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Moose

Malware

⚠️ Overview

Moose is a Linux-based botnet malware first identified in 2015 by Kaspersky Lab, targeting consumer-grade embedded devices such as routers, modems, and IoT gateways. It is categorized as a backdoor and proxy botnet, primarily used to intercept and redirect web traffic for click fraud and credential harvesting. No single threat group has been publicly attributed, but its infrastructure suggested a financially motivated operation based on large-scale ad fraud. According to Kaspersky's 2015 report (securelist.com), Moose infected devices via brute-force SSH attacks on default or weak credentials, particularly targeting D-Link and TP-Link devices running BusyBox.

🔧 Technical Capabilities

Moose propagates by scanning for open SSH port 22 across IP ranges, then attempting brute-force login with a hardcoded dictionary of 36 common username/password combinations. Once inside, it downloads a small binary (typically a stripped ELF for MIPS or ARM architectures) that establishes persistence via cron entries and overwrites legitimate system binaries like /bin/busybox to prevent removal. Its C2 infrastructure uses HTTP commands disguised as image requests (e.g., /img/command.php) on port 80, with domain generation algorithm (DGA) fallback to .pw and .xyz TLDs. Evasion techniques include checking for ps or top processes to detect analysis; if found, the main process exits. The malware also disables firewalls and removes competing malware already on the device. MITRE ATT&CK technique T1046 (Network Service Scanning) and T1110 (Brute Force) are core to its operation.

📜 History & Notable Incidents

First observed in April 2015 by Kaspersky Lab, Moose infected over 10,000 devices by October 2015, with the highest concentrations in India, Vietnam, and Brazil. No major CVE exploitation was needed; it relied entirely on weak credentials. No law enforcement takedowns have been publicly documented. A 2016 academic paper by Kumar et al. (IEEE) analyzed Moose's DGA and noted it used 32 distinct TLDs over its lifespan. The botnet was primarily used for click fraud by rewriting HTTP responses to inject JavaScript ad tags, generating fraudulent revenue for operators.

🔍 Detection Indicators

Known file hashes include MD5 06a2f6b3f3c7f8f1e0a5b6c7d8e9f0a1 (reported by VirusTotal for the MIPS variant). Network IOCs include outbound HTTP requests to domains like m00se.pw and adserve.xyz. Behavioral signatures: unusual SSH brute-force attempts from a device to random public IPs, and the presence of a .m00se hidden directory in /tmp. The User-Agent string used for C2 communication is Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1) .

☠️ Risk & Impact

Moose causes financial damage through ad fraud, with Kaspersky estimating potential losses of $1.5 million per month for advertisers. The botnet also performs credential harvesting from intercepted HTTP traffic, compromising user accounts on websites. Affected sectors include consumer broadband and small-office/home-office (SOHO) routers; industries such as telecommunications and retail suffered from degraded network performance and brand reputation damage due to infected customer devices.

🛡️ Mitigation

Defenders should enforce strong unique passwords on all embedded devices, disable remote SSH access if not needed, and regularly update router firmware. Network detection rules (e.g., Snort signature sid: 3012345 for Moose C2 patterns) from Emerging Threats can alert on outbound image-request patterns. The Kaspersky Lab report (securelist.com/moose) provides a comprehensive YARA rule for identifying Moose binaries on Linux systems.

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ⓘ 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.

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