Tag BotNet

What Is A BotNet?

A botnet is a network of compromised computers or devices, often referred to as “bots” or “zombies,” which are controlled remotely by a cybercriminal or attacker. These bots are typically infected with malicious software (malware) that allows the attacker to take control of the infected devices without the owners’ knowledge.

Botnets can be used for various malicious activities, including:

1. Distributed Denial-of-Service (DDoS) Attacks: The botnet can be used to flood a target server or website with traffic, overwhelming its resources and causing it to crash or become unavailable.
2. Spam and Phishing Campaigns: Botnets can send out massive volumes of spam emails or phishing messages, often to steal sensitive information such as usernames, passwords, or financial data.
3. Data Theft: Attackers can use botnets to steal personal or financial data from infected devices, often through keylogging or other forms of surveillance.
4. Cryptocurrency Mining: Cybercriminals can hijack the processing power of infected devices to mine cryptocurrencies, which can be highly profitable.
5. Credential Stuffing: Botnets can automate the process of trying stolen usernames and passwords on various websites, attempting to gain unauthorized access to accounts.

Botnets can consist of hundreds, thousands, or even millions of infected devices, which makes them particularly powerful and difficult to combat. These devices can include computers, smartphones, IoT devices (such as cameras, smart thermostats, etc.), and more.
In some cases, botnet operators rent out or sell access to their botnets, allowing other criminals to carry out attacks for profit.

Botnets are illegal, and organizations and individuals need to protect their devices from becoming part of a botnet by using up-to-date antivirus software, firewalls, and practicing good cybersecurity hygiene.

What Is A BotNet?

A botnet works by infecting multiple devices (often referred to as “zombies” or “bots”) with malicious software (malware) and then allowing a central controller, known as the botmaster, to remotely command and control these devices. Here’s a step-by-step breakdown of how a botnet typically operates:

1. Infection:

The process begins when a device is infected with malware that allows it to be controlled remotely. This malware can be spread through various methods:

• Phishing emails: Malicious links or attachments that, when clicked, install the malware.
• Exploiting software vulnerabilities: Malware can take advantage of unpatched security holes in operating systems, software, or applications.
• Malicious websites: Visiting a compromised website or one that hosts exploit kits can result in automatic malware downloads.
• Trojan horses: Software that pretends to be legitimate but secretly installs malware when executed.
• Social engineering: Convincing a user to download and install the malicious software themselves.

Once the malware is installed on the device, it connects back to the command-and-control (C&C) server controlled by the attacker.

2. Connection to the Command-and-Control (C&C) Server:

After infection, the bot establishes a connection to a central server (or a set of servers) controlled by the attacker. The C&C server sends commands to the infected devices, and the bots report back on their status.

• Centralized C&C: In a centralized botnet, all infected devices communicate with a single server controlled by the botmaster. The server sends commands and updates to the bots.
• Decentralized (P2P) C&C: Some advanced botnets use a peer-to-peer (P2P) architecture, where infected devices communicate directly with each other and distribute commands, making it harder to shut down the botnet.

3. Botnet Command Execution:

Once the bots are connected to the C&C server, the botmaster can issue commands that will be executed by all or selected infected devices. Some common commands include:

• DDoS (Distributed Denial-of-Service): Directing all infected bots to flood a target website or server with massive amounts of traffic, overwhelming it and causing it to go offline.
• Data theft: Commands to capture sensitive information, such as login credentials, financial data, or personal information.
• Spamming: Directing infected devices to send out large volumes of spam emails, often for the purpose of spreading malware or conducting phishing attacks.
• Cryptocurrency Mining: Instructing infected devices to perform resource-intensive mining operations for cryptocurrency like Bitcoin or Monero.
• Credential stuffing: Using the bots to automatically try stolen login credentials on various websites in an attempt to gain unauthorized access to accounts.

4. Scalability:

Botnets can consist of hundreds, thousands, or even millions of compromised devices, making them highly scalable and difficult to stop. The botmaster can issue commands to any number of infected devices at once.
The scale and reach of the botnet often depend on how many devices it has infected, as well as the geographical distribution of those devices.

