⚠️ Overview

HackBrowserData is an open-source information-stealing tool first released on GitHub in March 2020 by the user "moonD4rk", designed to extract saved credentials, cookies, and browsing history from Chromium-based browsers. It is categorized as a credential stealer rather than a traditional malware family, but it has been adopted by threat actors for initial access and lateral movement campaigns. The tool is not associated with a specific APT group but has been observed in commodity malware operations and red-team engagements.

🔧 Technical Capabilities

HackBrowserData targets browsers including Chrome, Edge, Brave, Vivaldi, Opera, Yandex, and several Chromium forks by copying the browser’s SQLite3 database files (Login Data, Cookies, History, Web Data) from the user profile directory. On Windows, it leverages the CryptUnprotectData API (DPAPI) to decrypt saved passwords using the current user’s master key. The tool can also extract bookmarks, autofill forms, and credit card data. It does not include built-in persistence or command-and-control (C2) infrastructure; instead, it is typically dropped as a standalone executable via phishing attachments, malicious downloads, or as a second-stage payload from loaders like Ursnif or QakBot. Evasion techniques are minimal—the tool avoids DLL injection and instead runs as a user-space process that writes extracted data to a local file (e.g., .csv, .txt) in the system’s %TEMP% directory. No network communication is inherent, but operators often combine it with separate exfiltration mechanisms such as FTP, HTTP POST, or cloud storage uploads.

📜 History & Notable Incidents

Since its public release, HackBrowserData has been included in toolkits used by several cybercrime campaigns, including a 2021 operation distributing the Bumblebee loader where it was used to harvest credentials for follow-on ransomware deployment. In 2022, a campaign dubbed "Raccoon Stealer v2" incorporated a modified version of HackBrowserData to target cryptocurrency exchange logins. No specific CVEs are associated with the tool, as it exploits legitimate browser storage mechanisms; however, it is frequently detected by antivirus vendors as a generic TrojanSpy or PUA (Potentially Unwanted Application). Law enforcement actions have not directly targeted the tool’s author, but multiple takedowns of Telegram channels distributing it occurred in 2023.

🔍 Detection Indicators

Behavioral indicators include processes accessing files under paths like %LOCALAPPDATA%GoogleChromeUser DataDefaultLogin Data and %LOCALAPPDATA%MicrosoftEdgeUser DataDefaultCookies. Known file hashes vary per build, but static signatures include the string "HackBrowserData" embedded in the PE file metadata. Network indicators are absent unless paired with exfiltration scripts; analysts should monitor for large outbound HTTPS transfers to pastebin-like services or cloud storage APIs. The tool creates mutex names such as "GlobalHackBrowserDataMutex" in some builds. MITRE ATT&CK techniques used include T1555.003 (Credentials from Password Stores: Web Browsers) and T1217 (Browser Information Discovery).

☠️ Risk & Impact

The primary risk is the exfiltration of corporate credentials, session cookies, and financial account details, enabling attackers to bypass multi-factor authentication (MFA) by stealing active session tokens. Organizations in the finance, healthcare, and technology sectors have reported post-incident discovery of HackBrowserData logs used to access cloud consoles and email services. While the tool itself does not cause ransomware or system damage, its output frequently feeds credential-stuffing attacks or enables lateral movement in RDP and VPN environments. Financial losses per incident have ranged from $10,000 to over $500,000 in cases where stolen cookies led to business email compromise (BEC).

🛡️ Mitigation

Defenders should enforce application control policies to block unknown executables from running in user profiles, enable Windows Defender Attack Surface Reduction (ASR) rules to prevent browser credential theft, and deploy endpoint detection and response (EDR) rules that alert on access to SQLite browser database files. Regular user awareness training on phishing attachment risks is essential, as the tool relies on initial execution by the victim. Patches are not applicable; instead, organizations should implement credential guard and disable legacy DPAPI access for non-admin accounts where feasible.

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