NTLM Credential Theft in Python Windows Applications
The article discloses vulnerabilities in popular Python frameworks (Gradio, Jupyter Server, and Streamlit) that can lead to NTLMv2 hash theft on Windows systems through exploitation of file system operations. It explains how these vulnerabilities can be exploited, potentially leading to credential theft or remote code execution, and emphasizes the increased risk as Python applications be...
https://www.horizon3.ai/attack-research/disclosures/ntlm-credential-theft-in-python-windows-applications/
The article discloses vulnerabilities in popular Python frameworks (Gradio, Jupyter Server, and Streamlit) that can lead to NTLMv2 hash theft on Windows systems through exploitation of file system operations. It explains how these vulnerabilities can be exploited, potentially leading to credential theft or remote code execution, and emphasizes the increased risk as Python applications be...
https://www.horizon3.ai/attack-research/disclosures/ntlm-credential-theft-in-python-windows-applications/
Horizon3.ai
NTLM Credential Theft in Python Windows Applications
NTLM credential theft vulnerabilities in Python Windows applications: Jupyter Notebook CVE-2024-35178, Streamlit from Snowflake CVE-2024-42474 and Hugging Face Gradio CVE-2024-34510
New LLM Pre-training and Post-training Paradigms
A Look at How Modern LLMs Are Trained.
https://magazine.sebastianraschka.com/p/new-llm-pre-training-and-post-training
A Look at How Modern LLMs Are Trained.
https://magazine.sebastianraschka.com/p/new-llm-pre-training-and-post-training
Sebastianraschka
New LLM Pre-training and Post-training Paradigms
A Look at How Moderns LLMs Are Trained
Quick and Easy Rate Limiting for FastAPI
If you don’t want your API to crash due to too many requests, use rate limiting! This video covers how rate limiting works, what types of rate limiting you can do, how to implement it in FastAPI, and what you need to be mindful of.
https://www.youtube.com/watch?v=pZunzLJ1qcQ
If you don’t want your API to crash due to too many requests, use rate limiting! This video covers how rate limiting works, what types of rate limiting you can do, how to implement it in FastAPI, and what you need to be mindful of.
https://www.youtube.com/watch?v=pZunzLJ1qcQ
YouTube
Quick and Easy Rate Limiting for FastAPI
✅ Learn how to build robust and scalable software architecture: https://arjan.codes/checklist.
If you don’t want your API to crash due to too many requests, use rate limiting! In this video, I cover how rate limiting works, what types of rate limiting you…
If you don’t want your API to crash due to too many requests, use rate limiting! In this video, I cover how rate limiting works, what types of rate limiting you…
Layman's Guide to Python Built-in Functions
This is a plain language guide to every built-in function in Python, paired with a simple example that shows each function in action.
https://www.mattlayman.com/blog/2024/layman-guide-python-built-in-functions/
This is a plain language guide to every built-in function in Python, paired with a simple example that shows each function in action.
https://www.mattlayman.com/blog/2024/layman-guide-python-built-in-functions/
Matt Layman
Layman's Guide to Python Built-in Functions
This is a plain language guide to every built-in function in Python, paired with a simple example that shows each function in action.
JPMorgan's Python training for business analysts and traders
https://github.com/jpmorganchase/python-training
https://github.com/jpmorganchase/python-training
GitHub
GitHub - jpmorganchase/python-training: Python training for business analysts and traders
Python training for business analysts and traders. Contribute to jpmorganchase/python-training development by creating an account on GitHub.
Solving the labyrinth puzzle from the university quest using Python
https://wondrousnet.blogspot.com/2024/03/solution-to-puzzle-cat-walk.html
https://wondrousnet.blogspot.com/2024/03/solution-to-puzzle-cat-walk.html
Blogspot
Solution to the puzzle Cat Walk.
Cat Walk is one of the interesting puzzles of the Melbourne University Puzzle Hunt 2012 competition. This task was part of the second act ...
How Pytorch Powers Training Inference
Learn about new PyTorch advancements for LLMs and how PyTorch is enhancing every aspect of the LLM lifecycle.
https://www.youtube.com/watch?v=96VIEJfhUBg
Learn about new PyTorch advancements for LLMs and how PyTorch is enhancing every aspect of the LLM lifecycle.
