# Attack Ent T1568 002 Domain Generation Algorithms

> Analyze MITRE ATT&CK T1568.002 Domain Generation Algorithms in the enterprise matrix. Use for TTP triage, detection engineering, hunting, defensive emulation planning, mitigations, incident response mapping, ATT&CK coverage, or questions mentioning T1568.002, Domain Generation Algorithms, or enterprise ATT&CK. Adversaries may make use of Domain Generation Algorithms (DGAs) to dynamically identify a destination domain for command and control traffic rather than relying on a list of static IP addresses or domains.

- Skill: `santosomar/attack-ent-t1568-002-domain-generation-algorithms` (Agent Skill, multi-file: 11 files)
- Install (CLI): `npx skillmds@latest add santosomar/attack-ent-t1568-002-domain-generation-algorithms`
- Raw SKILL.md: https://api.skillmd.com/api/skills/santosomar/attack-ent-t1568-002-domain-generation-algorithms/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- License: MITRE ATT&CK Terms of Use apply to ATT&CK-derived content. See h
- Author: santosomar (https://skillmd.com/u/santosomar)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/santosomar/attack-ent-t1568-002-domain-generation-algorithms

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# MITRE ATT&CK T1568.002: Domain Generation Algorithms

## When to use this skill

Use this skill when the task involves T1568.002, Domain Generation Algorithms, enterprise ATT&CK, TTP mapping, detection engineering, hunting, incident-response enrichment, control validation, or authorized adversary-emulation planning. Treat it as a defensive analysis aid: keep outputs focused on understanding, detecting, mitigating, and safely validating this ATT&CK sub-technique.

## Technique context

- ATT&CK domain: enterprise
- ATT&CK ID: T1568.002
- Technique name: Domain Generation Algorithms
- Type: sub-technique
- ATT&CK URL: https://attack.mitre.org/techniques/T1568/002
- Tactics: command-and-control
- Platforms: ESXi, Linux, macOS, Windows
- Required permissions: Not specified
- Effective permissions: Not specified
- Defenses bypassed: Not specified

## ATT&CK description

Adversaries may make use of Domain Generation Algorithms (DGAs) to dynamically identify a destination domain for command and control traffic rather than relying on a list of static IP addresses or domains. This has the advantage of making it much harder for defenders to block, track, or take over the command and control channel, as there potentially could be thousands of domains that malware can check for instructions.(Citation: Cybereason Dissecting DGAs)(Citation: Cisco Umbrella DGA)(Citation: Unit 42 DGA Feb 2019)

DGAs can take the form of apparently random or “gibberish” strings (ex: istgmxdejdnxuyla.ru) when they construct domain names by generating each letter. Alternatively, some DGAs employ whole words as the unit by concatenating words together instead of letters (ex: cityjulydish.net). Many DGAs are time-based, generating a different domain for each time period (hourly, daily, monthly, etc). Others incorporate a seed value as well to make predicting future domains more difficult for defenders.(Citation: Cybereason Dissecting DGAs)(Citation: Cisco Umbrella DGA)(Citation: Talos CCleanup 2017)(Citation: Akamai DGA Mitigation)

Adversaries may use DGAs for the purpose of [Fallback Channels](https://attack.mitre.org/techniques/T1008). When contact is lost with the primary command and control server malware may employ a DGA as a means to reestablishing command and control.(Citation: Talos CCleanup 2017)(Citation: FireEye POSHSPY April 2017)(Citation: ESET Sednit 2017 Activity)

## Agent workflow

1. Clarify scope: identify the system, asset class, log sources, cloud or endpoint platform, and whether the user wants triage, detection, coverage assessment, or safe emulation planning.
2. Load bundled resources as needed: use `references/technique-profile.json` for structured metadata, `references/detection-and-mitigation.md` for triage and telemetry guidance, `references/known-threat-context.md` for ATT&CK relationship context, and `templates/` for repeatable outputs.
3. Map observations to ATT&CK: compare the user's evidence to the ATT&CK description, tactics, platforms, and known procedure patterns before asserting a match.
4. Produce defensive outputs: prioritize hypotheses, telemetry requirements, detection logic ideas, validation steps, containment guidance, and mitigations.
5. Preserve uncertainty: distinguish confirmed evidence, plausible indicators, assumptions, and gaps. Recommend what to collect next.
6. Stay safe: do not provide malware, credential theft, persistence, evasion, destructive automation, or unauthorized exploitation instructions. For adversary emulation, keep steps bounded to approved lab or control-validation contexts and omit operational abuse details.

## Bundled resources

- `references/technique-profile.json`: machine-readable ATT&CK metadata for this technique.
- `references/detection-and-mitigation.md`: detection notes, telemetry checklist, triage questions, mitigation candidates, and false-positive considerations.
- `references/known-threat-context.md`: ATT&CK relationship context with attribution cautions.
- `templates/detection-brief.md`: detection engineering brief template.
- `templates/hunt-plan.md`: threat hunt plan template.
- `templates/incident-response-note.md`: incident response note template.
- `templates/coverage-assessment.md`: ATT&CK coverage assessment template.
- `scripts/render_brief.py`: local helper that renders a Markdown defensive brief from `technique-profile.json`.
- `assets/output-schema.json`: JSON schema for structured technique analysis outputs.

To generate a quick brief, run `python scripts/render_brief.py --output brief.md` from inside this skill directory, or adapt the templates directly.

## Detection guidance

No ATT&CK detection guidance was present in the source STIX object.

## Useful telemetry and data sources

- Not specified in the STIX object.

## Mitigations to consider

- Network Intrusion Prevention
- Restrict Web-Based Content

## Known threat context

Use these examples only as contextual leads, not as proof that an observed event is this technique:

- APT41 (intrusion-set)
- Aria-body (malware)
- Astaroth (malware)
- AsyncRAT (tool)
- BONDUPDATER (malware)
- Bazar (malware)
- CCBkdr (malware)
- CHOPSTICK (malware)
- Conficker (malware)
- DarkWatchman (malware)
- Doki (malware)
- Ebury (malware)
- Grandoreiro (malware)
- HiddenFace (malware)
- Milan (malware)
- MiniDuke (malware)
- POSHSPY (malware)
- QakBot (malware)
- ShadowPad (malware)
- Shark (malware)

## Recommended output pattern

When responding with this skill, structure the answer as:

- Assessment: whether the evidence supports this ATT&CK mapping and why.
- Evidence: specific indicators, logs, behaviors, and assumptions.
- Detection: telemetry sources, analytic logic, and tuning considerations.
- Response: containment, eradication, recovery, and validation actions.
- Coverage gaps: missing logs, sensors, controls, or environmental details.
- References: include the ATT&CK URL and any user-provided evidence references.

## ATT&CK contributors

- Ryan Benson, Exabeam
- Barry Shteiman, Exabeam
- Sylvain Gil, Exabeam