Email Bombing

Adversaries may flood targeted email addresses with an overwhelming volume of messages. This may bury legitimate emails in a flood of spam and disrupt business operations.[1][2]

An adversary may accomplish email bombing by leveraging an automated bot to register a targeted address for e-mail lists that do not validate new signups, such as online newsletters. The result can be a wave of thousands of e-mails that effectively overloads the victim’s inbox.[2][3]

By sending hundreds or thousands of e-mails in quick succession, adversaries may successfully divert attention away from and bury legitimate messages including security alerts, daily business processes like help desk tickets and client correspondence, or ongoing scams.[3] This behavior can also be used as a tool of harassment.[2]

This behavior may be a precursor for Spearphishing Voice. For example, an adversary may email bomb a target and then follow up with a phone call to fraudulently offer assistance. This social engineering may lead to the use of Remote Access Software to steal credentials, deploy ransomware, conduct Financial Theft[1], or engage in other malicious activity.[4]

ID: T1667
Sub-techniques:  No sub-techniques
Tactic: Impact
Platforms: Linux, Office Suite, Windows, macOS
Impact Type: Availability
Contributors: Ryan Perez
Version: 1.0
Created: 31 January 2025
Last Modified: 15 April 2025

Procedure Examples

ID Name Description
G1046 Storm-1811

Storm-1811 has deployed large volumes of non-malicious email spam to victims in order to prompt follow-on interactions with the threat actor posing as IT support or helpdesk to resolve the problem.[4][5]

Mitigations

ID Mitigation Description
M1054 Software Configuration

Use anti-spoofing and email authentication mechanisms to filter messages based on validity checks of the sender domain (using SPF) and integrity of messages (using DKIM). Enabling these mechanisms within an organization (through policies such as DMARC) may enable recipients (intra-org and cross domain) to perform similar message filtering and validation.[6][7] Note that additional filtering may be necessary if emails are coming from legitimate sources.

M1017 User Training

Train users to be aware of access or manipulation attempts by an adversary to reduce the risk of successful social engineering via e-mail bombing.

Detection

ID Data Source Data Component Detects
DS0015 Application Log Application Log Content

Monitor e-mail logs for an abnormally high volume of messages or message content sent to specific victim e-mail addresses or servers.

Analytic 1 - Spike in Email Volume index=email_logs sourcetype="mail:log"| timechart span=5m count by recipient_email| eventstats avg(count) as avg_count stdev(count) as std_dev by recipient_email| eval spike=if(count > avg_count + (3*std_dev), 1, 0)| search spike=1| table _time, recipient_email, count, avg_count, std_dev

DS0022 File File Creation

Monitor for - Attachment creation events with excessive or repetitive file creation- Unusual file size from email messages (e.g., base64-encoded attachments dumped locally)- Burst of .eml, .msg, .tmp file extensions in mail client folders

Analytic 1 - Email file creations

EventCode=11 (file_name=".eml" OR file_name=".msg" OR file_name="*.tmp")| stats count avg(file_size) max(file_size) by user, file_path, process_name, _time| where count > 100 OR max(file_size) > 1000000| table _time, user, process_name, file_path, file_name, count, max(file_size)

DS0029 Network Traffic Network Traffic Flow

Monitor network data for uncommon data flows. Abnormal spikes in incoming traffic volume to specific victim e-mail addresses or servers may indicate an email bombing attempt.

Analytic 1 - Suspicious network traffic

sourcetype="zeek:conn" dest_port=25 OR dest_port=465 OR dest_port=587| stats count avg(bytes_in) by src_ip, dest_ip, dest_port, _time| eventstats avg(count) as avg_flows, stdev(count) as std_flows by dest_ip| eval anomaly=if(count > avg_flows + (2*std_flows), 1, 0)| search anomaly=1| table _time, src_ip, dest_ip, dest_port, count, avg_flows

References