Tag Crawler

Lÿnх: The Ultimate Backlink Verification Utility for Web Developers

In today’s digital landscape, web development and search engine optimization (SEO) are inseparable. A major part of SEO involves verifying backlinks to ensure your site’s credibility and search engine ranking. Enter Lÿnх—a powerful and highly efficient backlink verification tool designed to streamline this critical process. Developed by K0NxT3D, a leader and pioneer in today’s latest web technologies, Lÿnх is software you can rely on, offering both a CLI (Command-Line Interface) version and a Web UI version for varied use cases.

What Does Lÿnх Do?

Lÿnх is a versatile tool aimed at web developers, SEOs, and site administrators who need to verify backlinks. A backlink is any hyperlink that directs a user from one website to another, and its verification ensures that links are valid, live, and properly pointing to the intended destination. Lÿnх’s core function is to efficiently scan or “Scrape” a website’s backlinks and validate their existence and correctness, ensuring that they are not broken or pointing to the wrong page.

Lÿnх Backlink Verification Utility

Lÿnх Backlink Verification Utility

Why Should You Use Lÿnх?

For any website owner or developer, managing backlinks is crucial for maintaining strong SEO. Broken links can damage a website’s credibility, affect search engine rankings, and worsen user experience. Lÿnх eliminates these concerns by providing a fast and effective solution for backlink verification. Whether you’re optimizing an existing site or conducting routine checks, Lÿnх ensures your backlinks are always in top shape.

The Technology Behind Lÿnх

Lÿnх employs cutting-edge web technologies for data processing and parsing. Built on a highly efficient parsing engine, it processes large amounts of data at lightning speed, scanning each link to ensure it’s valid. The CLI version (Lÿnх 1.0) operates through straightforward commands, perfect for automation in server-side environments, while Lÿnх 1.2 Web UI version offers a clean, user-friendly interface for more interactive and accessible verification.

The tool integrates seamlessly into your web development workflow, parsing HTML documents, extracting backlinks, and checking their status. Its low resource usage and high processing speed make it ideal for both small websites and large-scale applications with numerous backlinks to verify.

Lÿnх Backlink Verification Utility – Efficiency and Speed

Lÿnх is designed with performance in mind. Its lightweight architecture allows it to quickly scan even the most extensive lists of backlinks without overloading servers or consuming unnecessary resources. The CLI version is especially fast, offering a no-nonsense approach to backlink verification that can run on virtually any server or local machine. Meanwhile, the Web UI version maintains speed without compromising on ease of use.

Why Lÿnх is Essential for Web Development

In the competitive world of web development and SEO, ensuring the integrity of backlinks is crucial for success. Lÿnх provides a reliable, high-speed solution that not only verifies links but helps you maintain a clean and efficient website. Whether you’re a freelance developer, part of an agency, or managing your own site, Lÿnх’s intuitive tools offer unmatched utility. With K0NxT3D’s expertise behind it, Lÿnх is the trusted choice for anyone serious about web development and SEO.

Lÿnх Backlink Verification Utility

Lÿnх is more than just a backlink verification tool; it’s an essential component for anyone looking to maintain a high-performing website. With its high efficiency, speed, and powerful functionality, Lÿnх continues to lead the way in backlink management, backed by the expertise of K0NxT3D.

WonderMule Stealth Scraper:
A Powerful and Efficient Web Scraping Tool.

WonderMule Stealth Scraper is a cutting-edge, highly efficient, and stealthy web scraping application designed to extract data from websites without triggering security measures or firewall blocks. It serves as an invaluable tool for security professionals, researchers, and data analysts alike. Whether you’re working in the realms of ethical hacking, threat intelligence, or simply need to scrape and mine data from the web without leaving a trace, WonderMule provides a robust solution.

