Blackenergy
Table of Contents
Overview
BlackEnergy is an advanced, modular persistent threat (APT) framework originally authored in 2007 by Ukrainian hacker Dmytro Oleksiuk (alias 'Cr4sh') as an underground HTTP-based distributed denial-of-service (DDoS) botnet. Between 2010 and 2014, the codebase was heavily overhauled and co-opted by Russian state-sponsored threat actors—specifically the Russian General Staff Main Intelligence Directorate (GRU) Unit 74455 and Unit 26165, collectively tracked worldwide as Sandworm Team (TeleBots, Voodoo Bear). Under Sandworm development, BlackEnergy 2 and BlackEnergy 3 evolved into a multi-tiered cyber espionage and industrial sabotaging platform. The framework utilized rootkit drivers, modular DLL payloads, and specialized industrial control system (ICS/SCADA) plugins targeting serial-to-ethernet converters and Human-Machine Interface (HMI) workstations. On December 23, 2015, Sandworm deployed BlackEnergy 3 alongside the destructive KillDisk wiper component against Ukraine's electricity distribution grid (Kyivoblenergo), severing power to approximately 230,000 citizens in the world's first publicly acknowledged electrical blackout triggered by a cyber weapon. BlackEnergy was subsequently highlighted in the October 2020 US Department of Justice indictment charging six GRU Unit 74455 officers with global cyber intrusions.
Known aliases
Threat reports may refer to this family under multiple names:
Threat Actor Attribution
Attribution is probabilistic, not a science. Each link below states its confidence level and the evidence behind it.
- Russian GRU Unit 74455 (Sandworm Team / TeleBots) / Dmytro Oleksiuk (Cr4sh) High confidence
Basis: US Department of Justice October 2020 federal indictment of six GRU military officers for Sandworm cyberattacks, corroborated by US CISA, FBI, and Ukrainian CERT (CERT-UA) alerts identifying BlackEnergy in the 2015 Ukrainian power grid blackout. [source]
Family Pedigree & Lineage
Malware authors regularly fork and iterate upon existing codebases. Observed upstream lineage and downstream variants for this family include:
Known Derivatives & Downstream Variants: Blackenergy V1 (Ddos) · Blackenergy V2 (Rootkit) · Blackenergy V3 (Ics/Scada) · Killdisk Wiper Module
MITRE ATT&CK Techniques
Observed techniques used by this family, mapped to our technical analysis hubs and the official MITRE ATT&CK framework:
| Technique | Name | Tactic | Official Spec |
|---|---|---|---|
T1055 | Process Injection | Defense Evasion | ATT&CK ↗ |
T1059.003 | Command and Scripting Interpreter: Windows Command Shell | Execution | ATT&CK ↗ |
T1562.001 | Impair Defenses: Disable or Modify Tools | Defense Evasion | ATT&CK ↗ |
T1485 | Data Destruction | Impact | ATT&CK ↗ |
T1071.001 | Application Layer Protocol: Web Protocols (C2 Communication) | Command and Control | ATT&CK ↗ |
T1082 | System Information Discovery | Discovery | ATT&CK ↗ |
Tactical Mitigations
Based on the techniques used by this family, consider the following defensive strategies:
- T1059.003: Restrict execution of Windows Command Shell (cmd.exe) and block unauthorized batch scripts.
- T1071.001: Implement web filtering and SSL/TLS inspection to detect malicious command and control (C2) traffic hiding in HTTP/HTTPS.
