Tag generators

Python Requirements Generator Script

Python Requirements Generator Script and Generating a Requirements.txt File Using genreq.py

When working with Python projects, one of the most important tasks is ensuring that the right dependencies are listed in a requirements.txt file. This file allows you to specify all the third-party modules your project depends on, making it easy to set up the same environment on a different machine. Generating an accurate requirements.txt is often a tedious and error-prone process, especially when using standard methods like pip freeze. These methods can sometimes generate incorrect versions or include unnecessary dependencies, leading to compatibility issues or bloat in your project.

One powerful solution to this problem is the genreq.py script. This Python script simplifies and streamlines the process of generating a requirements.txt by reading the imports in a specified Python file and matching them with the installed versions of the libraries. It works both inside and outside of virtual environments, ensuring that the correct dependencies are captured accurately.

Simplicity of Generating requirements.txt

The genreq.py script eliminates the need for manual entry or reliance on pip freeze, which often lists all installed packages, including those irrelevant to the specific project. Unlike pip freeze, which outputs a comprehensive list of all installed packages in the environment, genreq.py looks specifically for third-party packages imported in the Python script provided by the user. This targeted approach ensures that only the necessary dependencies are included in the generated requirements.txt file.

What makes this tool even more efficient is that it works equally well inside or outside a virtual environment. Inside a virtual environment, it ensures that only the packages relevant to the project are considered, while outside of it, it checks the global Python environment. This flexibility allows developers to generate the file in any setup without worrying about misidentifying irrelevant packages.

Ensuring Current Versions of Dependencies

One of the key benefits of using genreq.py is that it guarantees the requirements.txt file reflects the current versions of the libraries installed in the environment. By using pkg_resources, the script checks which installed versions of packages match the imports in the provided Python script. This ensures that the generated requirements.txt file is as current as the installed versions of Python and the third-party modules.

Unlike pip freeze, which can sometimes pull older versions or omit recent updates, genreq.py only includes the precise versions of the libraries currently in use. This ensures compatibility across environments and helps avoid issues where an older version of a package might be installed in a new setup, causing bugs or errors.

Python Requirements Generator Script Accuracy and Ease of Use

The ease with which genreq.py generates an accurate requirements.txt makes it an invaluable tool for developers. Traditional methods like pip freeze can often result in inaccurate version numbers, including unnecessary or outdated dependencies. Moreover, manually managing requirements.txt entries can lead to errors, especially when switching between multiple environments.

In contrast, genreq.py simplifies this process. It automatically analyzes the imports, checks installed packages, and writes the necessary ones to the requirements.txt file, with the correct versions based on the current environment. This level of precision makes it easier to share and deploy Python projects without worrying about dependency mismatches.

In conclusion, genreq.py is a simple yet powerful tool that ensures accurate, up-to-date, and environment-specific dependencies are listed in the requirements.txt file. By automatically extracting and validating imports, it eliminates the need for manual dependency tracking and avoids the common pitfalls of other methods. This script not only saves time but also reduces the likelihood of compatibility issues, making it an essential tool for any Python Developer.

Python Requirements Generator Script – The Code:

Stand Alone Flask Application Template By K0NxT3D

The Stand Alone Flask Application Template is a minimal yet powerful starting point for creating Flask-based web UI applications. Developed by K0NxT3D, this template is designed to run a Flask app that can be deployed easily on a local machine. It features an embedded HTML template with Bootstrap CSS for responsive design, the Oswald font for style, and a simple yet effective shutdown mechanism. Here’s a detailed look at how it works and how you can use it.

Stand Alone Flask Application – Key Features

1. Basic Flask Setup
   The template leverages Flask, a lightweight Python web framework, to build a minimal web application. The app is configured to run on port 26001, with versioning details and a friendly app name displayed in the user interface.
2. Embedded HTML Template
   The HTML template is embedded directly within the Flask application code using render_template_string(). This ensures that the application is fully self-contained and does not require external HTML files.
3. Bootstrap Integration
   The application uses Bootstrap 5 for responsive UI components, ensuring that the application adapts to different screen sizes. Key elements like buttons, form controls, and navigation are styled with Bootstrap’s predefined classes.
4. Oswald Font
   The Oswald font is embedded via Google Fonts, giving the application a modern, clean look. This font is applied globally to the body and header elements.
5. Shutdown Logic
   One of the standout features is the built-in shutdown mechanism, allowing the Flask server to be stopped safely. The /exit route is specifically designed to gracefully shut down the server, with a redirect and a JavaScript timeout to ensure the application closes cleanly.
6. Automatic Browser Launch
   When the application is started, the script automatically opens the default web browser to the local Flask URL. This is done by the open_browser() function, which runs in a separate thread to avoid blocking the main Flask server.

