Complete technique description
Adversaries may perform Endpoint Denial of Service (DoS) attacks to degrade or block the availability of services to users. Endpoint DoS can be performed by exhausting the system resources those services are hosted on or exploiting the system to cause a persistent crash condition. Example services include websites, email services, DNS, and web-based applications. Adversaries have been observed conducting DoS attacks for political purposes[FireEye OpPoisonedHandover February 2016] and to support other malicious activities, including distraction[FSISAC FraudNetDoS September 2012], hacktivism, and extortion.[Symantec DDoS October 2014]
An Endpoint DoS denies the availability of a service without saturating the network used to provide access to the service. Adversaries can target various layers of the application stack that is hosted on the system used to provide the service. These layers include the Operating Systems (OS), server applications such as web servers, DNS servers, databases, and the (typically web-based) applications that sit on top of them. Attacking each layer requires different techniques that take advantage of bottlenecks that are unique to the respective components. A DoS attack may be generated by a single system or multiple systems spread across the internet, which is commonly referred to as a distributed DoS (DDoS).
To perform DoS attacks against endpoint resources, several aspects apply to multiple methods, including IP address spoofing and botnets.
Adversaries may use the original IP address of an attacking system, or spoof the source IP address to make the attack traffic more difficult to trace back to the attacking system or to enable reflection. This can increase the difficulty defenders have in defending against the attack by reducing or eliminating the effectiveness of filtering by the source address on network defense devices.
Botnets are commonly used to conduct DDoS attacks against networks and services. Large botnets can generate a significant amount of traffic from systems spread across the global internet. Adversaries may have the resources to build out and control their own botnet infrastructure or may rent time on an existing botnet to conduct an attack. In some of the worst cases for DDoS, so many systems are used to generate requests that each one only needs to send out a small amount of traffic to produce enough volume to exhaust the target's resources. In such circumstances, distinguishing DDoS traffic from legitimate clients becomes exceedingly difficult. Botnets have been used in some of the most high-profile DDoS attacks, such as the 2012 series of incidents that targeted major US banks.[USNYAG IranianBotnet March 2016]
In cases where traffic manipulation is used, there may be points in the global network (such as high traffic gateway routers) where packets can be altered and cause legitimate clients to execute code that directs network packets toward a target in high volume. This type of capability was previously used for the purposes of web censorship where client HTTP traffic was modified to include a reference to JavaScript that generated the DDoS code to overwhelm target web servers.[ArsTechnica Great Firewall of China]
For attacks attempting to saturate the providing network, see Network Denial of Service.
Official technique definition · Open in the interactive matrix
Parent and sub-techniques
Related pages are navigation context. Their tools, rules and lab results are not automatically inherited.
Detection telemetry and configuration
These contracts are selected through exact technique-to-data-component relationships or explicitly labelled planning overrides. Configure a collector at the relevant observation point; a telemetry name alone is not coverage.
Application Log Content · source-mapped
DC0038 collection page — Select the application event family required by the detection and document its native schema before normalization.
Providers and collection configuration
- Enable the application audit category or instrument the owned lab application at the authorization/action boundary.
- Define a schema with timestamp, service, actor, object, action, result and correlation ID. Export structured records through an authenticated collector.
- Redact secrets and personal content, separate audit from debug logs, set retention and verify delivery during rotation/restart.
Required normalized fields: service, action, actor, record_count, result.
Illustrative collection event
Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.
{
"schema": "1200km.telemetry.example.v1",
"synthetic": true,
"timestamp": "2026-09-27T12:00:00Z",
"telemetry_id": "DC0038",
"collector": "illustrative-lab-collector",
"observation": {
"service": "lab-portal",
"action": "export_requested",
"actor": "lab-reader",
"record_count": 3,
"result": "authorized"
}
}
Visibility limits: Debug output is not necessarily a durable audit trail. Application developers must emit the relevant event; installing a log pipeline does not make an absent event exist.
Host Status · source-mapped
DC0018 collection page — Collect agent heartbeat and OS health independently; record missed polls, last-seen time and monitor health.
Providers and collection configuration
- osquery: Scheduled host-state queries; supported tables and privileges vary by OS. Select a table that actually exposes the required object.
- Linux Audit plus inventory snapshots: Events explain changes; snapshots describe state at collection time.
- Define the inventory query, allowed host set, interval and least-privileged reader. Store a stable asset ID, observation time and collector version.
- Keep successive snapshots and calculate additions, removals and changed attributes. Pair state changes with audit events when available.
- Export collector health and missed-poll counts so a missing snapshot is not misclassified as a missing asset.
Required normalized fields: asset_id, status, heartbeat_age_seconds, collector_healthy.
Illustrative collection event
Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.
{
"schema": "1200km.telemetry.example.v1",
"synthetic": true,
"timestamp": "2026-09-27T12:00:00Z",
"telemetry_id": "DC0018",
"collector": "illustrative-lab-collector",
"observation": {
"asset_id": "lab-host-1",
"status": "degraded",
"heartbeat_age_seconds": 90,
"collector_healthy": true
}
}
Visibility limits: Snapshots miss short-lived objects and do not identify who caused a change. A generic inventory agent is not guaranteed to expose firmware or kernel-level details.
