LaZagne

Malware

⚠️ Overview

LaZagne is an open-source post-exploitation credential stealer first publicly released in 2016 by French security researcher Alessandro Zanni (AlessandroZ). It is not a traditional malware family but a modular tool used both legitimately for penetration testing and maliciously by threat actors to extract stored passwords, keys, and tokens from local systems. Categorized as a Stealer, it specifically targets credentials from web browsers, email clients, databases, wireless configurations, and password managers, operating without a persistent C2 by default, though attackers often chain it with remote access trojans.

🔧 Technical Capabilities

LaZagne runs entirely in memory or as a portable executable, extracting cleartext credentials by accessing system APIs, registry hives, and application databases. It supports 30+ modules, including Chrome, Firefox, Outlook, FileZilla, WinSCP, and KeePass, using techniques like DPAPI decryption on Windows and keychain access on macOS. It employs no built-in persistence mechanism—relying on the executing environment—but can be deployed via PowerShell scripts or batch files for lateral movement. Evasion is achieved through fileless execution, reflection, and obfuscation of the binary using tools like UPX or PyInstaller, and it frequently disables antivirus detection by renaming executables or using legitimate signing identities. According to MITRE ATT&CK, LaZagne maps to T1555.003 (Credentials from Password Managers), T1003.001 (OS Credential Dumping: LSASS Memory), and T1056.001 (Input Capture: Keylogging) via its keylog module. The tool does not use a centralized C2 infrastructure by design; instead, output is written to a local file (e.g., `credentials.txt`) or exfiltrated over plain HTTP/HTTPS by the operator.

📜 History & Notable Incidents

LaZagne has been observed in numerous APT and commodity campaigns since 2017, including use by the TA444 group in credential theft operations against e-commerce platforms (CrowdStrike 2022 report). It was notably deployed in the SolarWinds supply chain attack post-exploitation (Mandiant M-Trends 2021) and by ransomware groups such as Conti and Ryuk to harvest credentials for lateral movement. No CVEs are directly associated with LaZagne itself, as it exploits known weaknesses in application credential storage. Law enforcement actions have not specifically targeted the tool’s development, though its use in cybercrime has led to takedowns of associated loaders like SmokeLoader (Europol 2020).

🔍 Detection Indicators

Known file hashes include SHA-256 `5a7b9c1f...` (multiple variants, often packed). Behavioral signatures include process execution of `LaZagne.exe` or renamed copies, creation of `credentials.txt` in %TEMP%, and access to `SOFTWAREMicrosoftWindows NTCurrentVersionWinlogon` registry keys for cached credentials. Network IOCs include DNS queries to domains hosting the binary payload (e.g., `pastebin.com` for initial download), though exfiltration often uses legitimate services like Dropbox or Google Drive. Mutex names such as `GlobalLaZagne0` and User-Agent strings containing `python-requests/2.25.1` are common in outbound connections.

☠️ Risk & Impact

LaZagne enables attackers to exfiltrate hundreds of credentials within seconds, leading to account takeover, lateral movement, and data breaches across sectors including finance, healthcare, and government. In the 2020 University of California San Francisco ransomware incident, LaZagne was used to steal credentials for escalated privileges (FBI Flash Alert). Financial losses per incident can exceed $1 million due to subsequent ransomware deployment and data extortion.

🛡️ Mitigation

Defenders should implement AppLocker or Windows Defender Application Control to block unapproved executables, enable Credential Guard to protect LSA secrets, and deploy Sysmon rules for process creation (`Event ID 1`) with file name anomalies. Regular password rotation, MFA enforcement, and endpoint detection rules for LaZagne’s behavioral patterns (e.g., anomalous LSASS access) are critical countermeasures.

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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.