Ibrahim Saud
@tektrixIndiaCompletionist
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This rule detects periodic network beaconing patterns consistent with BabylonRAT malware. It flags established TCP connections to external networks that occur at a frequency exceeding 5 connections within a 300-second window, which may indicate a C2 check-in mechanism. Due to the heuristic nature of this detection, it is recommended to tune the threshold and correlate with payload analysis or entropy inspection to reduce noise.
This rule detects periodic network beaconing patterns consistent with BabylonRAT malware. It flags established TCP connections to external networks that occur at a frequency exceeding 5 connections within a 300-second window, which may indicate a C2 check-in mechanism. Due to the heuristic nature of this detection, it is recommended to tune the threshold and correlate with payload analysis or entropy inspection to reduce noise.
This rule detects modifications to the Windows hosts file by unauthorized processes. The hosts file is often targeted by adversaries to redirect network traffic, intercept communications, or prevent access to security-related websites.
This rule detects potential API abuse by identifying high-frequency API calls using the 'python-requests' user agent that occur within a short time window (120 seconds) immediately following a successful device code authentication event. This behavior is indicative of automated token theft or session hijacking where an adversary attempts to perform unauthorized actions quickly using tokens obtained via device code phishing.
This rule detects anomalous behavior where a single user account registers multiple devices within a very short timeframe (80 seconds). This pattern often follows the theft of a device code or OAuth authorization token, where an adversary attempts to rapidly enroll multiple rogue devices to maintain persistent access or bypass MFA controls.
This rule identifies the Stella_Gary modular C# backdoor framework, which has been attributed to the Kimsuky (APT-C-55) threat group. The rule functions by detecting specific naming conventions within the binary and the presence of .NET assembly loading capabilities combined with plugin management functionality, characteristic of this modular malware family.
Detects the execution of PowerShell with suspicious command-line arguments (e.g., -enc, -nop, -windowstyle hidden) originating from an LNK file launched by explorer.exe. This pattern is commonly used by adversaries to execute obfuscated malicious payloads embedded within shortcut files.
Detects the execution of PowerShell commands intended to gather system information, specifically targeting the discovery of security software (anti-virus/EDR) and virtualization/sandbox artifacts. This behavior is indicative of an attacker performing environment reconnaissance to identify defensive controls or to determine if the payload is executing within an analysis environment.
Detects unauthorized processes attempting to access browser credential database files such as Login Data for Chromium-based browsers or logins.json and key4.db for Firefox. The rule filters out known browser processes to isolate potential credential harvesting or exfiltration activity.
Detects an Azure AD Device Code authentication event followed within 60 seconds by a non-interactive Primary Refresh Token (PRT) sign-in event from the same user. This sequence is characteristic of adversary-in-the-middle (AiTM) phishing attacks where a user is tricked into authorizing a device code, and the adversary immediately leverages the resulting session/token to obtain a PRT for persistent access.
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