Mirai: The IoT Botnet
Mirai is a well-known IoT botnet that has evolved significantly since its initial discovery in 2016. Originally used primarily for massive distributed denial-of-service (DDoS) attacks, recent variants from 2025 show enhanced stealth, modularity, and capabilities including data exfiltration and persistence. These newer samples use advanced evasion techniques such as UPX packing and leverage common network utilities to avoid detection. The threat targets a broad range of IoT devices, exploiting their often weak security postures. Although no known exploits are currently active in the wild for this variant, the botnet’s evolution increases its potential impact. European organizations with extensive IoT deployments are at risk, especially those with insufficient device management and monitoring. Mitigation requires proactive network monitoring, updated antivirus signatures, and strict IoT device security policies. Countries with high IoT adoption and critical infrastructure reliance on connected devices are most vulnerable. Given the medium severity rating and the expanded threat capabilities, vigilance is essential to prevent exploitation and long-term compromise.
AI Analysis
Technical Summary
Mirai is a notorious IoT botnet first identified in 2016, primarily known for orchestrating large-scale DDoS attacks by compromising vulnerable IoT devices such as routers, cameras, and DVRs. The 2025 variant of Mirai represents a significant evolution in its threat profile. Unlike the original, which focused mainly on volumetric DDoS, the modern Mirai employs sophisticated evasion techniques including UPX packing—a method of compressing and obfuscating binaries to hinder analysis and detection. It also uses legitimate network utilities to blend in with normal traffic, increasing stealth and persistence. The new variant is modular, allowing it to adapt its payloads and behaviors dynamically, extending its capabilities beyond DDoS to include data exfiltration and establishing long-term footholds on infected devices. Technical analysis reveals changes in execution flow, network communication patterns, and file characteristics compared to the original Mirai. Indicators of compromise include specific IP addresses and file hashes associated with this variant. Although no active exploits are currently reported in the wild, the botnet’s enhanced stealth and modularity raise the risk of future attacks targeting IoT ecosystems. The threat leverages common IoT device vulnerabilities such as default credentials and unpatched firmware, exploiting the widespread lack of robust security controls in these devices. Prevention strategies emphasize maintaining updated antivirus software capable of detecting packed binaries, avoiding suspicious links or downloads that could deliver the malware, and implementing continuous system and network monitoring to detect anomalous behavior indicative of infection or data exfiltration attempts.
Potential Impact
For European organizations, the evolving Mirai botnet poses multifaceted risks. The widespread use of IoT devices in industries such as manufacturing, healthcare, smart cities, and critical infrastructure means that infections could disrupt essential services through DDoS attacks or sabotage. The new focus on data exfiltration threatens confidentiality, potentially exposing sensitive operational or personal data. Long-term persistence on devices could facilitate further lateral movement within networks, increasing the risk of broader compromise. The stealth and modularity of the 2025 variant make detection and remediation more challenging, potentially leading to prolonged infections and increased operational impact. Disruptions caused by DDoS attacks could affect online services, causing financial losses and reputational damage. Additionally, compromised IoT devices could be leveraged as part of larger botnets to attack other targets, implicating infected organizations in broader cybercrime activities. The threat is particularly concerning for sectors with high IoT device density and limited security management, as well as for organizations lacking comprehensive incident response capabilities.
Mitigation Recommendations
To mitigate the risks posed by the modern Mirai botnet variant, European organizations should implement a multi-layered security approach tailored to IoT environments. First, conduct thorough inventories of all IoT devices to identify unmanaged or vulnerable endpoints. Enforce strong authentication by changing default credentials and applying unique, complex passwords on all devices. Regularly update device firmware and software to patch known vulnerabilities. Deploy network segmentation to isolate IoT devices from critical business systems, limiting lateral movement opportunities. Utilize advanced endpoint protection solutions capable of detecting packed malware binaries such as those using UPX packing. Implement continuous network traffic monitoring and anomaly detection to identify unusual communication patterns or data exfiltration attempts. Employ threat intelligence feeds to update detection rules with known indicators of compromise like the provided IP addresses and file hashes. Educate staff on the risks of phishing and suspicious links that could deliver malware payloads. Develop and regularly test incident response plans specific to IoT-related incidents. Finally, collaborate with device manufacturers and service providers to ensure security best practices are followed throughout the device lifecycle.
Affected Countries
Germany, France, United Kingdom, Netherlands, Italy, Spain, Sweden
Indicators of Compromise
- ip: 160.30.44.120
- hash: 1da4d5f6186e99ab77a9845dcd7c3d85
- hash: 7fece27824b34816e0cc18c2ab3ee3ff
- hash: 425c3449a87b561550fc7f66544d00cb87ce3374
- hash: 85f2287445fc0de461e357a7a2ffc26cd26955ad
- hash: a80261af4b7f2cad62a55983686c91c2a1aa78033451b851c4ac4f5fdb6f94a6
- hash: f139c78c06276aaa4139c04859754f287a1c497e380627e64dbe7c901ea0ab43
- ip: 65.222.202.53
Mirai: The IoT Botnet
Description
Mirai is a well-known IoT botnet that has evolved significantly since its initial discovery in 2016. Originally used primarily for massive distributed denial-of-service (DDoS) attacks, recent variants from 2025 show enhanced stealth, modularity, and capabilities including data exfiltration and persistence. These newer samples use advanced evasion techniques such as UPX packing and leverage common network utilities to avoid detection. The threat targets a broad range of IoT devices, exploiting their often weak security postures. Although no known exploits are currently active in the wild for this variant, the botnet’s evolution increases its potential impact. European organizations with extensive IoT deployments are at risk, especially those with insufficient device management and monitoring. Mitigation requires proactive network monitoring, updated antivirus signatures, and strict IoT device security policies. Countries with high IoT adoption and critical infrastructure reliance on connected devices are most vulnerable. Given the medium severity rating and the expanded threat capabilities, vigilance is essential to prevent exploitation and long-term compromise.