How The Stand Alone Flask Application Works

1. Application Setup

The core setup includes the following elements:

This sets the title, version, and application name, which are used throughout the app’s user interface. The PORT is set to 26001 and can be adjusted as necessary.

2. Main Route (/)

The main route (/) renders the HTML page, displaying the app title, version, and a button to exit the application:

This route serves the home page with an HTML template that includes Bootstrap styling and the Oswald font.

3. Shutdown Route (/exit)

The /exit route allows the server to shut down gracefully. It checks that the request is coming from localhost (to avoid unauthorized shutdowns) and uses JavaScript to redirect to an exit page, which informs the user that the application has been terminated.

This section includes a timer that schedules the server’s termination after 1 second, allowing the browser to process the redirect.

4. HTML Template

The embedded HTML template includes:

• Responsive Design: Using Bootstrap, the layout adapts to different devices.
• App Title and Version: Dynamically displayed in the header.
• Exit Button: Allows users to gracefully shut down the application.

This structure creates a clean, visually appealing user interface, with all styling contained within the app itself.

5. Automatic Browser Launch

The following function ensures that the web browser opens automatically when the Flask app is launched:

This function is executed in a separate thread to avoid blocking the Flask server from starting.

How to Use the Template

1. Install Dependencies:
   Ensure that your requirements.txt includes the following:
   Flask==2.0.3


   Install the dependencies with pip install -r requirements.txt.

2. Run the Application:
   Start the Flask application by running the script:
   python app.py


   This will launch the server, open the browser to the local URL (http://127.0.0.1:26001), and serve the application.

3. Exit the Application:
   You can shut down the application by clicking the “Exit Application” button, which triggers the shutdown route (/exit).

Why Use This Template?

This template is ideal for developers looking for a simple and straightforward Flask application to use as a base for a web UI. It’s particularly useful for local or single-user applications where quick setup and ease of use are essential. The built-in shutdown functionality and automatic browser launch make it even more convenient for developers and testers.

Additionally, the use of Bootstrap ensures that the UI will look good across all devices without requiring complex CSS work, making it a great starting point for any project that needs a web interface.

The Stand Alone Flask Application Template by K0NxT3D is an efficient and versatile starting point for building simple Flask applications. Its integrated features, including automatic browser launching, shutdown capabilities, and embedded Bootstrap UI, make it a powerful tool for developers looking to create standalone web applications with minimal setup.

The Rise of AI-Generated Spam on Facebook: Current Issues and Trends

Over the past few days, Facebook has faced a notable increase in spam activity driven by AI-generated content. These posts, often featuring surreal or hyper-realistic images, are part of a coordinated effort by spammers to exploit the platform’s algorithms for financial gain. Here’s a breakdown of the situation and its implications:

What’s Happening?

1. AI-Generated Images: Spam pages are flooding Facebook with AI-crafted images, ranging from bizarre art to visually stunning but nonsensical content. A notable example includes viral images of statues made from unusual materials, such as “Jesus made of shrimp”​.
2. Amplification by Facebook Algorithms: These posts gain traction due to Facebook’s “Suggested for You” feature, which promotes posts based on engagement patterns rather than user preferences. When users interact with these posts—even unintentionally—the algorithm further boosts their visibility​.
3. Monetary Motives: Many spam pages link to external ad-heavy or dropshipping sites in the comments, monetizing the engagement from these viral posts. Some pages even invest in Facebook ads to amplify their reach, complicating the platform’s efforts to detect and mitigate such content​.
4. Global Scale: The spam campaigns are widespread, with some pages managing hundreds of millions of interactions collectively. This level of engagement highlights the challenge of moderating such content at scale​.

Facebook’s Response

Meta (Facebook’s parent company) has acknowledged the issue and pledged to improve transparency by labeling AI-generated content. This move comes after similar concerns about misinformation and malicious AI use on the platform. However, critics argue that Facebook’s reliance on automated moderation tools may not be enough to counter the evolving tactics of spammers​.

