Matrix Botnet Exploits IoT Devices for Widespread DDoS Attacks

Threat Group: Matrix
Threat Type: Distributed Denial-of-Service (DDoS) Botnet
Exploited Vulnerabilities: Weak/default credentials; known vulnerabilities in IoT devices, routers, and enterprise servers
Malware Used: Mirai, PYbot, Pynet, DiscordGo, Homo Network
Threat Score: High (8.5/10) — Due to its expansive scope targeting IoT and enterprise systems, easy-to-access attack tools, and financial motivations.
Last Threat Observation: November 28

Overview

Matrix, a rapidly evolving cyber threat actor, has launched a new Distributed Denial-of-Service (DDoS) campaign targeting a wide array of Internet-connected devices, including IoT systems, routers, and even enterprise servers. Aqua Nautilus researchers uncovered the campaign through honeypot detections, revealing Matrix's use of brute-force attacks, exploitation of known vulnerabilities, and reliance on publicly available hacking tools.

This campaign is emblematic of a broader trend where less technically sophisticated attackers, often referred to as script kiddies, leverage plug-and-play tools and pre-built malware to orchestrate large-scale cyberattacks. While Matrix’s methods are not highly advanced, their ability to integrate multiple attack vectors and automate exploitation processes demonstrates a significant threat to organizations globally.

Key Details

• Delivery Method: Brute-force attacks and exploitation of weak or default credentials in IoT devices, servers, and enterprise systems.
• Primary Targets: IoT devices such as IP cameras, routers, and DVRs; telecom equipment; enterprise servers using applications like Hadoop and HugeGraph.
• Primary Functions:
  1. Scanning for vulnerable systems using preconfigured scripts.
  2. Exploiting IoT-specific and server-based vulnerabilities (e.g., command injection flaws).
  3. Deploying malware such as Mirai to establish a botnet.
  4. Selling DDoS services via a Telegram-based automated storefront.
• Obfuscation Tactics: Heavy reliance on open-source scripts modified to mask malicious activities and emulate legitimate traffic.

Attack Vectors

Matrix exploits vulnerabilities and misconfigurations in IoT and enterprise devices to gain control over systems and integrate them into a botnet. Key attack mechanisms include:

1. IoT Vulnerabilities: Exploitation of weak credentials and firmware flaws in IP cameras, routers, and DVRs. For example, the GPON router vulnerability (CVE-2018-10561) enables attackers to bypass authentication mechanisms.
2. Server Exploits: Matrix targets servers running Hadoop and HugeGraph, leveraging vulnerabilities like CVE-2024-27348 for remote code execution (RCE).
3. Credential-Based Attacks: Using precompiled dictionaries, Matrix conducts brute-force attacks to compromise systems with default credentials such as admin:admin or root:camera.
4. Distributed Toolkit Integration: Matrix combines multiple malware strains, including Mirai variants and custom Python-based tools, to expand the botnet's reach and functionality.

Analysis of Tools and Infrastructure

Matrix’s attack framework relies heavily on open-source tools and a flexible operational structure. The botnet integrates malware such as Mirai, PYbot, and DiscordGo, each serving a specific role in the campaign.

• Mirai: A widely recognized malware targeting IoT devices. Its variants are repurposed to compromise devices with weak credentials and integrate them into the botnet.
• DiscordGo: A lightweight botnet framework leveraging Discord for command-and-control communications.
• PYbot and Pynet: Python-based frameworks enabling cross-platform malware deployment on Linux and Windows systems.
• Custom Scripts: Matrix modifies open-source tools to bypass security measures and evade detection. These scripts focus on scanning, exploiting, and propagating the botnet.

Matrix also uses GitHub repositories to host tools and coordinate updates, emphasizing a work-oriented operational style with consistent weekday activity.

