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MITRE ATT&CK® Technique

T1048.003: Exfiltration Over Unencrypted Non-C2 Protocol

Adversaries may steal data by exfiltrating it over an un-encrypted network protocol other than that of the existing command and control channel. The data may also be sent to an alternate network location from the main command and control server.[1]

Adversaries may opt to obfuscate this data, without the use of encryption, within network protocols that are natively unencrypted (such as HTTP, FTP, or DNS). This may include custom or publicly available encoding/compression algorithms (such as base64) as well as embedding data within protocol headers and fields.

EnterpriseT1048.003Sub-techniqueObject v2.2 Modified
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Glexia's Take

Analyst context for executives and security teams

Analyst confidence Medium

This technique matters because data theft may leave the environment over ordinary, unencrypted protocols that are not the attacker’s main command-and-control channel. For leaders, the risk is not just “malware traffic”; it is whether the organization can prove that outbound HTTP, FTP, DNS, and similar traffic is governed, inspected, and explainable across Windows, Linux, macOS, ESXi, and network devices.

Executive priority

Prioritize this where sensitive data, regulated records, payment data, government information, operational technology dependencies, or critical infrastructure communications could be exposed through weak egress control. ATT&CK relationships show this behavior is associated with multiple groups, campaigns, and tools, so leadership should ask whether outbound traffic policy, DLP, network segmentation, and incident response playbooks can distinguish legitimate business transfer from suspicious unencrypted exfiltration.

Technical view

SOC and IR teams should validate visibility into outbound non-C2 protocols used for data movement, especially HTTP, FTP, and DNS, and look for abnormal volumes, destinations, headers, fields, encoding, or compression patterns that do not match expected business use. Because official ATT&CK detection text is not provided, coverage should be mapped to DET0149 and tested against the local environment’s real protocol usage. Pay special attention to built-in or common utilities such as ftp and BITSAdmin where relationships indicate possible use, and to network devices where alternate network locations and copy-style operations may be relevant.

Likely telemetry

  • Firewall, proxy, and egress filtering logs for outbound HTTP, FTP, DNS, and other unencrypted protocols
  • DNS query logs, including volume, length, domain patterns, and unusual field usage
  • FTP server/client logs and file transfer metadata
  • Network flow records showing unusual outbound volume, frequency, destination, or protocol use
  • Endpoint process and command-line telemetry tied to network connections

Detection direction

  • Baseline legitimate outbound unencrypted protocol use by business function, system type, and destination before alerting on volume alone.
  • Tune detections for data staging followed by outbound transfer over a protocol different from known command-and-control traffic.
  • Inspect for obfuscation without encryption, such as base64-like content, compression, or data embedded in protocol headers and fields.
  • Correlate endpoint process execution with network egress so normal services are not confused with unusual user- or malware-driven transfer activity.
  • Include network devices, ESXi, Linux, macOS, and Windows in coverage validation; do not assume endpoint-only telemetry is sufficient.

Mitigation priorities

  • Start with egress filtering: restrict outbound protocols and destinations to approved business need, consistent with Filter Network Traffic.
  • Use Network Segmentation to limit which systems can reach external networks and to reduce access from sensitive segments to broad outbound paths.
  • Apply Network Intrusion Prevention at network boundaries where signatures or protocol controls can block suspicious transfers.
  • Deploy or tune Data Loss Prevention for sensitive data types, including PII, intellectual property, financial data, and other regulated content.
  • Review legitimate FTP, DNS, HTTP, and network-device file transfer use cases so controls do not break operations while still producing audit evidence.
Analyst notes and limits

This is a sub-technique of T1048, Exfiltration Over Alternative Protocol. The key decision point is whether the organization can observe and control data leaving over unencrypted protocols that may look operationally normal. Relationship context includes campaigns, groups, and software that use the technique, plus mitigations M1030, M1031, M1037, and M1057.

Official ATT&CK detection text is not provided for this object. The take is based only on the supplied ATT&CK description, platforms, external references, and relationships; actual exposure and detection quality require local network architecture, data classification, logging, and approved traffic baselines.