Broader Implications

• Erosion of Trust: As AI-generated spam becomes more prevalent, users may find it increasingly difficult to discern authentic content from manipulated posts.
• Algorithmic Loopholes: The incident underscores the potential vulnerabilities in content recommendation systems, which can inadvertently amplify harmful or deceptive material.
• Economic and Security Risks: The monetization of these schemes often involves redirecting users to risky sites, posing both financial and cybersecurity threats​.

The current surge in spam ads on Facebook is primarily linked to bot farms and automation tools that exploit the platform for fake engagement. These bots are not only designed to spread irrelevant ads but also to generate fake clicks, skew ad analytics, and disrupt genuine user experiences. Recent incidents indicate that these ad bots are part of larger operations targeting platforms like Facebook, Instagram, and others.

Two categories of bots dominate Facebook spamming:

1. Automated Bots: These are simpler systems designed to mass-produce accounts and post repetitive ads. Facebook’s AI can often detect and block these quickly, but the sheer volume still creates noise.
2. Manual or Sophisticated Bots: These accounts mimic real user behavior, making them harder to detect. They are often used for more strategic ad campaigns, spreading disinformation or promoting scams.

Historically, operations like Boostgram and Instant-Fans.com have been known to utilize such bot networks, targeting users with fake engagement across multiple platforms, including Facebook. Meta (Facebook’s parent company) regularly takes legal action against such entities, but many adapt and persist​.

Additionally, bot farms often consist of thousands of fake accounts designed to interact with ads, affecting advertiser metrics and budgets. Facebook reports significant efforts in removing fake accounts, claiming millions blocked quarterly, but challenges remain with sophisticated bots bypassing detection​.

If you’re seeing increased spam, it might be part of a broader effort by these bot operators to exploit Facebook’s ad systems or test new evasion techniques. Users and advertisers are encouraged to report suspicious activity and remain cautious about ad engagement.

Bot farms are large-scale operations leveraging networks of automated programs to execute repetitive digital tasks for malicious purposes. These include manipulating financial markets, inflating ad metrics, and engaging in cyber fraud. Bot farms often consist of numerous servers, diverse IP address pools, and highly advanced scripts to evade detection, allowing them to operate at scale and with precision.

In financial markets, bots can exacerbate volatility by executing coordinated trades, such as artificial inflation schemes (pump-and-dump) or high-frequency trades to disrupt normal market behavior. These actions mislead investors, distort pricing mechanisms, and can destabilize entire markets, especially during periods of economic uncertainty. Such disruptions are not limited to legitimate trading but also extend to platforms reliant on algorithmic responses, creating widespread ripple effects.

Economically, these bot-driven disruptions cause substantial financial losses, costing industries billions annually. For example, fraudulent advertising metrics waste business resources while masking true engagement. High-profile operations like Methbot exploited hundreds of thousands of fake IP addresses, generating fraudulent ad revenue on a massive scale and undermining trust in digital advertising ecosystems.

Efforts to mitigate the impact of bot farms include deploying machine learning models to identify anomalous behavior, monitoring for IP spoofing, and implementing stronger authentication methods. However, as bot technology continues to evolve, combating their influence requires ongoing innovation, stricter regulations, and global collaboration to protect financial and digital ecosystems from systemic risks.

Current Events and Developments

1. Meta’s AI Transparency Push: Meta has committed to labeling AI-generated images across its platforms, aiming to curtail the spread of manipulated content and improve user awareness​.
2. Increased Monitoring Efforts: Researchers and watchdogs are ramping up analyses of such campaigns. For instance, studies by Stanford and Georgetown have documented hundreds of spam pages exploiting Facebook’s engagement-driven algorithms​.
3. User Awareness Campaigns: Public advisories are being issued, encouraging users to avoid interacting with suspicious posts and report them to Facebook for moderation.

What You Can Do

• Avoid Interactions: Refrain from liking, commenting, or sharing suspicious content.
• Report Spam: Use Facebook’s reporting tools to flag AI-generated spam posts.
• Stay Informed: Regularly update your knowledge of online scams and be cautious of external links, especially those posted in comments.

By understanding the tactics and implications of these campaigns, users can help reduce their impact while pushing platforms like Facebook to strengthen their moderation policies.

