Atlas / Skills / cyberstrikeus / T1568.002 Domain Generation Algorithms

T1568.002 Domain Generation AlgorithmsCAUTION

skills/cyberstrikeus/t1568-002-domain-generation-algorithms

Open-source AI-powered offensive security harness for automated penetration testing.

Verdict
CAUTION
Grade
B
Trust score
89 /100
Version
18.1
Hosts
—
License
AGPL-3.0
Stars
3,185
01

Overview

Open-source AI-powered offensive security harness for automated penetration testing.

Read from source at commit eaf7d03223fcOBSERVED · 2026-10-18
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02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: "T1568.002_domain-generation-algorithms"
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 ..."
category: "configuration"
version: "18.1"
author: "cyberstrike-official"
tags:
  - mitre-attack
  - enterprise
  - t1568.002
  - command-and-control
  - linux
  - macos
  - windows
  - esxi
  - sub-technique
technique_id: "T1568.002"
tactic: "command-and-control"
all_tactics:
  - command-and-control
platforms:
  - Linux
  - macOS
  - Windows
  - ESXi
mitre_url: "https://attack.mitre.org/techniques/T1568/002"
tech_stack:
  - linux
  - macos
  - windows
  - esxi
cwe_ids:
  - CWE-300
chains_with:
  - T1568
  - T1568.001
  - T1568.003
prerequisites:
  - T1568
severity_boost:
  T1568: "Chain with T1568 for deeper attack path"
  T1568.001: "Chain with T1568.001 for deeper attack path"
  T1568.003: "Chain with T1568.003 for deeper attack path"
---

# T1568.002 Domain Generation Algorithms

> **Sub-technique of:** T1568

## High-Level 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.

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.

Adversaries may use DGAs for the purpose of Fallback Channels. When contact is lost with the primary command and control server malware may employ a DGA as a means to reestablishing command and control.

## Kill Chain Phase

- Command and Control (TA0011)

**Platforms:** Linux, macOS, Windows, ESXi

## What to Check

- [ ] Identify if Domain Generation Algorithms technique is applicable to target environment
- [ ] Check Linux systems for indicators of Domain Generation Algorithms
- [ ] Check macOS systems for indicators of Domain Generation Algorithms
- [ ] Check Windows systems for indicators of Domain Generation Algorithms
- [ ] Verify mitigations are bypassed or absent (2 known mitigations)
- [ ] Assess detection coverage (1 detection strategies)

## How to Test

### Manual Testing

1. **Identify Attack Surface**: Determine if the target environment is susceptible to Domain Generation Algorithms by examining the target platforms (Linux, macOS, Windows).

2. **Assess Existing Defenses**: Review whether mitigations for T1568.002 are in place. If defenses are absent or misconfigured, this technique may be exploitable.

3. **Execute Test**: Use tools and methods described in the MITRE ATT&CK page and external references below.

> **Note**: No Atomic Red Team tests available for this technique. See [Atomic Red Team GitHub](https://github.com/redcanaryco/atomic-red-team) for updates.

## Remediation Guide

### M1031 Network Intrusion Prevention

Network intrusion detection and prevention systems that use network signatures to identify traffic for specific adversary malware can be used to mitigate activity at the network level. Malware researchers can reverse engineer malware variants that use DGAs and determine future domains that the malware will attempt to contact, but this is a time and resource intensive effort. Malware is also increasingly incorporating seed values that can be unique for each instance, which would then need to be determined to extract future generated domains. In some cases, the seed that a particular sample uses can be extracted from DNS traffic. Even so, there can be thousands of possible domains generated per day; this makes it impractical for defenders to preemptively register all possible C2 domains due to the cost.

### M1021 Restrict Web-Based Content

In some cases a local DNS sinkhole may be used to help prevent DGA-based command and control at a reduced cost.

## Detection

### Detection Strategy for Dynamic Resolution using Domain Generation Algorithms.

## Risk Assessment

| Finding                                           | Severity | Impact              |
| ------------------------------------------------- | -------- | ------------------- |
| Domain Generation Algorithms technique applicable | Low      | Command And Control |

## CWE Categories

| CWE ID  | Title                              |
| ------- | ---------------------------------- |
| CWE-300 | Channel Accessible by Non-Endpoint |

## References

- [Elastic Predicting DGA](https://arxiv.org/pdf/1611.00791.pdf)
- [Talos CCleanup 2017](http://blog.talosintelligence.com/2017/09/avast-distributes-malware.html)
- [Pace University Detecting DGA May 2017](http://csis.pace.edu/~ctappert/srd2017/2017PDF/d4.pdf)
- [FireEye POSHSPY April 2017](https://www.fireeye.com/blog/threat-research/2017/03/dissecting_one_ofap.html)
- [ESET Sednit 2017 Activity](https://www.welivesecurity.com/2017/12/21/sednit-update-fancy-bear-spent-year/)
- [Data Driven Security DGA](https://datadrivensecurity.info/blog/posts/2014/Oct/dga-part2/)
- [Akamai DGA Mitigation](https://medium.com/@yvyuz/a-death-match-of-domain-generation-algorithms-a5b5dbdc1c6e)
- [Cisco Umbrella DGA](https://umbrella.cisco.com/blog/2016/10/10/domain-generation-algorithms-effective/)
- [Cybereason Dissecting DGAs](http://go.cybereason.com/rs/996-YZT-709/images/Cybereason-Lab-Analysis-Dissecting-DGAs-Eight-Real-World-DGA-Variants.pdf)
- [Unit 42 DGA Feb 20
03

Trust audit

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

LayerWhat it checksResult
L0Provenance & inventoryWARN
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (5)

MEDIUMInventory / provenance · inv.symlink · CWE-1104
packages/app/public/apple-touch-icon-v3.png
packages/app/public/apple-touch-icon-v3.png
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
packages/app/public/apple-touch-icon.png
packages/app/public/apple-touch-icon.png
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
packages/app/public/favicon-96x96-v3.png
packages/app/public/favicon-96x96-v3.png
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
packages/app/public/favicon-96x96.png
packages/app/public/favicon-96x96.png
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
packages/app/public/favicon-v3.ico
packages/app/public/favicon-v3.ico
Why it matters. link not followed

Gates applied: no_behavioural_pass.

Audited 2026-10-18 · audit v0.4.1 · source sha eaf7d03223fcfull audit observations/trust-audit/skill/cyberstrikeus__t1568.002_domain-generation-algorithms.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-18eaf7d03223fcCAUTIONB89first audit
05

Questions

What does the T1568.002 Domain Generation Algorithms skill do?

Open-source AI-powered offensive security harness for automated penetration testing.

Is T1568.002 Domain Generation Algorithms safe to install?

With care. The audit graded it B (89/100) and found 5 things worth knowing before you trust this skill, listed below with the exact line each was found on.

What can T1568.002 Domain Generation Algorithms access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (eaf7d03223fc), read on 2026-10-18. The repository is watched, and a new audit runs when it changes — this is the first audit.

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