Official MITRE ATT&CK definition

Exfiltration Over Unencrypted Non-C2 Protocol

Adversaries may steal data by exfiltrating it over an un-encrypted network protocol other than that of the existing command and control channel. The data may also be sent to an alternate network location from the main command and control server.[1]

Adversaries may opt to obfuscate this data, without the use of encryption, within network protocols that are natively unencrypted (such as HTTP, FTP, or DNS). This may include custom or publicly available encoding/compression algorithms (such as base64) as well as embedding data within protocol headers and fields.

View the same entry on attack.mitre.org (MITRE-hosted reference; in-page links above use the Glexia ATT&CK library.)

Glexia analysis

How security teams should use this page

Treat this object as behavior context, not an attribution claim. Validate the related groups, software, data sources, and mitigations against official ATT&CK relationships and your own telemetry before making control-coverage decisions.

ATT&CK relationship table

Related techniques

This mirrors the MITRE pattern of making group, software, campaign, and technique relationships scannable. Relationship notes come from mirrored ATT&CK relationship text when available.

1 rows
Domain ID Name Relationship / procedure
Enterprise T1048 Exfiltration Over Alternative Protocol This object subtechnique of Exfiltration Over Alternative Protocol.
Associated objects

Groups, software, and campaigns

Group Enterprise

G0032: Lazarus Group

Lazarus Group is a North Korean state-sponsored cyber threat group attributed to the Reconnaissance General Bureau (RGB). [1] [2] Lazarus Group has been active since at least 2009 and is reportedly responsible for the November 2014 destructive wiper attack on Sony Pictures Entertainment, identified by Novetta as part of Operation Blockbuster. Malware used by Lazarus Group correlates to other reported campaigns, including Operation Flame, Operation 1Mission, Operation Troy, DarkSeoul, and Ten Days of Rain.[3]

North Korea’s cyber operations have shown a consistent pattern of adaptation, forming and reorganizing units as national priorities shift. These units frequently share personnel, infrastructure, malware, and tradecraft, making it difficult to attribute specific operations with high confidence. Public reporting often uses “Lazarus Group” as an umbrella term for multiple North Korean cyber operators conducting espionage, destructive attacks, and financially motivated campaigns.[4][5][6]

Group Enterprise

G0061: FIN8

FIN8 is a financially motivated threat group that has been active since at least January 2016, and known for targeting organizations in the hospitality, retail, entertainment, insurance, technology, chemical, and financial sectors. In June 2021, security researchers detected FIN8 switching from targeting point-of-sale (POS) devices to distributing a number of ransomware variants.[1][2][3][4]

Group Enterprise

G0076: Thrip

Thrip is an espionage group that has targeted satellite communications, telecoms, and defense contractor companies in the U.S. and Southeast Asia. The group uses custom malware as well as "living off the land" techniques. [1]

Group Enterprise

G0050: APT32

APT32 is a suspected Vietnam-based threat group that has been active since at least 2014. The group has targeted multiple private sector industries as well as foreign governments, dissidents, and journalists with a strong focus on Southeast Asian countries like Vietnam, the Philippines, Laos, and Cambodia. They have extensively used strategic web compromises to compromise victims.[1][2][3]

Group Enterprise

G1045: Salt Typhoon

Salt Typhoon is a People's Republic of China (PRC) state-backed actor that has been active since at least 2019 and responsible for numerous compromises of network infrastructure at major U.S. telecommunication and internet service providers (ISP).[1][2]

Group Enterprise

G0129: Mustang Panda

Mustang Panda is a China-based cyber espionage threat actor that has been conducting operations since at least 2012. Mustang Panda has been known to use tailored phishing lures and decoy documents to deliver malicious payloads. Mustang Panda has targeted government, diplomatic, and non-governmental organizations, including think tanks, religious institutions, and research entities, across the United States, Europe, and Asia, with notable activity in Russia, Mongolia, Myanmar, Pakistan, and Vietnam. [1][2][3][4][5][6][7][8][9][10][11][12][13]

Group Enterprise

G0102: Wizard Spider

Wizard Spider is a Russia-based financially motivated threat group originally known for the creation and deployment of TrickBot since at least 2016. Wizard Spider possesses a diverse arsenal of tools and has conducted ransomware campaigns against a variety of organizations, ranging from major corporations to hospitals.[1][2][3]

