external/anthropic-cybersecurity-skills/skills/executing-red-team-exercise/SKILL.md
Run a stealthy, MITRE ATT&CK-mapped adversary emulation against an organization's people, processes, and technology, using C2 infrastructure (Cobalt Strike, Sliver, Brute Ratel, Mythic) through the full attack lifecycle to test SOC detection and response rather than just find vulnerabilities. Use when executing a full-scope red team exercise, adversary simulation/emulation, or a regulatory exercise (TIBER-EU, CBEST, AASE, iCAST) with executive authorization and a signed Rules of Engagement already in place.
npx skillsauth add seikaikyo/dash-skills executing-red-team-exerciseInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Do not use without executive-level authorization and a detailed Rules of Engagement document, against systems where disruption could affect safety or critical operations, or as a replacement for basic vulnerability management (fix known vulnerabilities first).
Legal Notice: This skill is for authorized security testing and educational purposes only. Unauthorized use against systems you do not own or have written permission to test is illegal and may violate computer fraud laws.
Develop the operation plan based on a realistic threat model:
Build OPSEC-hardened attack infrastructure:
Gain initial foothold in the target environment:
Operate within the target environment while maintaining stealth:
Convert red team findings into defensive improvements:
| Term | Definition | |------|------------| | Adversary Emulation | Simulating the specific TTPs of a known threat actor to test defenses against realistic threats relevant to the organization | | C2 (Command and Control) | Infrastructure and communication channels used by the red team to remotely control implants deployed on compromised systems | | OPSEC | Operational Security; practices employed by the red team to avoid detection by the defending team during the exercise | | Domain Fronting | A technique for hiding C2 traffic behind legitimate CDN domains to evade network-based detection and domain blocking | | Purple Teaming | Collaborative exercise where red and blue teams work together to improve detection by sharing attack techniques and defensive gaps | | White Cell | The trusted agent or exercise control group that manages the exercise, handles deconfliction, and mediates between red and blue teams | | Implant | Software deployed by the red team on compromised systems to maintain access, execute commands, and facilitate lateral movement | | MTTD/MTTR | Mean Time to Detect / Mean Time to Respond; metrics measuring how long it takes the defending team to identify and contain threats |
Context: A national retail chain wants to test its defenses against FIN7, a financially motivated threat group known for targeting retail and hospitality organizations with point-of-sale malware, phishing, and data exfiltration.
Approach:
Pitfalls:
## Red Team Exercise Report - FIN7 Adversary Emulation
### Exercise Summary
**Duration**: November 4-22, 2025 (15 business days)
**Objective**: Access cardholder data environment and demonstrate data exfiltration capability
**Outcome**: OBJECTIVE ACHIEVED - Red team accessed POS management system and staged cardholder data for exfiltration
### ATT&CK Technique Coverage
| Technique | ID | Status | Detected? | MTTD |
|-----------|----|--------|-----------|------|
| Spear-Phishing Attachment | T1566.001 | Executed | No | - |
| Visual Basic Macro | T1059.005 | Executed | No | - |
| Process Injection | T1055 | Executed | No | - |
| Kerberoasting | T1558.003 | Executed | No | - |
| Remote Desktop Protocol | T1021.001 | Executed | YES | 47h |
| Data Staged | T1074 | Executed | No | - |
| Exfiltration Over C2 | T1041 | Executed | No | - |
### Detection Summary
- **Techniques Executed**: 14
- **Techniques Detected**: 3 (21.4%)
- **Mean Time to Detect**: 47 hours (for detected techniques)
- **Mean Time to Respond**: 4 hours (from detection to containment)
### Priority Recommendations
1. Deploy email detonation sandboxing for macro-enabled document analysis
2. Implement Kerberoasting detection via Windows Event ID 4769 monitoring
3. Enhance PowerShell logging (Script Block Logging, Module Logging)
4. Deploy memory-scanning EDR capability to detect process injection
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.