WonderMule Stealth Scraper

Key Features

1. Super Fast and Efficient
   WonderMule is built with speed and efficiency in mind. Utilizing Python’s httpx library, an asynchronous HTTP client, the tool can handle multiple requests simultaneously. This allows for quick extraction of large datasets from websites. httpx enables non-blocking I/O operations, meaning that it doesn’t have to wait for responses before continuing to the next request, resulting in a much faster scraping process compared to synchronous scraping tools.
2. Stealthy Firewall Evasion
   One of the standout features of WonderMule is its ability to bypass firewalls and evade detection. Websites and web servers often employ anti-scraping measures such as IP blocking and rate limiting to protect their data. WonderMule has built-in functionality that alters the User-Agent and mimics legitimate traffic, making it harder for servers to distinguish between human users and the scraper.
   This makes it particularly useful in environments where security measures are stringent.
   WonderMule is even often missed entirely, as discovered testing against several well-known firewalls.
   This feature makes it an invaluable and in some instances, even unethical or illegal to use.
   No Public Download Will Be Made Available.
3. Torsocks Compatibility
   WonderMule comes pre-configured for seamless integration with torsocks, allowing users to route their traffic through the Tor network for anonymity and additional privacy. This feature is useful for those who need to maintain a low profile while scraping websites. By leveraging the Tor network, users can obfuscate their IP address and further reduce the risk of being detected by security systems.
4. CSV Output for Easy Data Import
   The application generates output in CSV format, which is widely used for data importation and manipulation. Data scraped from websites is neatly organized into columns such as titles, links, and timestamps. This makes it easy to import the data into other technologies and platforms for further processing, such as databases, Excel sheets, or analytical tools. The structured output ensures that the scraped data is immediately usable for various applications.
5. Lightweight and Portable
   Despite its rich feature set, WonderMule remains lightweight, with the full set of libraries and dependencies bundled into a 12.3MB standalone executable. This small footprint makes it highly portable and easy to run on different systems without requiring complex installation processes. Users can run the application on any compatible system, making it an ideal choice for quick deployments in various environments.

WonderMule Stealth Scraper:
Functions and How It Works

At its core, WonderMule utilizes Python’s httpx library to send asynchronous HTTP requests to target websites. The process begins when a URL is provided to the scraper. The scraper then makes an HTTP GET request to the server using a custom user-agent header (configured to avoid detection). The response is parsed using BeautifulSoup to extract relevant data, such as article titles, links, and timestamps. Once the data is extracted, it is written to a CSV file for later use.

The integration of asyncio enables the scraper to handle multiple requests concurrently, resulting in faster performance and better scalability. The data is collected in real-time, and the CSV output is structured in a way that it can be easily integrated into databases, spreadsheets, or other analytical tools.

A Versatile Tool for Security Experts and Data Miners

WonderMule’s versatility makes it valuable for a broad spectrum of users. Black hat hackers may use it to gather intelligence from various websites while staying undetected. White hat professionals and penetration testers can leverage its stealth features to evaluate the security posture of websites and detect vulnerabilities such as weak firewall protections or improper rate limiting. Moreover, data analysts and researchers can use WonderMule to perform data mining on websites for trend analysis, market research, or competitive intelligence.

Whether you’re conducting a security audit, gathering publicly available data for research, or looking to extract large sets of information without triggering detection systems, WonderMule Stealth Scraper is the perfect tool for the job. With its speed, stealth, and portability, it offers a unique blend of functionality and ease of use that is difficult to match.

WonderMule Stealth Scraper

WonderMule Stealth Scraper provides a powerful solution for anyone needing to extract data from the web quickly and discreetly. Whether you are working on a security project, performing ethical hacking tasks, or conducting large-scale data mining, WonderMule’s ability to bypass firewalls, its compatibility with Tor for anonymous scraping, and its lightweight nature make it a top choice for both security professionals and data analysts.

Web Scraping Basics:
Understanding the World of Scrapers

Web scraping basics refer to the fundamental techniques and tools used to extract data from websites. This powerful process enables users to gather large amounts of data automatically from the internet, transforming unstructured content into structured formats for analysis, research, or use in various applications.

At its core, web scraping involves sending an HTTP request to a website, downloading the page, and then parsing the HTML to extract useful information. The extracted data can range from text and images to links and tables. Popular programming languages like Python, along with libraries like BeautifulSoup, Scrapy, and Selenium, are often used to build scrapers that automate this process.

The importance of web scraping basics lies in its ability to collect data from numerous sources efficiently. Businesses, data scientists, marketers, and researchers rely on scraping to gather competitive intelligence, track market trends, scrape product details, and monitor changes across websites.

However, web scraping is not without its challenges. Websites often use anti-scraping technologies like CAPTCHAs, rate-limiting, or IP blocking to prevent unauthorized scraping. To overcome these hurdles, scrapers employ techniques like rotating IPs, using proxies, and simulating human-like browsing behavior to avoid detection.

Understanding the ethical and legal implications of web scraping is equally important. Many websites have terms of service that prohibit scraping, and violating these terms can lead to legal consequences. It’s crucial to always respect website policies and use scraping responsibly.

