Slenfbot

Category: advanced_threat · Aliases: None known · Sample count (EMBER 2018): 2 · Enrichment: expert-seo · Updated: 2026-06-09
Category: Advanced_ThreatStatus: Automated SignaturePlatform: WINDOWS_PEStage: Execution, PersistenceActor: Unknown / CybercriminalIndustry: Global / OpportunisticMotivation: Opportunistic🕸 Explore Relationship Graph⚙ API JSON⚡ Sigma Rule💾 YARA RuleOS: Windows 11, Windows 10, Windows Server 2022
Executive Summary
Worm:Win32/Slenfbot is a highly infectious network worm and botnet agent notorious for its aggressive self-propagation methods.

Table of Contents

Overview

Worm:Win32/Slenfbot is a highly infectious network worm and botnet agent notorious for its aggressive self-propagation methods. Once executed on a host, it immediately attempts to replicate itself across the local network and to any connected removable media (USB drives), while simultaneously connecting the infected machine to a central IRC-based Command and Control (C2) botnet for further instructions, such as launching DDoS attacks or downloading additional malware.

Understanding Slenfbot (USB Worms/Botnets)
To an end-user, the infection might be unnoticeable until their network connection slows to a crawl due to DDoS activity or aggressive scanning. For a security administrator, a Slenfbot outbreak is a severe incident that can rapidly paralyze a corporate network. It exploits the human tendency to share files via USB (`T1091`) and weak network share permissions (`T1021.002`).

Execution and Propagation Mechanics
Slenfbot is most commonly introduced into an environment via an infected USB drive. It relies on the Windows `autorun.inf` feature (or tricks the user into clicking a disguised executable) to launch (`T1204.002`). Upon execution, it copies itself to the Windows system folder and establishes persistence via the Registry Run keys. Crucially, it immediately begins polling for new USB drives; when one is inserted, it silently copies itself and a malicious `autorun.inf` to the drive. Simultaneously, it connects to an IRC server (`T1071.002`) to join the botnet, awaiting commands from the botmaster.

Indicators of Compromise & Impact
The impact is rapid, widespread infection and potential involvement in coordinated botnet attacks. Host-based IoCs include the presence of malicious `.exe` or `.vbs` files and hidden `autorun.inf` files on the root directory of all attached USB drives. EDR will detect the creation of autostart registry keys pointing to executables in the `System32` directory. Network IoCs are highly visible: unauthorized IRC traffic (often TCP ports 6667-6669) connecting to unknown domains, and massive internal network scanning (SMB/Port 445) as the worm attempts lateral movement.

MITRE ATT&CK Techniques

Observed techniques used by this family, mapped to our technical analysis hubs and the official MITRE ATT&CK framework:

→ Explore the complete 226-Technique ATT&CK Threat Matrix

Tactical Mitigations

Based on the techniques used by this family, consider the following defensive strategies:

MITRE D3FEND™ Defensive Countermeasures

Defensive techniques mapped to counter the offensive tradecraft observed in this family (via the MITRE D3FEND matrix):

D3FEND IDCountermeasure NameTacticCountered ATT&CKDefensive Guidance
D3-ALPAApplication Layer Protocol AnalysisDetectT1071.002Fingerprint application traffic structures and enforce TLS inspection for external outbound sessions.
D3-RMCRemovable Media Access ControlHardenT1091Enforce Group Policy settings disabling Windows autorun and block execution permissions on removable USB storage media.
D3-RPMRegistry Persistence MonitoringDetectT1547.001Audit and restrict write privileges to user and machine-level Registry Run/RunOnce keys using Endpoint Privilege Management.

