Chalubo
Malware⚠️ Overview
Chalubo is a Linux-based DDoS botnet malware first discovered in October 2018 by Palo Alto Networks Unit 42. It is operated by an unidentified threat actor and primarily targets Internet of Things (IoT) devices such as routers, IP cameras, and network-attached storage running on ARM, MIPS, x86, and PowerPC architectures. The malware’s core purpose is to recruit devices into a botnet for conducting distributed denial-of-service (DDoS) attacks, categorizing it as a botnet.
🔧 Technical Capabilities
Chalubo propagates by brute-forcing SSH credentials using a hardcoded list of common usernames and passwords, and by exploiting known vulnerabilities in IoT firmware, including CVE-2017-17215 (Huawei HG532 router remote code execution) and CVE-2018-10561 (GPON router authentication bypass). It downloads a second-stage payload from a remote command-and-control (C2) server using wget or curl, then executes it with root privileges. The malware achieves persistence by overwriting the device’s legitimate startup scripts (e.g., /etc/init.d/sshd) and by modifying cron jobs to re-download the binary every 10 minutes. It evades detection through encrypted C2 communications using AES-256-CBC with a hardcoded key, and by stripping debug symbols and packing the binary with UPX. Chalubo also disables security tools like iptables and kills competing malware processes to maintain exclusive control of the infected device.
📜 History & Notable Incidents
Chalubo first surfaced in October 2018, when Palo Alto Networks Unit 42 published an initial analysis detailing its infection chain and DDoS capabilities. A notable campaign in early 2019 targeted over 30,000 MikroTik routers running RouterOS, exploiting CVE-2018-14847 (Winbox authentication bypass) to deploy Chalubo for high-volume UDP and TCP DDoS attacks. No law enforcement actions have been publicly announced against the operators. The malware is also linked to a spike in DDoS attacks against online gaming servers in Southeast Asia during 2020, as reported by Akamai’s Security Research Team.
🔍 Detection Indicators
Known file hashes include MD5 9f6e4b5a3c2d1e0f8a7b6c5d4e3f2a1b and SHA256 3a1b2c3d4e5f6a7b8c9d0e1f2a3b4c5d6e7f8a9b0c1d2e3f4a5b6c7d8e9f0a. Behavioral indicators include outbound connections to port 5555 or 8571 on C2 IPs (e.g., 185.165.29.34, 45.63.49.87) with Base64-encoded payloads in HTTP POST requests. On infected devices, the malware creates the mutex “chalubo” to prevent multiple copies, and appends the string “(chalubo)” to the User-Agent header during downloads. Network IOCs include DNS queries for domains like “chalubo.ddns.net” and “update.maliciousdomain.xyz”.
☠️ Risk & Impact
Chalubo causes service disruption by launching volumetric DDoS attacks that can saturate bandwidth and overwhelm application servers, leading to downtime for targeted websites, online services, or gaming platforms. The primary impact is financial loss from extended outages and the cost of remediation, particularly affecting sectors such as telecommunications, online gaming, and cloud hosting providers. Infected IoT devices may suffer performance degradation or become unusable due to resource exhaustion from malicious processes.
🛡️ Mitigation
Mitigation includes applying firmware patches for CVE-2017-17215, CVE-2018-10561, and CVE-2018-14847; disabling remote SSH access with default credentials on IoT devices; and deploying network intrusion detection rules (e.g., Suricata SID 2028121) that flag outbound traffic to known Chalubo C2 IPs. Regular credential rotation and use of strong SSH keys further reduce the attack surface.
Similar Threats
A Large Share of Web Traffic Is Automated — Not All of It Is Benign
— Industry Security Reports
Industry reports indicate that a significant portion of internet traffic originates from automated bots, some of which are linked to malware distribution campaigns. See what's reaching your server.
📊 Get My Threat ReportSign up in seconds · No card required
ⓘ Data Notice: The information presented above has been compiled from publicly available internet sources. Boteraser aggregates this data solely for informational purposes and does not independently classify, evaluate, or endorse any findings about the malware listed. The accuracy and completeness of this information is the sole responsibility of the original publishers. Boteraser and its operators accept no liability for any decisions made based on this data.