In conclusion, web scraping basics provide the foundation for harnessing the power of automated data extraction. By mastering the techniques and tools involved, you can unlock valuable insights from vast amounts of online data, all while navigating the challenges and ethical considerations in the world of scrapers.

Web Scraping Basics:
Best Resources for Learning Web Scraping

Web scraping is a popular topic, and there are many excellent resources available for learning. Here are some of the best places where you can find comprehensive and high-quality resources on web scraping:

1. Online Courses

• Udemy:
  • “Web Scraping with Python” by Andrei Neagoie: Covers Python libraries like BeautifulSoup, Selenium, and requests.
  • “Python Web Scraping” by Jose Portilla: A complete beginner’s guide to web scraping.
• Coursera:
  • “Data Science and Python for Web Scraping”: This course provides a great mix of Python and web scraping with practical applications.
• edX:
  • Many universities, like Harvard and MIT, offer courses that include web scraping topics, especially related to data science.

2. Books

• “Web Scraping with Python” by Ryan Mitchell: This is one of the best books for beginners and intermediates, providing in-depth tutorials using popular libraries like BeautifulSoup, Scrapy, and Selenium.
• “Python for Data Analysis” by Wes McKinney: Although it’s primarily about data analysis, it includes sections on web scraping using Python.
• “Automate the Boring Stuff with Python” by Al Sweigart: A beginner-friendly book that includes a great section on web scraping.

3. Websites & Tutorials

• Real Python:
  • Offers high-quality tutorials on web scraping with Python, including articles on using BeautifulSoup, Scrapy, and Selenium.
• Scrapy Documentation: Scrapy is one of the most powerful frameworks for web scraping, and its documentation provides a step-by-step guide to getting started.
• BeautifulSoup Documentation: BeautifulSoup is one of the most widely used libraries, and its documentation has plenty of examples to follow.
• Python Requests Library: The Requests library is essential for making HTTP requests, and its documentation has clear, concise examples.

4. YouTube Channels

• Tech with Tim: Offers great beginner tutorials on Python and web scraping.
• Code Bullet: Focuses on programming projects, including some that involve web scraping.
• Sentdex: Sentdex has a great web scraping series that covers tools like BeautifulSoup and Selenium.

5. Community Forums

• Stack Overflow: There’s a large community of web scraping experts here. You can find answers to almost any problem related to web scraping.
• Reddit – r/webscraping: A community dedicated to web scraping with discussions, tips, and resources.
• GitHub: There are many open-source web scraping projects on GitHub that you can explore for reference or use.

6. Tools and Libraries

• BeautifulSoup (Python): One of the most popular libraries for HTML parsing. It’s easy to use and great for beginners.
• Scrapy (Python): A more advanced, powerful framework for large-scale web scraping. Scrapy is excellent for handling complex scraping tasks.
• Selenium (Python/JavaScript): Primarily used for automating browsers. Selenium is great for scraping dynamic websites (like those that use JavaScript heavily).
• Puppeteer (JavaScript): If you’re working in JavaScript, Puppeteer is a great choice for scraping dynamic content.

7. Web Scraping Blogs

• Scrapinghub Blog: Articles on best practices, tutorials, and new scraping techniques using Scrapy and other tools.
• Dataquest Blog: Offers tutorials and guides that include web scraping for data science projects.
• Towards Data Science: This Medium publication regularly features web scraping tutorials with Python and other languages.

8. Legal and Ethical Considerations

• It’s important to understand the ethical and legal aspects of web scraping. Resources on this topic include:
  • Scrapinghub Legal Section: Includes guides and articles on the legal implications of web scraping.
  • Legal Risks of Web Scraping (Blog): Discusses the dos and don’ts of web scraping to ensure you are compliant with laws like GDPR and site-specific Terms of Service.

9. Practice Sites

• Web Scraper.io: A web scraping tool that also offers tutorials and practice datasets.
• BeautifulSoup Practice: Hands-on exercises specifically for web scraping.
• Scrapingbee: Provides an API for scraping websites and a blog with tutorials.

With these resources, you should be able to build a solid foundation in web scraping and advance to more complex tasks as you become more experienced.

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.

I collect a lot of data and data mining is just one of those things that I enjoy.
I build Web Crawlers and Web Scrapers often, but I really love tracking other
bots, some of which I’ve “known” for decades now.

With the ever expanding Facebook Empire, I’ve been catching a lot of the
hits from FacebookExternalHit,
[ facebookexternalhit/1.1 (+http://www.facebook.com/externalhit_uatext.php) ]
and while Facebook it’self is being overrun by nefarious bots and hacked accounts,
their problem is my solution.