Tiered Detection Rules (Cisco CAIRN Model)

Modern threat detection requires multi-layered rule engineering. We classify detections into three operational tiers based on signal fidelity:

Tier 1 Primitive Artifact Rule (Fast Triage)

Matches raw strings and file markers. Vulnerable to binary repacking and simple obfuscation.

rule MALWARE_WIN_SLENFBOT_T1_ARTIFACT {
    meta:
        description = "Tier 1 Primitive Artifact: Raw string matches for Slenfbot"
        tier = "T1 - Primitive Artifact"
        confidence = "Low-Medium (Fast Triage)"
        author = "SystemHelpdesk Threat Research Desk"
        date = "2026-10-14"
    strings:
        $s1 = "slenfbot" ascii wide nocase
    condition:
        uint16(0) == 0x5a4d and any of them
}

Tier 2 Behavioral Context Rule (Process Chains & Sigma)

Tracks parent-child process anomalies and suspicious scripting telemetry. Resilient against file renames.

title: SystemHelpDesk Detection - Slenfbot (Advanced Threat) Execution & Triage
id: e413b3a9-3d02-5a80-861c-410b8b469b14
status: production
description: Detects execution, defense evasion, and persistence behaviors associated
  with the Slenfbot malware family. Detects proxy execution, reflective DLL loading,
  and remote command injection associated with modular enterprise backdoors.
references:
- https://malware-families-catalog.systemhelpdesk.com/families/slenfbot
- https://malware-families-catalog.systemhelpdesk.com/defensive/backdoor-rat-protection
- https://malware-families-catalog.systemhelpdesk.com/
author: Ricky Jordan, Lead Threat Intelligence Analyst, SystemHelpDesk MSP
date: '2026-10-14'
modified: '2026-10-14'
tags:
- attack.advanced-threat
- author.ricky-jordan
- source.systemhelpdesk-mfc
- attack.t1091
- attack.t1071_002
- attack.t1547_001
logsource:
  category: process_creation
  product: windows
detection:
  selection_process:
    Image|endswith:
    - \powershell.exe
    - \cmd.exe
    - \rundll32.exe
    - \regsvr32.exe
    CommandLine|contains:
    - DownloadString
    - IEX(
    - '/s /n /u /i:'
    - sc create
    - start-process
  condition: selection_process
falsepositives:
- Legitimate enterprise administrative scripts during approved change windows
- Authorized IT software deployment utilities and backup management agents
level: high

Tier 3 Attribution Fingerprint Rule (High Fidelity)

Deep signature matching distinctive operational fingerprints and payload characteristics.

rule MALWARE_WIN_SLENFBOT_T3_ATTRIBUTION {
    meta:
        description = "Tier 3 Attribution Fingerprint: Heuristic detection for Slenfbot tradecraft"
        tier = "T3 - Attribution Fingerprint"
        confidence = "High (Confirmed Family Signature)"
        author = "SystemHelpdesk Threat Research Desk"
        date = "2026-10-14"
    strings:
        // Core family identifier & heuristic payload signatures
        $attrib_str = "slenfbot" ascii wide nocase
        $pe_magic = "MZ" ascii
        $net_marker = "http" ascii nocase
    condition:
        uint16(0) == 0x5a4d and ($attrib_str and $net_marker) and filesize < 15MB
}
SOC & SIEM Rule Downloads: ⬇ Download YARA Rule (.yar) ⬇ Download Sigma Rule (YAML) ⬇ Download Sigma Rule (JSON) ⚙ Threat Profile API (JSON)

Containment & Response Steps

Home Users: If you suspect a malware infection on your personal device, disconnect from the internet immediately and run a full system scan with your antivirus software (see our TotalAV Antivirus & Security Support Guide). The steps below are intended for IT professionals responding to enterprise incidents.

Ordered checklist for responders. Adapt to your environment and engage professional support for active incidents.

  1. Immediately disable the 'Autorun' and 'Autoplay' features across the entire enterprise via Group Policy to halt USB-based propagation.
  2. Isolate infected machines from the network to prevent them from participating in botnet activities (like DDoS) or spreading laterally via SMB.
  3. Block known IRC ports (6667-6669) at the perimeter firewall to sever the C2 connection for all infected bots.
  4. Mandate a physical sweep and format of all unapproved USB flash drives used within the organization.