Group Enterprise

G0049: OilRig

OilRig is a suspected Iranian threat group that has targeted Middle Eastern and international victims since at least 2014. The group has targeted a variety of sectors, including financial, government, energy, chemical, and telecommunications. It appears the group carries out supply chain attacks, leveraging the trust relationship between organizations to attack their primary targets. The group works on behalf of the Iranian government based on infrastructure details that contain references to Iran, use of Iranian infrastructure, and targeting that aligns with nation-state interests.[1][2][3][4][5][6][7]

Group Enterprise

G0064: APT33

APT33 is a suspected Iranian threat group that has carried out operations since at least 2013. The group has targeted organizations across multiple industries in the United States, Saudi Arabia, and South Korea, with a particular interest in the aviation and energy sectors.[1][2]

Group Enterprise

G0037: FIN6

FIN6 is a cyber crime group that has stolen payment card data and sold it for profit on underground marketplaces. This group has aggressively targeted and compromised point of sale (PoS) systems in the hospitality and retail sectors.[1][2]

Malware Enterprise

S0125: Remsec

Remsec is a modular backdoor that has been used by Strider and appears to have been designed primarily for espionage purposes. Many of its modules are written in Lua. [1]

Windows
Malware Enterprise

S0492: CookieMiner

CookieMiner is mac-based malware that targets information associated with cryptocurrency exchanges as well as enabling cryptocurrency mining on the victim system itself. It was first discovered in the wild in 2019.[1]

macOS
Malware Enterprise

S1043: ccf32

ccf32 is data collection malware that has been used since at least February 2019, most notably during the FunnyDream campaign; there is also a similar x64 version.[1]

Windows
Malware Enterprise

S1116: WARPWIRE

WARPWIRE is a Javascript credential stealer that targets plaintext passwords and usernames for exfiltration that was used during Cutting Edge to target Ivanti Connect Secure VPNs.[1][2]

Network Devices
Malware Enterprise

S0356: KONNI

KONNI is a remote access tool that security researchers assess has been used by North Korean cyber actors since at least 2014. KONNI has significant code overlap with the NOKKI malware family, and has been linked to several suspected North Korean campaigns targeting political organizations in Russia, East Asia, Europe and the Middle East; there is some evidence potentially linking KONNI to APT37.[1][2][3][4][5]

Windows
Malware Enterprise

S0428: PoetRAT

PoetRAT is a remote access trojan (RAT) that was first identified in April 2020. PoetRAT has been used in multiple campaigns against the private and public sectors in Azerbaijan, including ICS and SCADA systems in the energy sector. The STIBNITE activity group has been observed using the malware. PoetRAT derived its name from references in the code to poet William Shakespeare. [1][2][3]

Windows
Malware Enterprise

S0335: Carbon

Carbon is a sophisticated, second-stage backdoor and framework that can be used to steal sensitive information from victims. Carbon has been selectively used by Turla to target government and foreign affairs-related organizations in Central Asia.[1][2]

Windows
Campaign Enterprise

C0063: 2025 Poland Wiper Attacks

2025 Poland Wiper Attacks is a Russian state-sponsored campaign that conducted destructive cyberattacks against Polish energy infrastructure in December 2025. Targets included more than 30 wind and photovoltaic farms, a combined heat and power (CHP) plant, and a manufacturing sector company. The attacks on the distributed energy resources (DER) disrupted communications between affected facilities and the distribution system operator, but did not impact electricity generation or heat supply. Across the campaign, threat actors deployed two previously undocumented wiper tools, DynoWiper, a Windows-based wiper and LazyWiper, a PowerShell wiper, distributed via malicious Group Policy Objects. At the CHP plant, threat actors had maintained access since at least March 2025, using that foothold to obtain credentials and move laterally before attempting wiper deployment. Some reporting has assessed the activity to be consistent with Russian Federal Security Service (FSB) threat activity group Dragonfly, also tracked as STATIC TUNDRA, while other reporting attributes the destructive wiper activities to the Russian General Staff Main Intelligence Directorate (GRU) threat activity group ELECTRUM, also tracked as Sandworm Team.[1][2][3][4]