MITRE D3FEND™ Defensive Countermeasures
Defensive techniques mapped to counter the offensive tradecraft observed in this family (via the MITRE D3FEND matrix):
| D3FEND ID | Countermeasure Name | Tactic | Countered ATT&CK | Defensive Guidance |
|---|---|---|---|---|
D3-PIAD | Process Injection Analysis & Detection | Detect | T1055 | Monitor cross-process thread creation (CreateRemoteThread) and asynchronous procedure calls (QueueUserAPC). |
D3-PBA | Process Spawn Analysis | Detect | T1059.003 | Inspect command-line arguments and anomalous parent-child relationships spawning from cmd.exe. |
D3-WAF | Web Content Filtering & Inspection | Filter | T1071.001 | Block newly registered domains (NRDs) and inspect HTTP Host and URI headers for known C2 profiles. |
D3-SDA | System Discovery Analysis | Detect | T1082 | Alert on rapid enumerations of systeminfo, hostname, and registry hardware trees in short intervals. |
D3-WORM | Immutable Backup Storage | Harden | T1485 | Store primary backups in Write-Once-Read-Many (WORM) cloud repositories protected by multi-party out-of-band credentials. |
D3-STA | Security Tool Anti-Tamper Enforcement | Harden | T1562.001 | Block unauthorized modification of antivirus registry flags and prevent stopping security agent services. |
Exploited Vulnerabilities (CVEs)
This malware family is documented weaponizing the following common vulnerabilities and exposures:
- CVE-2014-4114 — In-depth exploitation analysis and catalog intelligence (NIST NVD ↗).
Command & Control (C2) and Network Profile
How this family talks to its operators. C2 traffic can often identify a family even when its code and configuration are hard to analyse. Ports and patterns are historical and change between campaigns, so use them as hunting leads rather than block-only rules.
| Protocols | HTTP, HTTPS, TCP, Base64 Encoded POST |
|---|---|
| Observed ports | 80, 443, 8080 |
| Infrastructure model | Multi-tiered proxy servers hosted across compromised routers and bulletproof VPS providers transmitting encrypted Base64 and XOR-encoded XML/JSON payloads to modular DLL loaders. |
| Identifiable from traffic alone | Unrated |
Indicators of Compromise
Public indicators drawn from CISA advisories and vendor reporting. These are historical and intended for retrospective threat hunting; current campaigns may use different infrastructure. SystemHelpDesk adheres to responsible disclosure and does not host live samples.
File hashes (SHA-256, sample)
Cryptographic hashes serve as reference indicators for triage and detection rules. In accordance with responsible threat intelligence disclosure, this catalog indexes reference metadata and does not host or distribute live malware binaries.
0f62d1c9ad9a64797a731efc1b4cfb0cc5a1b5d12de1d668749a46995642456e294ac5e533c37560d2b8feeb492f58cfcb6c3c6efec24bb93b22cfd8ccb05612
Delivery vectors
Spear-phishing emails containing malicious Microsoft PowerPoint (.pps/.ppt) documents weaponized with CVE-2014-4114Phishing emails disguised as official Ukrainian energy authority communications delivering weaponized macro-enabled Excel sheets
Persistence mechanisms
Kernel-mode rootkit drivers installed in %SYSTEM32%\driversScheduled Tasks executing rundll32.exe with encrypted configuration files in %APPDATA%
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_BLACKENERGY_T1_ARTIFACT {
meta:
description = "Tier 1 Primitive Artifact: Raw string matches for Blackenergy"
tier = "T1 - Primitive Artifact"
confidence = "Low-Medium (Fast Triage)"
author = "SystemHelpdesk Threat Research Desk"
date = "2026-10-14"
strings:
$s1 = "blackenergy" ascii wide nocase
$s2 = "blackenergy" ascii wide nocase
$s3 = "blackenergy 2" ascii wide nocase
$s4 = "blackenergy 3" ascii wide nocase
$s5 = "sandworm toolkit" ascii wide nocase
$s6 = "win32/blackenergy" ascii wide nocase
$s7 = "backdoor.blackenergy" 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 - Blackenergy (Advanced Threat) Execution & Triage
id: 6226fa75-1e9c-540d-8db9-19039cd43bbe
status: production
description: Detects execution, defense evasion, and persistence behaviors associated
with the Blackenergy 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/blackenergy
- 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.t1055
- attack.t1059_003
- attack.t1562_001
- attack.t1485
- attack.t1071_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_BLACKENERGY_T3_ATTRIBUTION {
meta:
description = "Tier 3 Attribution Fingerprint: Heuristic detection for Blackenergy 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 = "blackenergy" 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
}
Containment & Response Steps
Ordered checklist for responders. Adapt to your environment and engage professional support for active incidents.