The majority of the hits from FacebookExternalHit have preceded an attack, which tells me several things.
1: Facebook For Developers has given nefarious actors an edge on the Facebook user and I won’t go into detail on that, but I can make better informed security decisions based on what can be done from that side of the platform.

2: I can test my security software on both Facebook and my websites by simply posting a link to Facebook and this is really handy in my line of work. I get to see which Data Center the bot is coming from (GeoLocation), how many bots that particular Data Center has (Interesting Data There) and how fast the reaction time is, which helps determine the software being used and in which manner it’s being used.

3: Most Importantly, it gives me reasons to build new software.

So, I built this database for such purpose as to collect more data on the situation and there’s some interesting patterns developing. While it’s not exactly something I feel the urge to release, it’s worth sharing.

FBDC uses Php and MySQL, a pretty simple database and small file sizes (I like small files).
The User Input Form Works.. Ikr, a form that works??
It has a few things left to work out on the user input; I’m a big fan of getting my hands dirty,
so Updating the Data Center / BotInfo is being done via phpmyadmin until I build a better form.
Here’s a few screenshots:

FBDC – Facebook Data Centers and FacebookExternalHit Bot Collected Data – Main Menu

FBDC – Facebook Data Centers and FacebookExternalHit Bot Collected Data – Data Center List

FBDC – Facebook Data Centers and FacebookExternalHit Bot Collected Data – BotInfo List

FBDC – Facebook Data Centers and FacebookExternalHit Bot Collected Data – User Input Form

FBDC – Facebook Data Centers and FacebookExternalHit Bot Collected Data – Because There HAS to be a Hacker Theme too.

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.

Random HTTP Request Generator – “generator.php”

This generates the Header Request Information to be sent to a Destination URL.
For Testing Purposes Only – Some Files Have Been Excluded.
The Destination URL tracks incoming HTTP Requests and filters them for “bad data” or
“Spoofed Requests” such as the requests generated here.

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;]

BashKat is pretty straight forward and really easy to use.
I made sure to add some “cute” to it with the emojis.
This bot will scrape from user input or a file using the wget function (example: urls.txt) and it’s Super Fun when using Proxychains.

#!/usr/bin/env bash
# BashKat Version 1.0.2
# K0NxT3D

# Variables
BotOptions="Url File Quit"

# Welcome Banner
clear
printf "✨ BashKat 1.0 ✨\nScrape Single URL/IP or Multiple From File.\n\n" && sleep 1

# Bot Options Menu
select option in $BotOptions; do

# Single URL Scrape
   if [ "$option" = "Url" ];
    then
      printf "URL To Scrape: "
       read scrapeurl
     mkdir -p data/
    wget -P data/ \
     -4 \
     -w 0 \
     -t 3 \
     -rkpN -e robots=off \
     --header="Accept: text/html" \
     --user-agent="BashKat/1.0 (BashKat 1.0 Web Scraper Utility +http://www.bashkat.bot/)" \
     --referer="http://www.bashkat.bot" \
     --random-wait \
     --recursive \
     --no-clobber \
     --page-requisites \
     --convert-links \
     --restrict-file-names=windows \
     --domains $scrapeurl \
     --no-parent \
         $scrapeurl

      printf "🏁Scrape Complete.\nHit Enter To Continue.👍"
       read anykey
./$(basename $0) && exit

  elif [ "$option" = "File" ];
   then
      printf "Path To File: "
       read filepath
     while IFS= read -r scrapeurl
      do
     mkdir -p data/
    wget -P data/ \
     -4 \
     -w 0 \
     -t 3 \
     -rkpN -e robots=off \
     --header="Accept: text/html" \
     --user-agent="BashKat/1.0 (BashKat 1.0 Web Scraper Utility +http://www.bashkat.bot/)" \
     --referer="http://www.bashkat.bot" \
     --random-wait \
     --recursive \
     --no-clobber \
     --page-requisites \
     --convert-links \
     --restrict-file-names=windows \
     --domains $scrapeurl \
     --no-parent \
         $scrapeurl 
     done < "$filepath"
      printf "🏁Scrape Complete.\nHit Enter To Continue.👍"
       read anykey
./$(basename $0) && exit

 elif [ "$option" = "Quit" ];
 then
   printf "Quitting🏳"
    sleep 1
     clear
      exit
# ERRORS
  else
   clear
    printf "❌"
    sleep 1
   ./$(basename $0) && exit
  fi
 exit
done