Aokigahara is a modular Windows information stealer observed in the wild that targets browser credentials, session cookies, cryptocurrency wallet data, and locally stored application secrets. It captures screenshots and clipboard contents, collects selected user files, queries Windows Credential Manager, and gathers system information, including running processes, installed software, and security products. Its collection targets include messaging clients, email applications, password managers, VPN clients, file-transfer tools, and gaming applications. It also drops a separate clipboard-manipulation component.
A distinctive AI-session collection module targets authentication files, session data, and configuration associated with Claude Code and Desktop, ChatGPT Desktop, Codex, Cursor, Windsurf, GitHub Copilot, Gemini CLI, JetBrains AI Assistant, Amazon Q, and Kiro. A separate developer-focused module collects Git credentials, SSH-related files that may contain private keys, and AWS, Microsoft Azure, and Google Cloud credential and configuration data. Not every collected file necessarily contains authentication secrets. Valid stolen credentials and reusable sessions can expose AI accounts, private repositories, and cloud resources; these capabilities involve theft from compromised endpoints rather than exploitation of vulnerabilities in the targeted services.
Aokigahara uses configurable debugger, virtual-machine, and sandbox checks, including hardware and process inspection and cursor-movement checks. It can terminate execution based on configured keyboard or Windows interface language exclusions. Additional evasion measures include hashed Windows API resolution, control-flow flattening, and AES-256-CBC-encrypted configuration. Collection modules are enabled through configuration flags. Stolen information is packaged into ZIP archives and uploaded using AES-256-GCM encryption with keys derived through X25519 key exchange. Its initial delivery mechanism, threat-actor attribution, and operators' monetization practices are not established.
180 indicators attributed across vendor reports, sandbox runs, and researcher write-ups. Values are masked here and available in full in Mallory.
21 sources tracked across advisories, community write-ups, and news. New activity surfaces here as Mallory finds it.