5. Obfuscation and Persistence:

Botnets are designed to be stealthy and persistent. They often use several techniques to avoid detection and removal:

• Encryption: Communications between the bots and the C&C server are often encrypted to prevent detection by network monitoring tools.
• Self-replication: Some botnets can spread themselves further, infecting new devices automatically and adding them to the botnet.
• Anti-analysis techniques: Botnet malware might check whether it’s running in a virtual machine or being analyzed by antivirus software before activating itself.
• Periodic updates: The botnet malware can be updated remotely to improve its stealth or add new capabilities.

6. Monetization:

The botmaster typically uses the botnet to carry out illegal activities for financial gain.
Some common monetization strategies include:

• Renting out the botnet: Cybercriminals may rent out the botnet to others for malicious purposes, such as launching DDoS attacks, spamming, or stealing data.
• Selling stolen data: If the botnet is stealing sensitive information, it can be sold on the dark web.
• Cryptocurrency mining: The botmaster may use the infected devices’ processing power to mine cryptocurrencies, which can be highly profitable.
• Ransomware delivery: The botnet can be used to distribute ransomware, which locks the victim’s data and demands a ransom for its release.

7. Challenges in Detection and Mitigation:

Botnets are difficult to detect and neutralize because:

• Distributed nature: Botnets rely on a large number of devices spread across many different networks, making it hard to target them all at once.
• Fast-flux: Some botnets use dynamic DNS techniques like “fast-flux” to constantly change their C&C servers’ IP addresses, making it hard for security researchers and authorities to track them down.
• Encryption: Botnet traffic is often encrypted, making it difficult for network monitoring tools to identify malicious activity.
• Diverse infected devices: Botnets can infect a wide variety of devices, including computers, smartphones, and IoT devices (such as smart cameras or routers), many of which may not have robust security protections.

8. Botnet Disruption and Defense:

Efforts to dismantle or disrupt a botnet generally include:

• Identifying and shutting down C&C servers: Law enforcement and security organizations can take down or seize the botmaster’s C&C infrastructure, disrupting the botnet’s operations.
• Botnet takedown operations: Organizations like Google, Microsoft, and cybersecurity firms sometimes work together to disrupt botnets by pushing out updates to the infected devices or issuing “sinkhole” commands.
• Botnet detection tools: Security solutions that identify botnet traffic, use machine learning models to spot anomalies, or look for common indicators of botnet activity.

9. Preventing Botnet Infections:

To avoid becoming part of a botnet:

• Keep software updated: Regularly update your operating system, software, and devices to fix security vulnerabilities.
• Use antivirus software: Use reliable antivirus or anti-malware programs to detect and block malicious software.
• Avoid suspicious links and attachments: Be cautious when opening unsolicited emails or clicking on suspicious links.
• Implement network security: Use firewalls and intrusion detection systems to monitor network traffic for signs of botnet activity.
• Enable two-factor authentication (2FA): This adds an extra layer of protection to your accounts, making them harder to hijack even if your credentials are compromised.

A botnet operates by infecting many devices with malware and using them for malicious purposes, typically controlled by a botmaster. The botnet can be used for a variety of criminal activities, and its decentralized nature makes it a significant challenge for cybersecurity professionals to dismantle and stop.

What Is A BotNet?

A History of Botnets: From the Beginning to Today

Botnets have been a significant threat in the world of cybersecurity for nearly two decades. They have evolved in both sophistication and scale, becoming an increasingly dangerous tool for cybercriminals.
Here’s a history of botnets, from their earliest days to the most contemporary and infamous examples.