SSH-Snake, a self-modifying worm that leverages SSH credentials.

Original Article : The Hacker News

A recently open-sourced network mapping tool called SSH-Snake has been repurposed by threat actors to conduct malicious activities.

“SSH-Snake is a self-modifying worm that leverages SSH credentials discovered on a compromised system to start spreading itself throughout the network,” Sysdig researcher Miguel Hernández said.

“The worm automatically searches through known credential locations and shell history files to determine its next move.”

SSH-Snake was first released on GitHub in early January 2024, and is described by its developer as a “powerful tool” to carry out automatic network traversal using SSH private keys discovered on systems.

In doing so, it creates a comprehensive map of a network and its dependencies, helping determine the extent to which a network can be compromised using SSH and SSH private keys starting from a particular host. It also supports resolution of domains which have multiple IPv4 addresses.

“It’s completely self-replicating and self-propagating – and completely fileless,” according to the project’s description. “In many ways, SSH-Snake is actually a worm: It replicates itself and spreads itself from one system to another as far as it can.”

BotNet CNC Control Hacker Infiltrates & Exploits Vulnerabilities Vie SSH TCP Both Hardware Software Exploited

Sysdig said the shell script not only facilitates lateral movement, but also provides additional stealth and flexibility than other typical SSH worms.

The cloud security company said it observed threat actors deploying SSH-Snake in real-world attacks to harvest credentials, the IP addresses of the targets, and the bash command history following the discovery of a command-and-control (C2) server hosting the data.

How Does It Work?

These attacks involve active exploitation of known security vulnerabilities in Apache ActiveMQ and Atlassian Confluence instances in order to gain initial access and deploy SSH-Snake.
“The usage of SSH keys is a recommended practice that SSH-Snake tries to take advantage of in order to spread,” Hernández said. “It is smarter and more reliable which will allow threat actors to reach farther into a network once they gain a foothold.”

When reached for comment, Joshua Rogers, the developer of SSH-Snake, told The Hacker News that the tool offers legitimate system owners a way to identify weaknesses in their infrastructure before attackers do, urging companies to use SSH-Snake to “discover the attack paths that exist – and fix them.”

“It seems to be commonly believed that cyber terrorism ‘just happens’ all of a sudden to systems, which solely requires a reactive approach to security,” Rogers said. “Instead, in my experience, systems should be designed and maintained with comprehensive security measures.”

Netcat file transfer chat utility. Easily Send & Receive Files Local & Remote.

“If a cyber terrorist is able to run SSH-Snake on your infrastructure and access thousands of servers, focus should be put on the people that are in charge of the infrastructure, with a goal of revitalizing the infrastructure such that the compromise of a single host can’t be replicated across thousands of others.”

Rogers also called attention to the “negligent operations” by companies that design and implement insecure infrastructure, which can be easily taken over by a simple shell script.

“If systems were designed and maintained in a sane manner and system owners/companies actually cared about security, the fallout from such a script being executed would be minimized – as well as if the actions taken by SSH-Snake were manually performed by an attacker,” Rogers added.

“Instead of reading privacy policies and performing data entry, security teams of companies worried about this type of script taking over their entire infrastructure should be performing total re-architecture of their systems by trained security specialists – not those that created the architecture in the first place.”

The disclosure comes as Aqua uncovered a new botnet campaign named Lucifer that exploits misconfigurations and existing flaws in Apache Hadoop and Apache Druid to corral them into a network for mining cryptocurrency and staging distributed denial-of-service (DDoS) attacks.

The hybrid cryptojacking malware was first documented by Palo Alto Networks Unit 42 in June 2020, calling attention to its ability to exploit known security flaws to compromise Windows endpoints.
As many as 3,000 distinct attacks aimed at the Apache big data stack have been detected over the past month, the cloud security firm said. This also comprises those that single out susceptible Apache Flink instances to deploy miners and rootkits.

“The attacker implements the attack by exploiting existing misconfigurations and vulnerabilities in those services,” security researcher Nitzan Yaakov said.

Apache Vulnerability Update Available!

“Apache open-source solutions are widely used by many users and contributors. Attackers may view this extensive use as an opportunity to have inexhaustible resources for implementing their attacks on them.”

Hacker News:
Russian Hackers Have Infiltrated U.S. Household and Small Business Routers, FBI Warns
Original Article: MSN News

The FBI has recently thwarted a large-scale cyberattack orchestrated by Russian operatives, targeting hundreds of routers in home offices and small businesses, including those in the United States.

