Classification: Payload Synthesis

Operation
Silent Impact

Adversary AI Analysis // March 02, 2026

Artifact Overview

Artifact Name

RedTeamIran03.02.26.exe

SHA256

7400ee3072280087426fbaa018e1a5bfd1bd41148a5167dbb38420714bd5b328

Execution Environment

Windows 11 x64 (Virtualized Sandbox)

Executive Summary

RedTeamIran03.02.26.exe is a purpose-built red team artifact designed to emulate a high-impact anti-forensic wiper operation incorporating Iranian thematic elements. The payload was developed using Rust and program logic synthesized through LLM-assisted offensive code generation.

The artifact demonstrates how AI-assisted software synthesis can generate non-deterministic operational logic capable of evading traditional static detection methods during initial submission.

Detection Metrics

Initial Analysis (First Submission)

VirusTotal

9/72

Detections

MetaDefender

2/26

Detections

CrowdStrike Falcon

CLEAN

Static / ML Analysis

Artifact remains marked clean under static / ML evaluation.

Current Detection Status

VirusTotal

45/72

Active Detections

MetaDefender

11/26

Active Detections

CrowdStrike Falcon

CLEAN

Static / ML Evaluation

Detection delta demonstrates the lag between initial artifact submission and subsequent vendor signature development.

Behavioral Synthesis Chain

01

Defense Evasion

Environment validation through virtual machine detection and driver verification to limit execution within analysis environments.

02

Anti-Forensics

Automated Windows event log purging via wevtutil.exe to remove local telemetry artifacts.

03

Impact Simulation

Execution of cipher.exe to perform free-space wiping operations, emulating destructive data sanitation behavior.

04

Defacement Simulation

Registry manipulation combined with Persian / English broadcast messaging to simulate politically themed system defacement.

Defensive Context

Initial detection metrics demonstrate that AI-assisted payload synthesis can produce artifacts that evade signature-based detection during early distribution phases. Effective detection requires behavioral telemetry analysis rather than reliance on static indicators alone.

Research Context

This artifact was generated as part of Black Eagle Group™ adversary AI research and red team development activities. All testing was conducted within controlled virtualized environments for the purpose of studying emerging AI-assisted adversary techniques and evaluating defensive detection capabilities.

Policy & Intent

This artifact is intended solely for authorized defensive research and security validation. Contributions are submitted to vendor analysis platforms to support the improvement of detection telemetry for AI-orchestrated threats.

Reports available on Hybrid Analysis tag: #BlackEagleGroup

© 2026 BLACK EAGLE GROUP™. AUDIT COMPLETE.