AI-Generated EDR Evasion Toolkit: Detecting Automated AD Discovery & Encryption Attacks

Introduction

The cybersecurity landscape has shifted again with the emergence of an AI-built encryption-based toolkit actively used in the wild to automate Endpoint Detection and Response (EDR) evasion and Active Directory (AD) discovery. As we navigate through 2026, the commoditization of sophisticated evasion techniques via artificial intelligence is no longer theoretical—it is an operational reality.

This toolkit represents a significant escalation in threat capability. By automating the "reconnaissance" and "defense evasion" phases of the kill chain, adversaries reduce the time required to move laterally from days to minutes. For defenders, this means the traditional window for detecting anomalous behavior has collapsed. We must shift our posture from reactive alert triage to proactive hunting for the specific TTPs (Tactics, Techniques, and Procedures) inherent in these AI-generated payloads.

Technical Analysis

The threat actor toolkit in question leverages AI generation to create polymorphic code variants, effectively bypassing static signature-based detection. The core functionality revolves around two primary objectives: mapping the victim's environment and blinding the security controls.

Affected Platforms:

Microsoft Windows environments (Active Directory domains)
Enterprise endpoints relying on EDR solutions

Attack Vector and Mechanics:

EDR Evasion: The toolkit employs userland hooking bypasses, often utilizing direct system calls or the manipulation of ntdll.dll memory regions to unhook EDR sensors. Because the code is AI-generated, the obfuscation patterns change with every compilation, making hash-based detection useless.
Encryption-Based C2 & Payloads: Communications and payload staging are wrapped in custom encryption layers. This is intended to frustrate network inspection tools (IDS/IPS) that rely on unencrypted command signatures.
Automated AD Discovery: The toolkit automates the execution of standard discovery binaries (net.exe, whoami.exe, dsquery.exe) but injects these calls via memory-resident techniques to masquerade as legitimate system activity. It maps out the AD structure to identify high-value targets (Domain Admins) for subsequent lateral movement or ransomware deployment.

Exploitation Status:

Confirmed Active Exploitation: Yes, reported in the wild targeting enterprise networks.
CVE Identifiers: None specified (Technique-based attack rather than a specific software vulnerability).

Detection & Response

Given the polymorphic nature of AI-generated malware, detection must rely on behavioral anomalies and the sequence of actions rather than static indicators. We must hunt for the "smoking gun" of automated discovery and the manipulation of memory structures required for EDR unhooking.

SIGMA Rules

YAML

---
title: Potential Automated Active Directory Discovery
id: 8a4f1c2b-3d6e-4f7a-9b1c-2d3e4f5a6b7c
status: experimental
description: Detects rapid sequential execution of Active Directory discovery commands often automated by toolkits.
references:
  - https://attack.mitre.org/techniques/T1018/
author: Security Arsenal
date: 2026/04/18
tags:
  - attack.discovery
  - attack.t1018
  - attack.t1087
logsource:
  category: process_creation
  product: windows
detection:
  selection:
    Image|endswith:
      - '\net.exe'
      - '\net1.exe'
      - '\whoami.exe'
      - '\dsquery.exe'
      - '\nltest.exe'
    CommandLine|contains:
      - 'group'
      - 'user'
      - 'domain'
      - 'trust'
      - 'all'
  condition: selection
falsepositives:
  - Administrative troubleshooting
  - Legitimate IT inventory scripts
level: medium
---
title: Suspicious Process Access via ntdll.dll (EDR Evasion Indicator)
id: 9b5g2d3c-4e7f-5a8b-0c2d-3e4f5a6b7c8d
status: experimental
description: Detects potential EDR unhooking activity by monitoring suspicious access patterns to ntdll.dll memory regions.
references:
  - https://attack.mitre.org/techniques/T1562/001/
author: Security Arsenal
date: 2026/04/18
tags:
  - attack.defense_evasion
  - attack.t1562.001
logsource:
  category: process_access
  product: windows
detection:
  selection:
    TargetImage|endswith: '\ntdll.dll'
    GrantedAccess|contains:
      - '0x10'  # PROCESS_VM_READ
      - '0x20'  # PROCESS_VM_WRITE
      - '0x8'   # PROCESS_CREATE_THREAD
    SourceImage|notcontains:
      - '\Program Files\'
      - '\Windows\System32\'
  condition: selection
falsepositives:
  - Some security software scanning memory
  - Debuggers
level: high

KQL (Microsoft Sentinel / Defender)

This query hunts for the automated discovery patterns characteristic of the toolkit, correlating process execution with network connection initiation.

