Python Coding | Breaking Cybersecurity News | The Hacker News

In another finding that could expose developers to increased risk of a supply chain attack, it has emerged that nearly one-third of the packages in PyPI, the Python Package Index, trigger automatic code execution upon downloading them. "A worrying feature in pip/PyPI allows code to automatically run when developers are merely downloading a package," Checkmarx researcher Yehuda Gelb  said  in a technical report published this week. "Also, this feature is alarming due to the fact that a great deal of the malicious packages we are finding in the wild use this feature of code execution upon installation to achieve higher infection rates." One of the ways by which packages can be installed for Python is by executing the " pip install " command, which, in turn, invokes a file called "setup.py" that comes bundled along with the module. "setup.py," as the name implies, is a  setup script  that's used to specify metadata associated wit

Python has its pros and cons, but it's nonetheless used extensively. For example, Python is frequently used in data crunching tasks even when there are more appropriate languages to choose from. Why? Well, Python is relatively easy to learn. Someone with a science background can pick up Python much more quickly than, say, C. However, Python's inherent approachability also creates a couple of problems. Whenever Python is updated, it means a big refactoring workload, which often gets dealt with poorly – or not at all. That leads to poor performance and security vulnerabilities. But maybe there is a better way: a tool to keep your Python tasks running smoothly and securely day in, day out. Let's take a look. It's slow, but it does the job Python isn't the fastest language around, but despite its comparative disadvantages, you'll often see it used for intensive data crunching operations. Think machine learning, computer vision, or even pure math in high-perform

Identities now transcend human boundaries. Within each line of code and every API call lies a non-human identity. These entities act as programmatic access keys, enabling authentication and facilitating interactions among systems and services, which are essential for every API call, database query, or storage account access. As we depend on multi-factor authentication and passwords to safeguard human identities, a pressing question arises: How do we guarantee the security and integrity of these non-human counterparts? How do we authenticate, authorize, and regulate access for entities devoid of life but crucial for the functioning of critical systems? Let's break it down. The challenge Imagine a cloud-native application as a bustling metropolis of tiny neighborhoods known as microservices, all neatly packed into containers. These microservices function akin to diligent worker bees, each diligently performing its designated task, be it processing data, verifying credentials, or