Campaign Enterprise

C0017: C0017

C0017 was an APT41 campaign conducted between May 2021 and February 2022 that successfully compromised at least six U.S. state government networks through the exploitation of vulnerable Internet facing web applications. During C0017, APT41 was quick to adapt and use publicly-disclosed as well as zero-day vulnerabilities for initial access, and in at least two cases re-compromised victims following remediation efforts. The goals of C0017 are unknown, however APT41 was observed exfiltrating Personal Identifiable Information (PII).[1]

Relationship explorer

All related ATT&CK context

uses · Group G0032: Lazarus Group Enterprise uses · Campaign C0063: 2025 Poland Wiper Attacks Enterprise uses · Group G0061: FIN8 Enterprise mitigates · Mitigation M1031: Network Intrusion Prevention Enterprise uses · Malware S0125: Remsec Enterprise uses · Malware S0492: CookieMiner Enterprise uses · Malware S1043: ccf32 Enterprise uses · Malware S1116: WARPWIRE Enterprise uses · Malware S0356: KONNI Enterprise uses · Malware S0252: Brave Prince Enterprise uses · Malware S0674: CharmPower Enterprise uses · Malware S0050: CosmicDuke Enterprise uses · Group G0076: Thrip Enterprise uses · Group G0050: APT32 Enterprise uses · Malware S0212: CORALDECK Enterprise uses · Group G1045: Salt Typhoon Enterprise uses · Group G0129: Mustang Panda Enterprise detects · Detection Strategy DET0149: Detection of Exfiltration Over Unencrypted Non-C2 Protocol Enterprise uses · Group G1052: Contagious Interview Enterprise uses · Group G0102: Wizard Spider Enterprise uses · Malware S0331: Agent Tesla Enterprise uses · Malware S0428: PoetRAT Enterprise uses · Campaign C0017: C0017 Enterprise uses · Group G0049: OilRig Enterprise
Mitigations

Mitigation direction

Mitigation Enterprise

M1057: Data Loss Prevention

Data Loss Prevention (DLP) involves implementing strategies and technologies to identify, categorize, monitor, and control the movement of sensitive data within an organization. This includes protecting data formats indicative of Personally Identifiable Information (PII), intellectual property, or financial data from unauthorized access, transmission, or exfiltration. DLP solutions integrate with network, endpoint, and cloud platforms to enforce security policies and prevent accidental or malicious data leaks. [1] This mitigation can be implemented through the following measures:

Sensitive Data Categorization:

- Use Case: Identify and classify data based on sensitivity (e.g., PII, financial data, trade secrets). - Implementation: Use DLP solutions to scan and tag files containing sensitive information using predefined patterns, such as Social Security Numbers or credit card details.

Exfiltration Restrictions:

- Use Case: Prevent unauthorized transmission of sensitive data. - Implementation: Enforce policies to block unapproved email attachments, unauthorized USB usage, or unencrypted data uploads to cloud storage.

Data-in-Transit Monitoring:

- Use Case: Detect and prevent the transmission of sensitive data over unapproved channels. - Implementation: Deploy network-based DLP tools to inspect outbound traffic for sensitive content (e.g., financial records or PII) and block unapproved transmissions.

Endpoint Data Protection:

- Use Case: Monitor and control sensitive data usage on endpoints. - Implementation: Use endpoint-based DLP agents to block copy-paste actions of sensitive data and unauthorized printing or file sharing.

Cloud Data Security:

- Use Case: Protect data stored in cloud platforms. - Implementation: Integrate DLP with cloud storage platforms like Google Drive, OneDrive, or AWS to monitor and restrict sensitive data sharing or downloads.

Mitigation Enterprise

M1037: Filter Network Traffic

Employ network appliances and endpoint software to filter ingress, egress, and lateral network traffic. This includes protocol-based filtering, enforcing firewall rules, and blocking or restricting traffic based on predefined conditions to limit adversary movement and data exfiltration. This mitigation can be implemented through the following measures:

Ingress Traffic Filtering:

- Use Case: Configure network firewalls to allow traffic only from authorized IP addresses to public-facing servers. - Implementation: Limit SSH (port 22) and RDP (port 3389) traffic to specific IP ranges.