KQL — Microsoft Sentinel / Defender

// Hunt for automated AD discovery followed by immediate network activity
let DiscoveryProcesses = dynamic(["net.exe", "net1.exe", "whoami.exe", "dsquery.exe", "nltest.exe"]);
DeviceProcessEvents
| where Timestamp > ago(24h)
| where FileName in~ DiscoveryProcesses
| where ProcessCommandLine contains any ("group", "user", "domain", "trust", "config")
| project Timestamp, DeviceName, AccountName, ProcessCommandLine, SHA256
| join kind=inner (
    DeviceNetworkEvents
    | where Timestamp > ago(24h)
    | where RemotePort in (443, 80, 445) or RemotePort >= 8000
) on DeviceName, $left.Timestamp <= $right.Timestamp and $right.Timestamp <= $left.Timestamp + 30s
| summarize Count=count(), NetworkConnections=make_list(RemoteUrl) by DeviceName, AccountName, bin(Timestamp, 5m)
| where Count > 5 // High volume of discovery commands

Velociraptor VQL

This VQL artifact hunts for processes that exhibit RWX (Read-Write-Execute) memory permissions, a common technique used by toolkits to inject shellcode or load decrypted payloads directly into memory.

VQL — Velociraptor

-- Hunt for suspicious memory protections often used by toolkits
SELECT Pid, Name, CommandLine, Username, Exe
FROM pslist()
WHERE Exe NOT IN ("C:\\Windows\\System32\\svchost.exe", "C:\\Windows\\System32\\lsass.exe")
  AND CommandLine =~ "System.Security.Cryptography"
  OR Name =~ "powershell"

-- Correlate with network connections
SELECT Pid, Name, RemoteAddress, RemotePort, State
FROM netstat()
WHERE Pid IN (
    SELECT Pid FROM pslist() WHERE Name =~ "powershell" AND CommandLine =~ "-EncodedCommand"
)

Remediation Script (PowerShell)

This script assists IR teams in identifying unsigned binaries in common drop locations and verifying the integrity of EDR services, which are primary targets for this toolkit.

PowerShell

<#
.SYNOPSIS
    Incident Response Script for AI-Toolkit Detection
.DESCRIPTION
    Scans for unsigned executables in temp directories and verifies EDR service status.
#>

Write-Host "[*] Starting Hunt for AI-Toolkit Artifacts..." -ForegroundColor Cyan

# 1. Check for Unsigned binaries in Temp folders (Common drop location for polymorphic payloads)
Write-Host "[*] Scanning for unsigned binaries in user temp directories..." -ForegroundColor Yellow
$tempPaths = @("$env:TEMP", "$env:PUBLIC\Downloads", "$env:APPDATA\Temp")

foreach ($path in $tempPaths) {
    if (Test-Path $path) {
        Get-ChildItem -Path $path -Filter "*.exe" -Recurse -ErrorAction SilentlyContinue | 
        ForEach-Object {
            $sig = Get-AuthenticodeSignature $_.FullName
            if ($sig.Status -ne "Valid") {
                Write-Host "[!] Suspicious unsigned binary found: $($_.FullName)" -ForegroundColor Red
                Write-Host "    Created: $($_.CreationTime) | SHA256: $((Get-FileHash $_.FullName -Algorithm SHA256).Hash)"
            }
        }
    }
}

# 2. Verify EDR Service Status
Write-Host "[*] Verifying Critical Security Services..." -ForegroundColor Yellow
$edrServices = @("Sense", "WinDefend", "MsMpEng", "WdNisSvc")

foreach ($svc in $edrServices) {
    $service = Get-Service -Name $svc -ErrorAction SilentlyContinue
    if ($service) {
        if ($service.Status -ne "Running") {
            Write-Host "[ALERT] Security Service $svc is not running! Status: $($service.Status)" -ForegroundColor Red
        } else {
            Write-Host "[OK] Security Service $svc is running." -ForegroundColor Green
        }
    }
}

Write-Host "[*] Hunt complete." -ForegroundColor Cyan

Remediation

Immediate containment and eradication are required when this toolkit is detected:

Isolate Hosts: Immediately isolate affected endpoints from the network to prevent the automated AD discovery tools from propagating laterally.
Terminate Malicious Processes: Kill the parent process responsible for the discovery chain. This is often a PowerShell instance or a disguised binary running from a temporary directory.
Block C2 Infrastructure: Identify the encryption-wrapped C2 traffic (usually characterized by high entropy connections to unknown IPs) and block the Indicators of Compromise (IOCs) at the firewall and proxy level.
Reset Credentials: Since the toolkit automates credential dumping and AD discovery, assume all credentials on the compromised host are compromised. Force a password reset for the affected accounts and revoke Kerberos tickets.
Review EDR Logs: specifically for the "Process Access" alerts indicating attempts to unhook ntdll.dll. Use these logs to identify other potentially compromised hosts that may have been scanned but not yet exploited.
Update AI/Heuristic Rules: Work with your EDR vendor to ensure heuristic models are tuned to detect the behavioral patterns of AI-generated code, specifically the rapid chaining of discovery commands and the use of non-standard API calls for encryption.

Related Resources

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