URLhaus-PL-844b854d590e9ebe4ae09a7233125f473ce3b05312bce3374b5f05c7d50d123a medium

Description

Malware family: Mirai. File type: elf. Size: 166,968 bytes. First seen: 2026-08-04 21:29:28.

Indicators of Compromise (4)

Each indicator is enriched from the IOC database, threat-intel feed corroboration (Threat Hunt) and VirusTotal. Click one to expand.

References (2)

• Download sample (ZIP, password: infected) URLhaus
• URLhaus payload page URLhaus

• Mirai Malware Analysis, Overview by ANY.RUN
  web:any.run

  Mirai is a self-propagating malware that scans the internet for vulnerable IoT devices and infects them to create a botnet. Mirai variants utilize lists of common default credentials to gain access to devices. Mirai's primary use is for launching distributed denial-of-service (DDoS) attacks, but it has also been used for cryptocurrency mining.

  2026-08-05 06:48 UTC
• URLhaus: mirai Malicious URLs | SOC Hunt Feed
  web:davidgodwinpratt.com

  The detection identifies potential Mirai botnet command-and-control (C2) communication attempts through known malicious URLs, indicating possible compromise of endpoints. SOC teams should proactively hunt for this behavior in Azure Sentinel to identify and mitigate Mirai -related botnet activity before it leads to widespread network compromise.

  2026-08-05 06:48 UTC
• URLhaus: mirai Malicious URLs | SOC Hunt Feed
  web:davidgodwinpratt.com

  Filter/Exclusion: Exclude URLs containing the string test_payload or sandbox-analysis. Scenario: A scheduled job runs a network scan using Nmap with a custom script that includes a Mirai -related payload for vulnerability assessment.

  2026-08-05 06:48 UTC
• Mirai (malware) - Wikipedia
  web:en.wikipedia.org

  Mirai (from the Japanese word for "future", 未来) is malware that turns networked devices running Linux into remotely controlled bots that can be used as part of a botnet in large-scale network attacks.

  2026-08-05 06:48 UTC
• GitHub - curbengh/urlhaus-filter: Mirror of https://gitlab.com/malware ...
  web:github.com

  A blocklist of malicious websites that are being used for malware distribution, based on the Database dump (CSV) of Abuse.ch URLhaus . Blocklist is updated twice a day.

  2026-08-05 06:48 UTC
• Mirai Source Code - GitHub
  web:github.com

  This repository contains the leaked source code of the Mirai botnet, originally created to infect IoT devices and launch large-scale DDoS attacks. This code is provided strictly for cybersecurity research, reverse engineering, malware analysis, and detection development purposes only.

  2026-08-05 06:48 UTC
• Mirai (Malware Family) - Fraunhofer
  web:malpedia.caad.fkie.fraunhofer.de

  Mirai is one of the first significant botnets targeting exposed networking devices running Linux. Found in August 2016 by MalwareMustDie, its name means "future" in Japanese. Nowadays it targets a wide range of networked embedded devices such as IP cameras, home routers (many vendors involved), and other IoT devices.

  2026-08-05 06:48 UTC
• URLhaus | Malware URL exchange
  web:urlhaus.abuse.ch

  URLhaus URLhaus is a platform from abuse.ch and Spamhaus dedicated to sharing malicious URLs that are being used for malware distribution. Report URLs and explore the database for valuable intelligence. Use the APIs, to seamlessly push and pull signals, and automate bulk queries. With this intelligence, gain insights into malware behavior, to help identify, track, and mitigate against malware ...

  2026-08-05 06:48 UTC
• URLhaus | Mirai
  web:urlhaus.abuse.ch

  In case URLhaus is able to identify the associated malware family, the payload will be tagged accordingly (field signature). The page below gives you an overview on payloads that URLhaus has identified as Mirai .

  2026-08-05 06:48 UTC
• YARAify | Rule ELF_Mirai
  web:yaraify.abuse.ch

  You are currently viewing the YARAhub entry of the YARA rule ELF_Mirai. Depending on the TLP classification of this YARA rule chosen by the author, further information about this YARA rule is available below.

  2026-08-05 06:48 UTC

Only Available for Registered Users. Sign in to view.