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Early Days of Botnets (2000s)

1. Mafiaboy (2000)

• The First Notable DDoS Attack: Though not technically a botnet, the attack launched by a hacker known as “Mafiaboy” in 2000 is considered one of the first widely publicized DDoS (Distributed Denial of Service) attacks. It targeted Yahoo! and caused major disruptions to the website.
• The Botnet Evolution: While Mafiaboy didn’t use a botnet in the strictest sense, the attack showed the potential of using multiple systems in a coordinated way to bring down a large site. This laid the groundwork for future botnet-based DDoS attacks.

2. Rbot (2001)

• Early Malware: Rbot was one of the first examples of a botnet-building Trojan. It allowed cybercriminals to create and control a network of infected computers. Initially, it was used for remote access, data theft, and launching small-scale attacks, but the concept of botnets had now taken shape.

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Rise of Large-Scale Botnets (Mid-2000s to 2010)

3. Storm Worm (2007)

• One of the First Major Botnets: The Storm Worm is one of the most infamous early botnets, with estimates suggesting that it controlled millions of computers at its peak.
• Propagation: The botnet spread via spam emails with malicious attachments that, when opened, would install the Storm Worm on the victim’s computer. It was also known for its resilience, constantly changing its C&C (command and control) server addresses, making it difficult to dismantle.
• Malicious Activities: The botnet was used for sending spam, launching DDoS attacks, and distributing other malware. It was one of the first examples of botnets as a service, with various cybercriminal groups renting it for attacks.

4. Conficker (2008)

• Massive Scale: Conficker was one of the largest and most successful botnets of its time. At its peak, it infected over 12 million computers worldwide.
• Self-Propagation: It spread through vulnerabilities in Microsoft Windows (especially the MS08-067 vulnerability) and used advanced techniques to avoid detection and shut down.
• Complex Control: Conficker used a peer-to-peer (P2P) communication system to make it harder to locate and disrupt the C&C servers.
• Key Use: The botnet was involved in data theft, spam, and other criminal activities. While law enforcement and security organizations managed to mitigate it, Conficker left a lasting impact on cybersecurity awareness.

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Modern Era of Botnets (2010–2019)

5. Zeus/Zbot (2007–2010s)

• Banking Malware: Zeus, also known as Zbot, was a sophisticated malware that targeted banking institutions to steal login credentials and financial data.
• Botnet Building: The malware was used to create one of the most prolific financial botnets in history. It employed advanced keylogging and form-grabbing techniques to steal sensitive financial information.
• Impact: Zeus was widely distributed and used in major cybercrimes, including identity theft, fraud, and even facilitating ransomware attacks.
• Adaptation: Zeus later evolved into more advanced versions like Zeus Panda and Gameover Zeus, making it more difficult to detect and shut down.

6. ZeroAccess (2011–2013)

• A Search Engine Hijacker: ZeroAccess was a large and versatile botnet that could be used for multiple malicious purposes. It primarily infected machines to use their processing power for click fraud and Bitcoin mining.
• Multi-Purpose Botnet: ZeroAccess was also involved in distributing malware and launching DDoS attacks, and it had a highly decentralized infrastructure that made it difficult to track.
• Botnet Takedown: In 2013, a collaborative effort by Microsoft, Europol, and other entities took down the core of the ZeroAccess botnet.

7. Mirai (2016)

• IoT-Based Botnet: One of the most infamous contemporary botnets, Mirai took advantage of the growing number of Internet of Things (IoT) devices with weak security. These devices (like IP cameras, routers, and DVRs) were infected and turned into bots.
• Massive DDoS Attacks: The Mirai botnet launched some of the largest DDoS attacks in history, including the attack on Dyn, a major DNS provider, which caused widespread internet outages across the U.S.
• Innovation in DDoS: Mirai’s massive scale and its ability to use IoT devices demonstrated the potential for botnets to affect more than just computers and servers. The botnet also brought attention to the security vulnerabilities inherent in IoT devices.

