Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →This skill should be used when the user asks to "attack Active Directory", "exploit AD", "Kerberoasting", "DCSync", "pass-the-hash", "BloodHound enumeration", "Golden Ticket", "Silver Ticket", "AS-REP roasting", "NTLM relay", or needs guidance on Windows domain penetration testing.
.claude/skills/dokhacgiakhoa-active-directory-attacks/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 44% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 241% | 0% |
| case-18 | ✗→✓ | ▲ Improved | 66% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 81% | 0% |
| case-05 | ✓→✓ | ＝ Same ✓ | 89% | 0% |
Provide comprehensive techniques for attacking Microsoft Active Directory environments. Covers reconnaissance, credential harvesting, Kerberos attacks, lateral movement, privilege escalation, and domain dominance for red team operations and penetration testing.
| Tool | Purpose | |------|---------| | BloodHound | AD attack path visualization | | Impacket | Python AD attack tools | | Mimikatz | Credential extraction | | Rubeus | Kerberos attacks | | CrackMapExec | Network exploitation | | PowerView | AD enumeration | | Responder | LLMNR/NBT-NS poisoning |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-05 | pass→pass | 5,700 | 6,411 | +12% | 1 | 1 | 0% | 960 | 1,811 | +89% | 0 | 0 | — |
case-01 | fail→pass | 25,498 | 40,764 | +60% | 1 | 1 | 0% | 3,241 | 4,674 | +44% | 0 | 0 | — |
case-02 | pass→pass | 22,943 | 15,205 | -34% | 1 | 1 | 0% | 3,313 | 3,158 | -5% | 0 | 0 | — |
case-03 | pass→pass | 6,269 | 4,805 | -23% | 1 | 1 | 0% | 885 | 1,678 | +90% | 0 | 0 | — |
case-04 | pass→pass | 20,855 | 18,807 | -10% | 1 | 1 | 0% | 3,044 | 3,704 | +22% | 0 | 0 | — |
case-06 | pass→pass | 16,541 | 17,167 | +4% | 1 | 1 | 0% | 1,005 | 1,740 | +73% | 0 | 0 | — |
case-07 | pass→pass | 18,001 | 19,637 | +9% | 1 | 1 | 0% | 1,199 | 2,119 | +77% | 0 | 0 | — |
case-08 | pass→pass | 4,352 | 14,365 | +230% | 1 | 1 | 0% | 781 | 1,942 | +149% | 0 | 0 | — |
case-09 | pass→pass | 8,244 | 6,653 | -19% | 1 | 1 | 0% | 1,134 | 2,075 | +83% | 0 | 0 | — |
case-10 | pass→pass | 9,325 | 6,944 | -26% | 1 | 1 | 0% | 1,344 | 2,194 | +63% | 0 | 0 | — |
case-11 | pass→pass | 12,170 | 8,759 | -28% | 1 | 1 | 0% | 1,769 | 2,258 | +28% | 0 | 0 | — |
case-12 | fail→pass | 3,445 | 6,037 | +75% | 1 | 1 | 0% | 501 | 1,709 | +241% | 0 | 0 | — |
case-13 | pass→pass | 8,540 | 6,145 | -28% | 1 | 1 | 0% | 1,499 | 1,846 | +23% | 0 | 0 | — |
case-14 | pass→pass | 19,479 | 22,153 | +14% | 1 | 1 | 0% | 3,465 | 4,660 | +34% | 0 | 0 | — |
case-15 | pass→pass | 5,946 | 12,421 | +109% | 1 | 1 | 0% | 993 | 1,743 | +76% | 0 | 0 | — |
case-16 | pass→pass | 4,991 | 6,870 | +38% | 1 | 1 | 0% | 841 | 1,363 | +62% | 0 | 0 | — |
case-17 | pass→pass | 15,938 | 21,214 | +33% | 1 | 1 | 0% | 2,452 | 3,950 | +61% | 0 | 0 | — |
case-18 | fail→pass | 19,101 | 23,379 | +22% | 1 | 1 | 0% | 2,716 | 4,513 | +66% | 0 | 0 | — |
case-19 | fail→pass | 5,155 | 9,325 | +81% | 1 | 1 | 0% | 770 | 1,397 | +81% | 0 | 0 | — |
case-20 | fail→fail | 13,414 | 17,461 | +30% | 1 | 1 | 0% | 2,002 | 3,475 | +74% | 0 | 0 | — |
case-21 | pass→pass | 15,501 | 18,345 | +18% | 1 | 1 | 0% | 2,810 | 3,797 | +35% | 0 | 0 | — |
case-22 | pass→pass | 13,060 | 15,591 | +19% | 1 | 1 | 0% | 1,968 | 3,020 | +53% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +18 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.