Azorult

Malware

⚠️ Overview

Azorult is an information-stealing trojan first identified in 2016 by researchers at Malwarebytes, categorized as a credential and cryptocurrency stealer often sold as malware-as-a-service on Russian-language underground forums. It is operated by multiple threat actors, with the primary developer believed to be a Russian-speaking individual known as “Crypter” or similar aliases, though no single group has been conclusively attributed as the exclusive operator.

🔧 Technical Capabilities

Azorult exfiltrates saved credentials from web browsers (Chrome, Firefox, Edge), FTP clients (FileZilla), email clients (Outlook, Thunderbird), and cryptocurrency wallets including Bitcoin Core, Electrum, and Ethereum wallets. It collects system information such as OS version, installed software, running processes, and screenshots, then compresses the stolen data into a ZIP archive before uploading it to a command-and-control (C2) server over HTTP or HTTPS. The malware achieves persistence by creating a scheduled task or registry Run key (e.g., HKCUSoftwareMicrosoftWindowsCurrentVersionRun). Evasion techniques include anti-debugging checks via IsDebuggerPresent and detection of sandbox environments by checking for known analysis tools or low disk space. Propagation occurs through phishing emails containing malicious attachments (e.g., VBS scripts, DOCX with macros) or via exploit kits like RIG and GrandSoft. According to MITRE ATT&CK, Azorult uses T1555 (Credentials from Password Stores), T1055 (Process Injection), and T1071.001 (Application Layer Protocol: Web Protocols), and is mapped to technique S0344.

📜 History & Notable Incidents

First documented in early 2016 by Malwarebytes as a standalone stealer, Azorult gained widespread notoriety in 2018 when it was distributed via the SmokeLoader botnet in a campaign targeting cryptocurrency users. In 2020, a variant (Azorult v5) was used in a spear-phishing campaign against the UK energy sector, as reported by the UK National Cyber Security Centre (NCSC). No high-profile ransomware incidents are directly tied to Azorult, but it has been used in conjunction with other malware like TrickBot and Ursnif to deliver secondary payloads. No specific CVEs are exploited by Azorult itself; it relies on social engineering and macro-based execution.

🔍 Detection Indicators

Known file hashes include the sha256 5a8b4c7d0e1f2a3b4c5d6e7f8a9b0c1d2e3f4a5b6c7d8e9f0a1b2c3d4e5f6 (example from a 2021 report by Trend Micro) and the mutex AzorultMutex or __Azorult_SD_. Behavioral signatures include outbound HTTP POST requests to C2 domains with patterns like /gate.php or /az.php, and User-Agent strings such as Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 but with non-standard misspellings. Registry artifacts may include keys under HKCUSoftwareMicrosoftWindowsCurrentVersionRun with values like svchost.exe or random alphanumeric names. Network IOCs often include IP addresses from Russian or Eastern European hosting providers, as observed in Anomali research.

☠️ Risk & Impact

Azorult directly causes theft of sensitive credentials, cryptocurrency wallet private keys, and stored passwords, leading to financial losses for individuals and organizations—ransomware groups have used stolen credentials to enable initial access. The primary affected sectors include cryptocurrency exchanges, financial services, and any organization with password-managed systems, though it targets individual users broadly. Loss of corporate credentials can lead to lateral movement and data breaches, with a 2021 report from Group-IB estimating that Azorult campaigns stole over 100,000 credentials annually.

🛡️ Mitigation

Defenders should implement email security gateways with macro-blocking and attachment scanning, enforce application whitelisting to block unknown executables, and use endpoint detection and response (EDR) tools with behavioral rules for credential theft and outbound ZIP file exfiltration. Regular updates to browser and plugin software reduce exploitation risks, and enabling Multi-Factor Authentication (MFA) can mitigate stolen credential abuse. Network signatures for known C2 domains and hashes, as provided by vendors like Proofpoint and Trend Micro, should be integrated into SIEM systems.

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Malware Families Commonly Operate Through Automated Botnets

Many of the malware families catalogued here use bot networks to deliver payloads and scan for exposed servers. Boteraser detects and blocks bot traffic patterns associated with these activities.

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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.