Nivdort

Category: trojan · Aliases: Trojan.Nivdort, Botnet.Bayrob, Win32/Nivdort · Sample count (EMBER 2018): 6 · Enrichment: expert-seo · Updated: 2026-10-15
Category: TrojanStatus: 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 7
Executive Summary
<h3>Executive Summary</h3> Nivdort (also widely tracked as Bayrob) is a highly sophisticated, modular Trojan and botnet client.

Table of Contents

Overview

Executive Summary

Nivdort (also widely tracked as Bayrob) is a highly sophisticated, modular Trojan and botnet client. Initially discovered around 2007 as a specialized tool for intercepting web traffic to steal credit card data and manipulate online auctions (like eBay), it evolved into a massive, multi-purpose botnet capable of spam distribution, credential theft, and cryptocurrency mining. The operators behind the core Bayrob botnet were arrested by the FBI in 2016, but variants of the malware occasionally resurface.

Infection Vector and Technical Capabilities

Nivdort/Bayrob was overwhelmingly distributed via massive, highly targeted spear-phishing campaigns. These emails frequently masqueraded as legitimate invoices or shipping documents from major couriers, containing malicious ZIP attachments that hid the executable payload. Its technical architecture was highly advanced for its time:

Threat Assessment

A Nivdort detection indicates a severe compromise by a highly capable (historically APT-level) threat. The primary threat is financial fraud via intercepted web traffic and the theft of sensitive credentials.

Incident Response and Remediation

Known aliases

Threat reports may refer to this family under multiple names:

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-MFAMulti-factor AuthenticationHardenT1056.001Enforce FIDO2 / WebAuthn physical tokens to render keystroke-intercepted passwords useless.
D3-MitBAMan-in-the-Browser AnalysisDetectT1185Deploy browser extension whitelisting and hardware-backed session binding to prevent rogue DOM and socket injection.
D3-STASecurity Tool Anti-Tamper EnforcementHardenT1562Enable EDR Tamper Protection and Windows Defender Protected Process Light (PPL) to prevent service termination.

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_NIVDORT_T1_ARTIFACT {
    meta:
        description = "Tier 1 Primitive Artifact: Raw string matches for Nivdort"
        tier = "T1 - Primitive Artifact"
        confidence = "Low-Medium (Fast Triage)"
        author = "SystemHelpdesk Threat Research Desk"
        date = "2026-10-14"
    strings:
        $s1 = "nivdort" ascii wide nocase
        $s2 = "trojan.nivdort" ascii wide nocase
        $s3 = "botnet.bayrob" ascii wide nocase
        $s4 = "win32/nivdort" 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 - Nivdort (Trojan) Execution & Triage
id: 3cbd8cb7-d2d7-5517-9ec9-5bc5b1b6418c
status: production
description: Detects execution, defense evasion, and persistence behaviors associated
  with the Nivdort malware family. Detects suspicious execution from temporary user
  directories with hidden window flags and background transfer utilities.
references:
- https://malware-families-catalog.systemhelpdesk.com/families/nivdort
- https://malware-families-catalog.systemhelpdesk.com/defensive/downloader-dropper-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.trojan
- author.ricky-jordan
- source.systemhelpdesk-mfc
- attack.t1562
- attack.t1185
- attack.t1056_001
logsource:
  category: process_creation
  product: windows
detection:
  selection_process:
    Image|endswith:
    - \cmd.exe
    - \powershell.exe
    - \cscript.exe
    - \wscript.exe
    CommandLine|contains:
    - AppData\Local\Temp
    - -WindowStyle Hidden
    - /e:jscript
    - bitsadmin /transfer
  condition: selection_process
falsepositives:
- Legitimate enterprise administrative scripts during approved change windows
- Authorized IT software deployment utilities and backup management agents
level: medium

Tier 3 Attribution Fingerprint Rule (High Fidelity)

Deep signature matching distinctive operational fingerprints and payload characteristics.

