This hypothesis posits that adversaries are deploying automated bot infrastructure to simulate legitimate user activity and obscure malicious reconnaissance within the Azure environment. Proactive hunting for these patterns is essential to distinguish between benign automation and sophisticated threat actors attempting to evade standard signature-based detections by mimicking normal operational noise.
rule TrumpBot : MALW
{
meta:
description = "TrumpBot"
author = "Joan Soriano / @joanbtl"
date = "2017-04-16"
version = "1.0"
MD5 = "77122e0e6fcf18df9572d80c4eedd88d"
SHA1 = "108ee460d4c11ea373b7bba92086dd8023c0654f"
strings:
$string = "trumpisdaddy"
$ip = "198.50.154.188"
condition:
all of them
}
This YARA rule can be deployed in the following contexts:
This rule contains 2 string patterns in its detection logic.
Here are 4 specific false positive scenarios for the TrumpBot detection rule in an enterprise environment, including suggested filters and exclusions:
Scheduled Patch Management Deployments
C:\Windows\SoftwareDistribution or specific service accounts like NT SERVICE\Wuauserv.Automated Compliance & Configuration Audits
Parent Process Name is TenableAgent.exe, QualysPCAgent.exe, or MsMpEng.exe. Furthermore, filter out events originating from dedicated management subnets (e.g., 10.20.x.x) reserved for security scanning infrastructure.Identity Management and Password Rotation Tasks