function decorated Python functions are mutually recursive. This occurs due to using a non-reentrant Lock Python object. Loading any model which...
PYSEC-2021-405
TensorFlow is an open source platform for machine learning. In affected versions the code behind tf.function API can be made to deadlock when two tf.function decorated Python functions are mutually recursive. This occurs due to using a non-reentrant Lock Python object. Loading any model which...
CVE-2021-41213
TensorFlow is an open source platform for machine learning. In affected versions the code behind tf.function API can be made to deadlock when two tf.function decorated Python functions are mutually recursive. This occurs due to using a non-reentrant Lock Python object. Loading any model which...
CVE-2021-41213
TensorFlow is an open source platform for machine learning. In affected versions the code behind tf.function API can be made to deadlock when two tf.function decorated Python functions are mutually recursive. This occurs due to using a non-reentrant Lock Python object. Loading any model which...
CVE-2020-26271
In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node given by outputindex and the input slot of the dst node...
PT-2020-16394 · Google · Tensorflow
Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 1.15.5 TensorFlow versions prior to 2.0.4 TensorFlow versions prior to 2.1.3 TensorFlow versions prior to 2.2.2 TensorFlow versions prior to 2.3.2 TensorFlow versions prior to 2.4.0 Description: In affected versio...
CVE-2020-15211
In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indice...
Out-of-bounds
In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indice...
PYSEC-2020-291
In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indice...
CVE-2020-15211
CVE-2020-15211 : In TensorFlow Lite (before 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1), a negative -1 tensor index used for optional inputs can be treated as a valid index during validation, allowing out-of-bounds reads/writes in some operators. The root cause is the double indexing scheme for tensors i...
CVE-2020-15211
In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indice...
CVE-2020-15211: Out-of-bounds Read
In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indice...