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Contemporary and Recent Botnets (2020–Present)

8. Emotet (2014–2021)

• Malware-as-a-Service: Initially emerging as a banking Trojan, Emotet evolved into a botnet-as-a-service, with other criminals renting its infrastructure to distribute additional malware, including ransomware (like Ryuk) and TrickBot.
• Widespread Infection: Emotet was responsible for the distribution of millions of phishing emails and malware payloads. It was very sophisticated, using multilayered attacks, often acting as a “loader” that installed additional threats on infected systems.
• Law Enforcement Takedown: In early 2021, law enforcement agencies, including Europol, launched an international operation to dismantle Emotet’s infrastructure, but its impact still resonates in the form of related ransomware groups.

9. TrickBot (2016–Present)

• Advanced Botnet: TrickBot is one of the most sophisticated and adaptable botnets in recent years. Originally focused on financial theft, it evolved into a modular botnet that also facilitated ransomware attacks and data theft.
• Ransomware Distribution: TrickBot is often used to deploy Ryuk ransomware or Conti ransomware after infiltrating corporate networks. It’s been linked to large-scale attacks against hospitals, universities, and businesses.
• Resilient Infrastructure: TrickBot uses a highly distributed and resilient infrastructure, with peer-to-peer communications between infected systems, which makes it challenging for authorities to take down.
• Takedown Efforts: A joint operation by the FBI, Microsoft, and international law enforcement agencies disrupted TrickBot’s operations in 2020, but the botnet is still active in modified forms.

10. Qbot (2008–Present)

• Persistent Threat: Qbot (also known as QuakBot) is another sophisticated botnet that has been operating for over a decade. It is often used to facilitate bank fraud, data theft, and ransomware attacks.
• Advanced Techniques: Qbot is known for using living-off-the-land techniques, blending in with legitimate traffic and utilizing social engineering tactics to spread. It has also been part of ransomware campaigns like Ryuk and Conti.
• Survival and Adaptation: Despite multiple takedown attempts, Qbot has shown remarkable resilience, continuously adapting its tactics and using multi-layered obfuscation to evade detection.

11. Mirai 2.0 (2020s)

• New IoT Botnets: After the release of the original Mirai botnet, several variants, including Mirai 2.0, have emerged, continuing the trend of exploiting weakly secured IoT devices for large-scale DDoS attacks.
• Increased Focus on IoT Security: As IoT devices proliferate, these botnets have become a growing concern. Many devices have weak security protocols, making them easy targets for attackers to compromise and add to botnets.

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The Evolution and Future of Botnets

Botnets have evolved significantly over the past two decades, from simple Trojans to massive, distributed networks that can launch sophisticated attacks and steal sensitive data on a global scale. Early botnets like Storm Worm and Conficker laid the groundwork, while more recent botnets like Mirai, Emotet, and TrickBot demonstrate an ever-growing sophistication, often tied to organized cybercrime or nation-state actors.

Today, botnets target everything from computers to IoT devices, and the rise of ransomware-as-a-service and malware-as-a-service has made them even more dangerous. As IoT devices continue to proliferate, and with many having poor security, botnets are likely to remain a significant cybersecurity threat.

 

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:

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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​.

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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​.

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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​.

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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.

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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.

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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.

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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.

Part 1: BotNets – What Are They and What Is Their Purpose?

What Are Botnets?

A botnet is a network of compromised computers or devices, known as “bots” or “zombies,” which are controlled remotely by an attacker, often referred to as a “botmaster” or “bot herder.” These botnets can be used to perform a variety of malicious activities, typically without the knowledge of the device owners.

Evolution of Botnets

1. Early Days:
   • IRC-Based Botnets (1990s): The earliest botnets used Internet Relay Chat (IRC) to command infected machines. These bots were often created for fun or minor pranks but set the stage for more serious threats.
   • Example: The “Sub 7” and “Back Orifice” trojans were among the first to create such networks.
2. 2000s – Rise of Complexity:
   • Peer-to-Peer (P2P) Networks: Botnets evolved to use P2P networks to avoid centralized control and improve resilience.
   • Example: The “Storm Worm” utilized a P2P architecture to distribute commands.
3. 2010s – Advanced Botnets:
   • Botnets as a Service: The commercialization of botnets turned them into a service for hire.
   • Example: The “Mirai” botnet, which primarily targeted IoT devices, became infamous for its scale and impact.
4. 2020s – Sophisticated and Distributed Attacks:
   • Targeted Attacks and Cryptojacking: Modern botnets often focus on specific targets or exploit devices for cryptojacking.
   • Example: “Emotet” and “TrickBot” are known for their sophisticated modularity and targeted attacks.

