SKILLEMALL.ai

CC exploiting-constrained-delegation-abuse

Exploits Kerberos Constrained Delegation misconfigurations in Active Directory using Impacket's findDelegation.py and getST.py (or Rubeus/Kekeo on Windows) to abuse S4U2Self and S4U2Proxy and impersonate privileged users. Use during authorized Active Directory penetration tests or red-team engagements for lateral movement and privilege escalation after finding an account trusted for constrained delegation.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 6 files · 1 script body ≈ 2 035 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Exploits Kerberos Constrained Delegation misconfigurations in Active Directory using Impacket's findDelegation.py and getST.py (or Rubeus/Kekeo on Windows) to…

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
75
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Risky intent intent-offensive-security references/standards.md:8
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | T1550.003 | Pass the Ticket | Lateral Movement |
    • low Risky intent intent-offensive-security references/standards.md:9
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | T1134.001 | Token Impersonation/Theft | Privilege Escalation |
    • low Risky intent intent-offensive-security SKILL.md:8
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      movement and privilege escalation after finding an account trusted for constrained
    • low Risky intent intent-offensive-security SKILL.md:54
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - When conducting red team exercises or penetration testing engagements
    • low Risky intent intent-offensive-security SKILL.md:59
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - Familiarity with red teaming concepts and tools

    Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "domain"
    • note frontmatter-key unknown frontmatter key "subdomain"
    • note frontmatter-key unknown frontmatter key "d3fend_techniques"
    • note frontmatter-key unknown frontmatter key "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 38 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2035 tokens
    • 100Running it twice. No mutating operations
    • low 10 top-level sections: this looks like several domains in one skill

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -43 reference files, but SKILL.md never points to them: the model will not open them
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 409: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 38 items
    • +4Has examples (9 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.