Instance Start · source-mapped
DC0080 collection page — Collect start APIs and instance-state transitions with request IDs; distinguish accepted from completed.
Providers and collection configuration
- In the isolated account/project/subscription, route administrative audit logs to a protected destination with retention and access controls.
- Select the relevant service, regions and read/write operations. Confirm whether the API below is a management or data event in the provider documentation.
- Preserve actor/session, resource, request ID, service, operation, region and error details. Check delivery latency and avoid logging credentials or sensitive request bodies.
Required normalized fields: instance_id, action, state_before, state_after.
Illustrative collection event
Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.
{
"schema": "1200km.telemetry.example.v1",
"synthetic": true,
"timestamp": "2026-09-27T12:00:00Z",
"telemetry_id": "DC0080",
"collector": "illustrative-lab-collector",
"observation": {
"instance_id": "vm-lab-1",
"action": "start",
"state_before": "stopped",
"state_after": "pending"
}
}
Visibility limits: AWS, Azure and Google expose different APIs and event schemas. An accepted API request does not prove the final resource state; join asynchronous outcomes and inventory.
Network Traffic Flow · source-mapped
DC0078 collection page — Collect Zeek conn.log, Suricata flow events or exporter equivalents, including observation point and sampling settings.
Providers and collection configuration
- Zeek: Connection and protocol metadata from traffic visible to the sensor.
- Suricata EVE: Configured flow, alert, DNS, HTTP, TLS and protocol records.
- AWS VPC Flow Logs: IP traffic metadata alternative; no packet payload or DNS answer history, and some traffic is not logged.
- Use an authorized lab TAP/SPAN, virtual mirror or gateway interface. Define which traffic crosses it; avoid assuming visibility into every segment.
- Enable the required Zeek analyzers or Suricata EVE event types. Export logs with sensor identity, clock synchronization and flow correlation identifiers.
- Monitor capture loss, truncation and exporter sampling. Capture payload only with approval and restrictive retention; encryption normally prevents plaintext inspection.
Required normalized fields: source_ip, destination_ip, destination_port, protocol, bytes_sent, bytes_received.
Illustrative collection event
Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.
{
"schema": "1200km.telemetry.example.v1",
"synthetic": true,
"timestamp": "2026-09-27T12:00:00Z",
"telemetry_id": "DC0078",
"collector": "illustrative-lab-collector",
"observation": {
"source_ip": "192.0.2.10",
"destination_ip": "198.51.100.20",
"destination_port": 443,
"protocol": "tcp",
"bytes_sent": 128,
"bytes_received": 512
}
}
Visibility limits: Flows are not packet payloads. NAT, asymmetric routes, encryption, missing mirrors and sampling can hide attribution or content. A destination connection alone does not prove malicious intent.
Process Creation · source-mapped
DC0032 collection page — Collect Sysmon ProcessCreate (1); preserve ProcessGuid and parent identifiers. Security 4688 is an alternative with separate audit/command-line settings.
Providers and collection configuration
- Microsoft Sysmon: Windows event-based collection; enable the event types needed below.
- Linux Audit: Linux alternative for supported system-call and file events; different semantics and fields.
- Apple Endpoint Security clients: macOS alternative where the subscribed event exists; requires an entitled, approved client, not an iOS collector.
- On a disposable Windows host, review the installed Sysmon schema and current configuration; merge scoped event filters into the existing policy rather than replacing it.
- Forward Microsoft-Windows-Sysmon/Operational to the lab collector. Preserve event ID, timestamp, computer, process identifiers and the original event.
- For Linux or macOS, select the equivalent sensor separately and test its emitted fields; a Windows event ID does not transfer across platforms.
Required normalized fields: process_guid, image, parent_image, command_line, user.
<EventFiltering>
<ProcessCreate onmatch="include">
<Image condition="is">C:\Windows\System32\whoami.exe</Image>
</ProcessCreate>
</EventFiltering>
This fragment only selects the named process. It is not a complete production policy. Inspect the installed schema with sysmon64 -s; preserve existing rules, then apply the reviewed complete configuration with sysmon64 -c <configuration-file>.
Illustrative collection event
Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.
{
"schema": "1200km.telemetry.example.v1",
"synthetic": true,
"timestamp": "2026-09-27T12:00:00Z",
"telemetry_id": "DC0032",
"collector": "illustrative-lab-collector",
"observation": {
"process_guid": "lab-process-001",
"image": "C:\\Windows\\System32\\whoami.exe",
"parent_image": "C:\\Windows\\System32\\cmd.exe",
"command_line": "whoami",
"user": "LAB\\analyst"
}
}
Visibility limits: Event filtering and sensor versions change coverage. High-volume image-load and process-access collection needs tuning; endpoint events alone do not establish intent.