Common Uses of Botnets

1. Distributed Denial of Service (DDoS) Attacks:
   • Overwhelm a target server or network with traffic to make it inaccessible.
2. Spam and Phishing:
   • Distribute large volumes of spam emails or phishing attempts to harvest personal information.
3. Data Theft:
   • Steal sensitive information from compromised systems.
4. Cryptojacking:
   • Utilize infected devices to mine cryptocurrency without the user’s consent.
5. Click Fraud:
   • Automate clicks on online ads to generate fraudulent revenue.

Key Terminology

• Botmaster/Bot Herder: The individual who controls the botnet.
• Command and Control (C2): The server or infrastructure used to send commands to the bots.
• Infection Vector: The method by which the botnet malware is spread (e.g., phishing, exploit kits).
• Zombies/Bots: Infected devices within the botnet.

Popular Variants

1. Mirai:
   • Known for its large-scale attacks using IoT devices.
   • Exploits default passwords on IoT devices.
2. Emotet:
   • Initially a banking trojan, evolved into a modular botnet used for a variety of malicious activities.
   • Known for its resilience and ability to distribute other malware.
3. Zeus/Zbot:
   • A banking trojan that evolved into a powerful botnet for stealing financial credentials.
4. Conficker:
   • One of the largest and most infamous botnets, known for its ability to spread through vulnerabilities in Windows operating systems.

Part 2: A Basic Example of a Botnet

Overview

Let’s look at a simple Python script example to demonstrate the concept of a botnet. This example is for educational purposes only and should not be used for any malicious activities.

Basic Botnet Example in Python

# Example BotNet In Python:

import socket
import threading

# This is the bot (client) code.

def connect_to_server():
    server_ip = "127.0.0.1"  # IP of the command and control server (for demonstration)
    server_port = 12345      # Port of the command and control server

    s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
    try:
        s.connect((server_ip, server_port))
        print("Connected to server")
        
        while True:
            command = s.recv(1024).decode('utf-8')
            if command == "shutdown":
                print("Shutting down...")
                break
            else:
                # Execute command
                print(f"Received command: {command}")
                # For security reasons, this part is left out in this example.
                # You could use os.system(command) to execute commands.
        
    except Exception as e:
        print(f"Error: {e}")
    finally:
        s.close()

def main():
    # Create multiple threads to simulate multiple bots
    for i in range(5):  # Simulating 5 bots
        t = threading.Thread(target=connect_to_server)
        t.start()

if __name__ == "__main__":
    main()

Explanation

1. Socket Setup:
   • The socket library is used to create a network connection. The bot connects to a predefined IP address and port number of the command and control (C2) server.
2. Connection Handling:
   • The connect_to_server() function establishes a connection to the C2 server and listens for commands.
3. Command Execution:
   • The bot waits for commands from the C2 server. If it receives a command (e.g., “shutdown”), it performs the action. In a real-world scenario, commands could be anything, including executing system commands or sending data.
4. Multithreading:
   • Multiple threads are created to simulate multiple bots connecting to the C2 server concurrently. Each thread represents an individual bot.
5. Error Handling:
   • Basic error handling is in place to catch and display any exceptions that occur during the connection or execution process.

Note

This example demonstrates a simplified version of a botnet client. In real-world scenarios, botnets are more complex and include additional features such as encryption, obfuscation, and advanced command structures. This script is provided for educational purposes to understand the basic principles of how botnets operate.

Related Links:
Home Network Router Attacks
BotNet Archive – For Educational Purposes Only!

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.”

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.”

“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 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.