These compromised routers were used to form “botnets”, which were then employed in cyber operations worldwide.

The United States Department of Justice has attributed this cyberattack to the Russian GRU Military Unit 26165. Countermeasures undertaken by authorities ensured that the GRU operators were expelled from the routers and denied further access, ABC News reported.

The GRU deployed a specialized malware called “Moobot,” associated with a known criminal group, to seize control of susceptible home and small office routers, converting them into “botnets” — a network of remotely controlled systems.

The Justice Department, in an official statement, explained, “Non-GRU cybercriminals installed the Moobot malware on Ubiquiti Edge OS routers that still used publicly known default administrator passwords. GRU hackers then used the Moobot malware to install their own bespoke scripts and files that repurposed the botnet, turning it into a global cyber espionage platform.”

Utilizing this botnet, Russian hackers engaged in various illicit activities, including extensive “spearphishing” campaigns and credential harvesting campaigns against targets of intelligence interest to the Russian government, such as governmental, military, security and corporate entities in the United States and abroad.

Botnets pose a significant challenge for intelligence agencies, hindering their ability to detect foreign intrusions into their computer networks, Reuters notes.

In January 2024, the FBI executed a court-approved operation dubbed “Operation Dying Ember” to disrupt the hacking campaign. According to the Department of Justice, the FBI employed malware to copy and erase the malicious data from the routers, restoring full access to the owners while preventing further unauthorized access by GRU hackers.

FEDOR was designed as an android able to replace humans in high-risk areas, such as rescue operations,” Andrey Grigoriev, director of Russia’s Advanced Research Fund, said.

Knowledge For Life Volume I

The Omniverse Library:
A diverse reading list from several topics.
The Omniverse Library boasts an extensive collection of resources covering a wide range of subjects, including science, history, philosophy, and the occult. Users can access a plethora of articles, books, research papers, manuscripts, and multimedia content curated from reputable sources worldwide.

Continuous Enrichment: The Omniverse Library is a dynamic platform continually enriched with new additions and updates. With regular contributions from experts, scholars, and content creators, the library remains a vital source of knowledge, fostering intellectual growth and exploration in an ever-evolving world.

Join the Quest for Knowledge: Embark on a journey of discovery and enlightenment with The Omniverse Library—an unparalleled digital repository where the boundaries of human understanding are transcended, and the pursuit of truth knows no bounds.

American & World History – Science – Philosophy – The Occult – Survival & Of Course.. some Miscreant Materials.
Carl Sagan – Isaac Newton – Nikola Tesla – Sun Tzu – Aleister Crowley – Karl Marx – Anarchist Cookbook – Bushcraft

Main Menu

Bionic Backdrop

Bionic Backdrop Digital Video Screen Media – Events, Rock Shows, DJ, Performances of Any Kind.
New Features Include A Hidden Drop Down Menu
(Mouse Over or Tap In The Top Black Header)
With Casting Support from Desktop or Mobile.
Tested on Chromium (Solid) and Firefox(Not Recommended)
Lyrics Library is active and still Beta (Opens in new window).
Binary Output is Currently Disabled (Beta Only)

Bionic Home Page

This is just a fun little toy that happened while working on MySQL Automation.
The files used are first_names.txt, last_names.txt and domains.txt.
Reading random lines from the files in order creates the “Fake Email Address” and using [array_rand($variable)]; each email address is somewhat unique as I’m only using 80,000 names (give or take a few hundred).

All Files: fake-email-generator.zip

#!/bin/bash
$first_names = 'first_names.txt';
$last_names = 'last_names.txt';
$dom = 'domains.txt';

    $firstname = file($first_names);
    $fdata = $firstname[array_rand($firstname)];
    $first = $fdata;

        $lastname = file($last_names);
        $ldata = $lastname[array_rand($lastname)];
        $last = $ldata;

    $comd = file($dom);
    $edata = $comd[array_rand($comd)];
    $com = $edata;

        $first = preg_replace('/\s+/', '', $first);
        $first = strtolower($first);
        $last = preg_replace('/\s+/', '', $last);
        $last = strtolower($last);
        $com = preg_replace('/\s+/', '', $com);

    echo $first."@".$last.$com;]