AI-Powered Analysis
Technical Analysis
Mirai is a notorious IoT botnet first identified in 2016, primarily known for orchestrating large-scale DDoS attacks by compromising vulnerable IoT devices such as routers, cameras, and DVRs. The 2025 variant of Mirai represents a significant evolution in its threat profile. Unlike the original, which focused mainly on volumetric DDoS, the modern Mirai employs sophisticated evasion techniques including UPX packing—a method of compressing and obfuscating binaries to hinder analysis and detection. It also uses legitimate network utilities to blend in with normal traffic, increasing stealth and persistence. The new variant is modular, allowing it to adapt its payloads and behaviors dynamically, extending its capabilities beyond DDoS to include data exfiltration and establishing long-term footholds on infected devices. Technical analysis reveals changes in execution flow, network communication patterns, and file characteristics compared to the original Mirai. Indicators of compromise include specific IP addresses and file hashes associated with this variant. Although no active exploits are currently reported in the wild, the botnet’s enhanced stealth and modularity raise the risk of future attacks targeting IoT ecosystems. The threat leverages common IoT device vulnerabilities such as default credentials and unpatched firmware, exploiting the widespread lack of robust security controls in these devices. Prevention strategies emphasize maintaining updated antivirus software capable of detecting packed binaries, avoiding suspicious links or downloads that could deliver the malware, and implementing continuous system and network monitoring to detect anomalous behavior indicative of infection or data exfiltration attempts.
Potential Impact
For European organizations, the evolving Mirai botnet poses multifaceted risks. The widespread use of IoT devices in industries such as manufacturing, healthcare, smart cities, and critical infrastructure means that infections could disrupt essential services through DDoS attacks or sabotage. The new focus on data exfiltration threatens confidentiality, potentially exposing sensitive operational or personal data. Long-term persistence on devices could facilitate further lateral movement within networks, increasing the risk of broader compromise. The stealth and modularity of the 2025 variant make detection and remediation more challenging, potentially leading to prolonged infections and increased operational impact. Disruptions caused by DDoS attacks could affect online services, causing financial losses and reputational damage. Additionally, compromised IoT devices could be leveraged as part of larger botnets to attack other targets, implicating infected organizations in broader cybercrime activities. The threat is particularly concerning for sectors with high IoT device density and limited security management, as well as for organizations lacking comprehensive incident response capabilities.
Mitigation Recommendations
To mitigate the risks posed by the modern Mirai botnet variant, European organizations should implement a multi-layered security approach tailored to IoT environments. First, conduct thorough inventories of all IoT devices to identify unmanaged or vulnerable endpoints. Enforce strong authentication by changing default credentials and applying unique, complex passwords on all devices. Regularly update device firmware and software to patch known vulnerabilities. Deploy network segmentation to isolate IoT devices from critical business systems, limiting lateral movement opportunities. Utilize advanced endpoint protection solutions capable of detecting packed malware binaries such as those using UPX packing. Implement continuous network traffic monitoring and anomaly detection to identify unusual communication patterns or data exfiltration attempts. Employ threat intelligence feeds to update detection rules with known indicators of compromise like the provided IP addresses and file hashes. Educate staff on the risks of phishing and suspicious links that could deliver malware payloads. Develop and regularly test incident response plans specific to IoT-related incidents. Finally, collaborate with device manufacturers and service providers to ensure security best practices are followed throughout the device lifecycle.
Affected Countries
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Technical Details
- Author
- AlienVault
- Tlp
- white
- References
- ["https://www.pointwild.com/threat-intelligence/mirai-the-iot-botnet"]
- Adversary
- Mirai
- Pulse Id
- 68f7ffea7e83f27edd935587
- Threat Score
- null
Indicators of Compromise
Ip
| Value | Description | Copy |
|---|---|---|
ip160.30.44.120 | — | |
ip65.222.202.53 | — |
Hash
| Value | Description | Copy |
|---|---|---|
hash1da4d5f6186e99ab77a9845dcd7c3d85 | — | |
hash7fece27824b34816e0cc18c2ab3ee3ff | — | |
hash425c3449a87b561550fc7f66544d00cb87ce3374 | — | |
hash85f2287445fc0de461e357a7a2ffc26cd26955ad | — | |
hasha80261af4b7f2cad62a55983686c91c2a1aa78033451b851c4ac4f5fdb6f94a6 | — | |
hashf139c78c06276aaa4139c04859754f287a1c497e380627e64dbe7c901ea0ab43 | — |
Threat ID: 68f8941fd59611fbd95e412e
Added to database: 10/22/2025, 8:21:51 AM
Last enriched: 10/22/2025, 8:37:42 AM
Last updated: 10/26/2025, 7:50:28 AM
Views: 44
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