ashen-lepus-dll-sideloading-analysis

name

ashen-lepus-dll-sideloading-analysis

description

Analyze and detect Ashen Lepus (WIRTE) advanced DLL side-loading attacks with HTML-staged payloads. Use this skill whenever investigating suspicious DLL loading patterns, HTML-based C2 staging, or Middle Eastern diplomatic targeting campaigns. Trigger for any analysis of netutils.dll, srvcli.dll, dwampi.dll, wtsapi32.dll, or propsys.dll side-loading, HTML comment-based payload extraction, or Rclone-based exfiltration patterns.

Ashen Lepus DLL Side-Loading Analysis

A skill for analyzing the advanced multi-stage DLL side-loading technique weaponized by Ashen Lepus (aka WIRTE) against Middle Eastern diplomatic networks.

What This Skill Does

This skill helps security analysts:

• Understand the Ashen Lepus multi-stage side-loading chain
• Detect HTML-staged C2 payloads with dynamic tag extraction
• Identify Rclone-based exfiltration patterns
• Generate detection rules for the technique
• Analyze captured traffic for the specific patterns

Attack Chain Overview

Decoy EXE → AshenLoader (DLL sideload) → HTML C2 → AshenStager → 
AshenOrchestrator → Modules (persistence, recon, exfil)

Stage 1: Initial Side-Loading

• Archive-based social engineering delivers EXE + malicious DLL + decoy PDF
• EXE side-loads DLL named after trusted library (netutils.dll, srvcli.dll, dwampi.dll, wtsapi32.dll, propsys.dll)
• AshenLoader performs host recon, encrypts with AES-CTR, POSTs to API-looking paths

Stage 2: HTML Staging

• C2 responds with <headerp>...</headerp> containing Base64/AES-CTR encrypted AshenStager
• Only delivers payload when IP geolocates to target region AND User-Agent matches
• Other clients receive benign HTML (news/health sites)

Stage 3: Second Side-Load

• AshenStager deploys with another legitimate binary importing wtsapi32.dll
• Fetches HTML with <article>...</article> containing AshenOrchestrator

Stage 4: Modular Controller

• AshenOrchestrator decodes Base64 JSON config
• tg + au fields → AES key → decrypts xrk → XOR key for modules
• Modules delivered via HTML comments redirecting to arbitrary tags

HTML Container Parsing Pattern

The technique uses dynamic tag names to evade static detection:

<!-- TAG: <customtag> -->
<customtag>BASE64_PAYLOAD_HERE</customtag>

Extraction logic:

1. Parse HTML comment for tag name: <!-- TAG: <xyz> -->
2. Extract content from <xyz>...</xyz>
3. Base64 decode
4. AES-CTR decrypt with embedded key/nonce
5. XOR with derived key if present

Detection Pivots

Process Monitoring

• Alert on signed processes loading DLLs from user-writable paths
• Focus on DLL names: netutils, srvcli, dwampi, wtsapi32, propsys
• Use: Get-ProcessMitigation -Module + Procmon filters

Network Detection

• HTTPS responses with large Base64 blobs in unusual HTML tags
• HTML comments with <!-- TAG: <xyz> --> pattern
• Base64 strings inside <script> blocks (HTML smuggling variant)
• C2 redirects that only respond to exact User-Agent strings

Persistence Detection

• Scheduled tasks running svchost.exe with non-service arguments:
  • WindowsDefenderUpdate\Windows Defender Updater
  • WindowsServicesUpdate\Windows Services Updater
  • Automatic Windows Update

Exfiltration Detection

• Rclone binaries outside IT-managed locations
• New rclone.conf files pointing to unknown HTTPS endpoints
• Sync jobs from C:\Users\Public\ directories

Scripts

parse_html_staging.py

Extracts payloads from HTML-staged C2 responses using the Ashen Lepus pattern.

generate_detection_rules.py

Generates Sigma/YARA rules for the technique.

Usage Examples

Analyzing a Suspicious HTML Response

Use parse_html_staging.py with the captured HTML to extract any embedded payloads
Check for the <!-- TAG: <xyz> --> comment pattern
Look for Base64 content in unusual tags

Hunting in Your Environment

1. Search for scheduled tasks matching the persistence patterns
2. Monitor for DLL loads from user-writable paths
3. Inspect HTTPS responses for Base64 blobs in HTML
4. Check for Rclone in unexpected locations

Generating Detection Rules

Run generate_detection_rules.py to create:
- Sigma rules for process monitoring
- YARA rules for payload detection
- Network detection patterns

Key Indicators

DLL Names to Watch

• netutils.dll
• srvcli.dll
• dwampi.dll
• wtsapi32.dll
• propsys.dll

C2 Patterns

• Paths: /api/v1/account, /api/v2/account
• Parameters: token=, id=, q=, auth=
• User-Agent pinning (exact match required)
• Geo-fenced responses

HTML Patterns

• <!-- TAG: <xyz> --> comments
• <headerp>, <article>, or dynamic tags with Base64
• Base64 in <script> blocks

Persistence Tasks

• C:\Windows\System32\Tasks\Windows\WindowsDefenderUpdate\
• C:\Windows\System32\Tasks\Windows\WindowsServicesUpdate\
• C:\Windows\System32\Tasks\Automatic Windows Update

References

• Unit42: Ashen Lepus AshTag Malware Suite
• Talos: HTML Smuggling Evasion Techniques
• Check Point: WIRTE 2024 Campaigns
• OWN-CERT: WIRTE Analysis

Important Notes

• This skill is for defensive security analysis only
• The techniques described are for understanding adversary TTPs
• Detection rules should be tested in controlled environments
• Always follow your organization's security policies when investigating