- Enforce forensic network isolation on all suspected endpoints while maintaining an out-of-band telemetry conduit to capture live Blackenergy adversary activity.
- Perform full memory dumps across identified staging nodes to extract memory-only implants, kernel rootkit hooks, and decrypted Blackenergy C2 infrastructure IP/domain lists.
- Review Active Directory domain controller authentication logs for anomalous Kerberos ticket requests (Pass-the-Ticket, Golden Ticket) and unauthorized DCSync operations associated with Blackenergy.
- Block all confirmed C2 domains, dynamic DNS endpoints, and proxy IP addresses across perimeter firewalls, proxies, and DNS security gateways.
- Conduct an enterprise-wide sweep across surrounding subnets for secondary webshells, WMI event subscriptions, or remote execution tooling left behind by Blackenergy operators.
What to Avoid
Common mistakes during response to this family that can destroy evidence, spread the infection, or worsen recovery.
- Do not assume the incident is resolved simply because an antivirus tool removed the initial Blackenergy dropper; always verify that secondary payloads and persistence hooks have been eradicated.
- Avoid logging in with Domain Admin or privileged credentials on a machine suspected of running Blackenergy until memory triage is complete.
- Do not delay host isolation; automated lateral movement and credential dumping can occur within minutes of initial execution.
References & External Analysis
- US DOJ Indictment of Six Russian GRU Officers
- CISA Advisory - Cyber-Attack Against Ukrainian Critical Infrastructure
- MITRE ATT&CK - BlackEnergy (S0089)
- Search "blackenergy" on VirusTotal (External Analysis)
- Search "blackenergy" on Any.Run (Sandbox Sandbox)
- Search "blackenergy" on MalwareBazaar (Malware Samples)
Frequently Asked Questions
What is BlackEnergy malware?
BlackEnergy is a sophisticated Russian state-sponsored cyber espionage and sabotage framework famous for its role in the historic December 2015 cyberattack on Ukraine's power grid.
Who operates BlackEnergy?
Originally created as a DDoS tool in 2007 by Dmytro Oleksiuk, it was weaponized and operated by the Russian GRU Unit 74455 (Sandworm Team), who were federally indicted by the US DOJ in 2020.
How was BlackEnergy used in the 2015 Ukraine electrical blackout?
Sandworm deployed BlackEnergy 3 to compromise regional electricity distribution workstations, sever power substations remotely, and execute the KillDisk wiper to destroy master boot records and hinder recovery.
What vulnerability did BlackEnergy exploit for initial access?
BlackEnergy campaigns extensively exploited CVE-2014-4114 (the 'Sandworm' vulnerability), a remote code execution flaw in Microsoft Windows OLE package handling.
How can industrial networks defend against BlackEnergy-style intrusions?
Enforce strict network segmentation between IT and OT/SCADA environments, require multi-factor authentication on all remote VPN access, and deploy endpoint application whitelisting on HMI stations.
How do I remove Blackenergy from Windows?
Manual removal of Blackenergy 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 Blackenergy a virus or an Advanced Threat?
Blackenergy is classified as an Advanced Threat. Unlike traditional viruses that infect files, modern malware like Blackenergy typically operates as a standalone payload designed to compromise systems, steal data, or deploy secondary stage implants.
What are the main symptoms of a Blackenergy infection?
Symptoms of Blackenergy 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 Blackenergy 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.
Machine-readable
Get this profile as JSON: https://malware-families-catalog.systemhelpdesk.com/api/blackenergy.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.