Indicators of Compromise (IoCs)

IP Addresses

• 5[.]181[.]159[.]78
• 85[.]192[.]37[.]173
• 217[.]18[.]63[.]132
• 5[.]42[.]78[.]100
• 78[.]138[.]130[.]114

CVEs

• CVE-2014-8361
• CVE-2017-17106
• CVE-2017-17215
• CVE-2017-18368
• CVE-2018-10561
• CVE-2018-10562
• CVE-2018-9995
• CVE-2021-20090
• CVE-2022-30075
• CVE-2022-30525
• CVE-2024-27348

File Hashes (MD5)

• 0e3a1683369ab94dc7d9c02adbed9d89
• 53721f2db3eb5d84ecd0e5755533793a
• 5a66b6594cb5da4e5fcb703c7ee04083
• 76975e8eb775332ce6d6ca9ef30de3de
• 866c52bc44c007685c49f5f7c51e05ca
• 9181d876e1fcd8eb8780d3a28b0197c9
• 9c9ea0b83a17a5f87a8fe3c1536aab2f
• c332b75871551f3983a14be3bfe2fe79
• c7d7e861826a4fa7db2b92b27c36e5e2
• d653fa6f1050ac276d8ded0919c25a6f
• df521f97af1591efff0be31a7fe8b925

File Hashes (SHA1)

• 6136fe4df8c0cce502d50671def6b6bc2850a38d
• 84791db42a6f321ea70cfcbf13913fa4e02533f8
• 8ba1f42c61e1bef97afb48b1e741c889cc0cad50
• 95a5ff1372f352434525a416570eef4379ebac19
• ada6c6646cc86e12a09355944700debf8abd2a55
• c72cd784e908c2026549be7439418f7d126936b9

File Hashes (SHA256)

• 0ee827d23752c2afc1b07e5312986703f63e05b8c4f1902f5db07bb494e4d057
• 2e7682abe30d93afb3bd9dee0011c450c1d72d727151344b8b7360441571e007
• 424058facc8f16fd578190a612bc3f9178f5e393d345c2330c39436abb4d1142
• 8dfe94a1b02d1330886ad4458b32db3da4b872f9c2116657840de499fee5438a
• aee08f24f2e0be5af8b9a7947e845e8364be2f8b5ff874fbc3e7a4c81ecdad83
• fa1b9e78b59cdb26d98da8b00fe701697a55ae9ea3bd11b00695cfbba2b67a7a

Mitigation and Defense Strategies

1. Change Default Credentials: Configure strong, unique passwords for IoT devices and administrative accounts.
2. Patch and Update Devices: Regularly apply firmware and software updates to fix known vulnerabilities, especially on IoT devices.
3. Monitor Network Activity: Deploy intrusion detection systems (IDS) and monitor for unusual traffic patterns indicative of DDoS activity.
4. Segment IoT Networks: Isolate IoT devices from critical systems using network segmentation to limit exposure.
5. Utilize Threat Intelligence: Leverage IoCs and vulnerability details to proactively identify potential threats.

Expanded Analysis from Aqua Nautilus

The Matrix botnet campaign exemplifies how accessible tools and low technical barriers enable even novice attackers to execute high-impact campaigns. While the primary targets are IoT devices, Matrix’s focus on enterprise servers signals a shift toward more strategic targeting.

• Evolution of Script Kiddies: The proliferation of AI-assisted tools and publicly available hacking frameworks has significantly empowered low-skilled attackers.
• Financial Motivation: Despite indications of Russian origins, Matrix demonstrates a clear business-driven approach, focusing on monetizing compromised devices rather than pursuing ideological goals.
• Scale of the Threat: With an estimated 35 million devices potentially at risk, even a conservative compromise rate could enable Matrix to assemble a botnet of over 1.5 million devices.

Conclusion

The Matrix botnet highlights the evolving threat landscape where accessible tools and minimal expertise can yield significant disruptions. Organizations must prioritize robust security practices, such as securing IoT devices, enforcing strong password policies, and patching vulnerabilities, to defend against such large-scale campaigns.

Proactive detection, coupled with intelligence-driven security measures, is essential to mitigate the risks posed by threats like Matrix.

Sources

1. The Hacker News
   Matrix Botnet Exploits IoT Devices in Widespread DDoS Botnet Campaign
2. CyberScoop
   Here’s how simple it is for script kiddies to stand up DDoS services
3. InfoSecurity Magazine
   New DDoS Campaign Exploits IoT Devices and Server Misconfigurations
4. SiliconANGLE
   Aqua Security uncovers massive denial-of-service campaign targeting 35M devices