What to Avoid

Common mistakes during response to this family that can destroy evidence, spread the infection, or worsen recovery.

  1. Do not insert a suspected infected USB drive into an unprotected machine for analysis without disabling Autorun first.
  2. Avoid assuming a single cleaned machine means the incident is over; worms propagate rapidly, and other infected machines will simply re-infect it.

References & External Analysis

Frequently Asked Questions

What is Slenfbot and what threat category does it belong to?

Slenfbot is classified as a Advanced Threat. Documented across security telemetry, it is engineered to execute unauthorized operations, establish persistent footholds on target endpoints, and facilitate malicious campaigns targeting enterprise and individual environments.

How does Slenfbot establish persistence and evade defensive controls?

Slenfbot typically establishes persistence through registry run keys, scheduled tasks, or service installations, while evading signature-based antivirus solutions through code obfuscation, memory injection, or anti-analysis sandbox checks.

What are the essential incident response steps for mitigating a Slenfbot compromise?

Security teams responding to Slenfbot should immediately isolate affected endpoints from the network, perform memory triage to capture volatile forensic artifacts, audit registry and startup persistence mechanisms, revoke exposed user credentials, and restore systems from verified, clean backups.

What lateral movement and credential access tactics does Slenfbot leverage in enterprise intrusions?

Slenfbot frequently utilizes privileged account harvesting techniques such as LSASS memory dumping, Kerberoasting, and token impersonation to escalate privileges. Once administrative credentials are acquired, it pivots across the victim network utilizing living-off-the-land binaries (LOLBins) such as WMI, PowerShell remoting, and PsExec, or abuses remote desktop protocols (RDP) to reach critical internal repositories and domain controllers.

How does Slenfbot maintain covert communications and evade perimeter network monitoring?

Slenfbot often relies on multi-stage command and control (C2) architectures utilizing encrypted protocols over standard web ports (HTTPS/443 or DNS tunneling) to blend in with legitimate enterprise network traffic. Many variants incorporate proxy networks, domain fronting, or cloud services (such as Microsoft Graph API, Google Drive, or Telegram) to masquerade C2 channels, bypassing traditional signature-based egress filtering.

How do I remove the Slenfbot Advanced_Threat from Windows?

Manual removal of Slenfbot is highly discouraged as it may leave persistence mechanisms intact. We recommend disconnecting the device from the internet and utilizing a professional incident response service or enterprise-grade EDR software to conduct a full forensic sweep.

Is Slenfbot a virus or a Advanced_Threat?

Slenfbot is classified as a Advanced_Threat. Unlike traditional viruses that infect files, modern malware like Slenfbot typically operates as a standalone payload designed to compromise systems, steal data, or deploy secondary stage implants.

What are the main symptoms of a Slenfbot infection?

Symptoms of Slenfbot can include unexpected system slowness, unauthorized outbound network traffic to unknown IP addresses, disabled security software, and suspicious background processes running from AppData or Temp directories.

Protect Your Network Against Advanced_Threats

Want to prevent Slenfbot and similar threats from compromising your organization? Read our comprehensive defensive guide: Think You've Been Hacked? What To Do First.

📣 Threat Intel Correction or Update?

Notice an outdated IOC, unlisted alias, or disputed attribution? Threat researchers are invited to propose an update on GitHub or contact the SystemHelpDesk research desk. All community revisions are credited in our public CHANGELOG.

Need help with an active incident? Published by the SystemHelpdesk team.

Machine-readable

Get this profile as JSON: https://malware-families-catalog.systemhelpdesk.com/api/slenfbot.json

Ecosystem & Interactive Environments

This profile is part of the Malware Families Catalog, a public dataset of 2,899 malware families. The catalog is also published across our ecosystem: Hugging Face, Kaggle, Zenodo, Replit, StackBlitz, CodeSandbox, and CodePen.