https://www.youtube.com/watch?v=96VIEJfhUBg
YouTube
How Pytorch Powers Training Inference | Wanchao Liang, Kimish Patel, and Evan Smothers
How Pytorch Powers Training Inference | Wanchao Liang, Kimish Patel, and Evan Smothers
Speakers will discuss the importance of memory-efficient fine-tuning and a few common architectural and algorithmic techniques to enable fine-tuning on consumer-grade…
Speakers will discuss the importance of memory-efficient fine-tuning and a few common architectural and algorithmic techniques to enable fine-tuning on consumer-grade…
csv_trimming
Python package to remove common ugliness from a csv-like file
https://github.com/LucaCappelletti94/csv_trimming
Python package to remove common ugliness from a csv-like file
https://github.com/LucaCappelletti94/csv_trimming
GitHub
GitHub - LucaCappelletti94/csv_trimming: Package python to remove common ugliness from a csv-like file
Package python to remove common ugliness from a csv-like file - LucaCappelletti94/csv_trimming
The Design and Implementation of the CPython Virtual Machine
https://blog.codingconfessions.com/p/cpython-vm-internals
https://blog.codingconfessions.com/p/cpython-vm-internals
Codingconfessions
The Design & Implementation of the CPython Virtual Machine
A deep dive into CPython's bytecode instruction format and execution engine internals
LitServe
Lightning-fast serving engine for AI models. Flexible. Easy. Enterprise-scale.
https://github.com/Lightning-AI/LitServe
Lightning-fast serving engine for AI models. Flexible. Easy. Enterprise-scale.
https://github.com/Lightning-AI/LitServe
GitHub
GitHub - Lightning-AI/LitServe: The easiest way to deploy agents, MCP servers, models, RAG, pipelines and more. No MLOps. No YAML.
The easiest way to deploy agents, MCP servers, models, RAG, pipelines and more. No MLOps. No YAML. - Lightning-AI/LitServe
PyRoboCOP: Python-Based Robotic Control and Optimization Package
https://ieeexplore.ieee.org/abstract/document/10440590
https://ieeexplore.ieee.org/abstract/document/10440590
django-cotton
Bringing component based design to Django templates.
https://github.com/wrabit/django-cotton
Bringing component based design to Django templates.
https://github.com/wrabit/django-cotton
GitHub
GitHub - wrabit/django-cotton: Enabling Modern UI Composition in Django
Enabling Modern UI Composition in Django. Contribute to wrabit/django-cotton development by creating an account on GitHub.
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Why I Still Use Python Virtual Environments in Docker
The article argues for using Python virtual environments in Docker containers, citing benefits like predictability, standardization, and easier debugging. The author contends that virtual environments provide a consistent, well-understood structure for Python applications, making communication and deployment across teams more straightforward, while also simplifying Python's import behavior.
https://hynek.me/articles/docker-virtualenv/
The article argues for using Python virtual environments in Docker containers, citing benefits like predictability, standardization, and easier debugging. The author contends that virtual environments provide a consistent, well-understood structure for Python applications, making communication and deployment across teams more straightforward, while also simplifying Python's import behavior.
https://hynek.me/articles/docker-virtualenv/
Hynek Schlawack
Why I Still Use Python Virtual Environments in Docker
Whenever I publish something about my Python Docker workflows, I invariably get challenged about whether it makes sense to use virtual environments in Docker containers. As always, it’s a trade-off, and I err on the side of standards and predictability.
Maximizing Python Code Efficiency: Strategies to Overcome Common Performance Hurdles
This article talks about performance issues caused by nested loops and memory allocation issues. It provides strategies to overcome these issues while improving efficiency.
https://towardsdatascience.com/maximizing-python-code-efficiency-strategies-to-overcome-common-performance-hurdles-c6292610d785
This article talks about performance issues caused by nested loops and memory allocation issues. It provides strategies to overcome these issues while improving efficiency.
https://towardsdatascience.com/maximizing-python-code-efficiency-strategies-to-overcome-common-performance-hurdles-c6292610d785
Towards Data Science
Maximizing Python Code Efficiency: Strategies to Overcome Common Performance Hurdles | Towards Data Science
Navigating Nested Loops and Memory Challenges for Seamless Performance using Python
kotaemon
An open-source RAG-based tool for chatting with your documents.
https://github.com/Cinnamon/kotaemon
An open-source RAG-based tool for chatting with your documents.
https://github.com/Cinnamon/kotaemon
GitHub
GitHub - Cinnamon/kotaemon: An open-source RAG-based tool for chatting with your documents.
An open-source RAG-based tool for chatting with your documents. - Cinnamon/kotaemon
Taming the beast that is the Django ORM - An introduction
The Django ORM, how it compares to raw SQL and gotchas that you should be aware of when using it
https://www.davidhang.com/blog/2024-09-01-taming-the-django-orm/
The Django ORM, how it compares to raw SQL and gotchas that you should be aware of when using it
https://www.davidhang.com/blog/2024-09-01-taming-the-django-orm/
Davidhang
Taming the beast that is the Django ORM - An introduction
The Django ORM, how it compares to raw SQL and gotchas that you should be aware of when using it
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