Egress Traffic Filtering:

- Use Case: Use firewalls or endpoint security software to block unauthorized outbound traffic to prevent data exfiltration and command-and-control (C2) communications. - Implementation: Block outbound traffic to known malicious IPs or regions where communication is unexpected.

Protocol-Based Filtering:

- Use Case: Restrict the use of specific protocols that are commonly abused by adversaries, such as SMB, RPC, or Telnet, based on business needs. - Implementation: Disable SMBv1 on endpoints to prevent exploits like EternalBlue.

Network Segmentation:

- Use Case: Create network segments for critical systems and restrict communication between segments unless explicitly authorized. - Implementation: Implement VLANs to isolate IoT devices or guest networks from core business systems.

Application Layer Filtering:

- Use Case: Use proxy servers or Web Application Firewalls (WAFs) to inspect and block malicious HTTP/S traffic. - Implementation: Configure a WAF to block SQL injection attempts or other web application exploitation techniques.

Mitigation Enterprise

M1030: Network Segmentation

Network segmentation involves dividing a network into smaller, isolated segments to control and limit the flow of traffic between devices, systems, and applications. By segmenting networks, organizations can reduce the attack surface, restrict lateral movement by adversaries, and protect critical assets from compromise.

Effective network segmentation leverages a combination of physical boundaries, logical separation through VLANs, and access control policies enforced by network appliances like firewalls, routers, and cloud-based configurations. This mitigation can be implemented through the following measures:

Segment Critical Systems:

- Identify and group systems based on their function, sensitivity, and risk. Examples include payment systems, HR databases, production systems, and internet-facing servers. - Use VLANs, firewalls, or routers to enforce logical separation.

Implement DMZ for Public-Facing Services:

- Host web servers, DNS servers, and email servers in a DMZ to limit their access to internal systems. - Apply strict firewall rules to filter traffic between the DMZ and internal networks.

Use Cloud-Based Segmentation:

- In cloud environments, use VPCs, subnets, and security groups to isolate applications and enforce traffic rules. - Apply AWS Transit Gateway or Azure VNet peering for controlled connectivity between cloud segments.

Apply Microsegmentation for Workloads:

- Use software-defined networking (SDN) tools to implement workload-level segmentation and prevent lateral movement.

Restrict Traffic with ACLs and Firewalls:

- Apply Access Control Lists (ACLs) to network devices to enforce "deny by default" policies. - Use firewalls to restrict both north-south (external-internal) and east-west (internal-internal) traffic.

Monitor and Audit Segmented Networks:

- Regularly review firewall rules, ACLs, and segmentation policies. - Monitor network flows for anomalies to ensure segmentation is effective.

Test Segmentation Effectiveness:

- Perform periodic penetration tests to verify that unauthorized access is blocked between network segments.

Change history

Object version and sync metadata

The fields below describe the current mirrored snapshot. When Glexia retains multiple ATT&CK source imports, you can open the table to compare the same object across releases (hashes and MITRE timestamps). For MITRE’s own release notes and roadmap, see ATT&CK resources — Updates .

ATT&CK release
19.1
Object version
2.2
Created
Modified
Raw hash
073921a1ba726ead...
Imported snapshots across ATT&CK releases (1)
Release Bundle imported Object version Modified Status Raw hash
19.1 2.2 Current bundle 073921a1ba72…
Raw source

Mirrored ATT&CK source object

The raw object is retained through the mirrored ATT&CK source bundle and object hash. The raw endpoint returns the exact object from the mirrored bundle when available.

Open mirrored raw JSON Open MITRE-hosted copy
Source references

External references and citations

MITRE external references are preserved separately from Glexia analysis so citations remain traceable to their original source records.

  1. [1]
    copy_cmd_cisco

    Cisco. (2022, August 16). copy - Cisco IOS Configuration Fundamentals Command Reference . Retrieved July 13, 2022.

    Open source URL
  2. [2]
    University of Birmingham C2

    Gardiner, J., Cova, M., Nagaraja, S. (2014, February). Command & Control Understanding, Denying and Detecting. Retrieved April 20, 2016.

    Open source URL
  3. [3]
    mitre-attack T1048.003
    Open source URL
Source and licensing

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