rule MALWARE_WIN_NIVDORT_T3_ATTRIBUTION {
    meta:
        description = "Tier 3 Attribution Fingerprint: Heuristic detection for Nivdort 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 = "nivdort" 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. Sever network connectivity for the flagged endpoint to terminate persistent command-and-control (C2) communication channels and stop Nivdort from retrieving secondary stage payloads.
  2. Capture process memory triage to detect and terminate malicious threads injected by Nivdort into legitimate system processes such as explorer.exe or svchost.exe.
  3. Audit Windows Registry Run keys (HKCU\Software\Microsoft\Windows\CurrentVersion\Run) and Task Scheduler entries to locate and purge Nivdort persistence hooks.
  4. Deploy updated enterprise EDR detection signatures and conduct an out-of-band endpoint scan to isolate dropped binaries and staged payloads.
  5. Rotate all credentials, domain user passwords, and session cookies active on the system during the Nivdort execution timeframe.

What to Avoid

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

  1. Do not assume the incident is resolved simply because an antivirus tool removed the initial Nivdort dropper; always verify that secondary payloads and persistence hooks have been eradicated.
  2. Avoid logging in with Domain Admin or privileged credentials on a machine suspected of running Nivdort until memory triage is complete.
  3. Do not delay host isolation; automated lateral movement and credential dumping can occur within minutes of initial execution.

References & External Analysis

Frequently Asked Questions

What is Nivdort (Bayrob) and what are its primary attack objectives?

Nivdort (widely tracked as Bayrob) is a sophisticated Trojan family that emerged around 2007. Its primary operational objectives include harvesting sensitive credentials (banking credentials, credit card details, and email accounts), executing distributed denial-of-service (DDoS) campaigns, and orchestrating large-scale fraudulent online marketplace schemes—most notably injecting fake vehicle auction listings on platforms like eBay.

How does Nivdort distribute itself and trick end users?

Nivdort relies heavily on high-volume malicious spam (malspam) campaigns delivering malicious ZIP or RAR attachments containing double-extension executables (e.g., invoice.pdf.exe) or weaponized Microsoft Office macros. Furthermore, threat actors established rogue websites mimicking legitimate escrow services and vehicle inspection portals to convince victims to download malicious escrow software.

What credential harvesting and browser manipulation techniques does Nivdort employ?

Nivdort performs Man-in-the-Browser (MitB) attacks by hooking Windows networking APIs and browser processes. When an infected user navigates to targeted banking or e-commerce websites, Nivdort intercepts the traffic, suppresses security alerts, and displays fabricated payment forms or fake customer verification screens to harvest authentication credentials and credit card numbers.

How did the Nivdort botnet structure its command and control (C2) communication?

The Nivdort botnet utilized a multi-tier proxy infrastructure to obscure backend C2 servers. Compromised bots communicated with intermediate proxy nodes over encrypted TCP channels, using proprietary XOR or RC4 encryption to conceal instructions. The botnet also integrated domain generation algorithms (DGA) to rotate rendezvous endpoints when primary nodes were seized.

How can enterprise networks detect and eradicate Nivdort infections?

Enterprise defenders should employ behavioral EDR detection against unauthorized registry Run key additions (HKCU\Software\Microsoft\Windows\CurrentVersion\Run) and process injection into svchost.exe or explorer.exe. Network monitoring should flag anomalous high-frequency outbound TCP connections to unclassified IP addresses. Remediation requires isolating compromised endpoints, terminating injected host processes, removing persistence registry entries, and resetting all cached user credentials.

How do I remove the Nivdort Trojan from Windows?

Manual removal of Nivdort 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 Nivdort a virus or a Trojan?

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

What are the main symptoms of a Nivdort infection?

Symptoms of Nivdort 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 Trojans

Want to prevent Nivdort and similar threats from compromising your organization? Read our comprehensive defensive guide: Banking Trojan Protection for Businesses.

📣 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/nivdort.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.