ai-exploits
fury-benchmarks
| ai-exploits | fury-benchmarks | |
|---|---|---|
| 6 | 4 | |
| 1,317 | 2 | |
| 6.9% | - | |
| 7.0 | 5.9 | |
| 15 days ago | about 1 month ago | |
| Python | Java | |
| GNU General Public License v3.0 or later | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ai-exploits
- RCE in Nvidia Triton Inference Server
- FLaNK Stack Weekly for 20 Nov 2023
-
AI-Exploits: Repo of multiple unauthenticated RCEs in AI tools
(I work for ProtectAI) We added a quick demo to the Readme [1]
[1] https://github.com/protectai/ai-exploits?tab=readme-ov-file#...
fury-benchmarks
- FLaNK Stack Weekly for 20 Nov 2023
- FLaNK Stack Weekly for 30 Oct 2023
-
Fury: 170x faster than JDK, fast serialization powered by JIT and Zero-copy
1) Fury is 41.6x faster than jackson for Struct serialization 2) Fury is 65.6x faster than jackson for Struct deserialization 3) Fury is 9.4x faster than jackson for MediaContent serialization 4) Fury is 9.6x faster than jackson for MediaContent deserialization
see https://github.com/chaokunyang/fury-benchmarks for detailed benchmark code.
What are some alternatives?
memq - MemQ is an efficient, scalable cloud native PubSub system
jvm-serializers - Benchmark comparing serialization libraries on the JVM
depthai-python - DepthAI Python Library
MemoryPack - Zero encoding extreme performance binary serializer for C# and Unity.
awesome-public-real-time-datasets - A list of publicly available datasets with real-time data maintained by the team at bytewax.io
MessagePack for C# (.NET, .NET Core, Unity, Xamarin) - Extremely Fast MessagePack Serializer for C#(.NET, .NET Core, Unity, Xamarin). / msgpack.org[C#]
StyleTTS2 - StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models
grpc-dotnet - gRPC for .NET
torchgeo - TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
incubator-fury - A blazingly fast multi-language serialization framework powered by JIT and zero-copy.
imgbeddings - Python package to generate image embeddings with CLIP without PyTorch/TensorFlow
orbital - Orbital automates integration between data sources (APIs, Databases, Queues and Functions). BFF's, API Composition and ETL pipelines that adapt as your specs change.