detecting-golden-ticket-forgery

detecting-golden-ticket-forgery is a skill for Claude Code from oyi77/1ai-skills. It costs 71 tokens per session (1,073 once invoked), scanned A, original, MIT.

A security-analysis guide for spotting forged Kerberos access tickets in Windows domain logs. It focuses on unusual encryption, ticket lifetimes, missing login events, and krbtgt account changes.

In plain words
What is it for?
Use it to build Splunk or Elastic SIEM detections, investigate suspected Golden Ticket attacks, and check whether monitoring covers this technique.
Why use it?
It helps security teams find signs that an attacker created fake credentials to access services across a Windows domain.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the 1ai-skills plugin — 209 skills, 4 commands shipped together

Good fit Use it to build Splunk or Elastic SIEM detections, investigate suspected Golden Ticket attacks, and check whether monitoring covers this technique.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/oyi77/1ai-skills/detecting-golden-ticket-forgery
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add oyi77/1ai-skills --skill detecting-golden-ticket-forgery
Clone the repo
git clone --depth 1 https://github.com/oyi77/1ai-skills

Made for: Claude Code.

Or install 1ai-skills, the plugin that ships this one along with the rest of its 209 skills, 4 commands.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for detecting-golden-ticket-forgery

README.md
[![agentmods](https://agentmods.dev/badge/skills/oyi77/1ai-skills/detecting-golden-ticket-forgery/github.svg)](https://agentmods.dev/skills/oyi77/1ai-skills/detecting-golden-ticket-forgery)
Your own site
<a href="https://agentmods.dev/skills/oyi77/1ai-skills/detecting-golden-ticket-forgery"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/detecting-golden-ticket-forgery/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for detecting-golden-ticket-forgery

Your own site · 80×15
<a href="https://agentmods.dev/skills/oyi77/1ai-skills/detecting-golden-ticket-forgery"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/detecting-golden-ticket-forgery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,073 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high YARA Match · line 13
    YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).
    Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00071 $0.01073
Opus 5 $0.00036 $0.00536
Sonnet 5 $0.00014 $0.00215
Haiku 4.5 $0.00007 $0.00107

Measured 8d ago against content hash e9e464055809, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

detecting-golden-ticket-forgery scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

cybersecurity/_deprecated/detecting-golden-ticket-forgery/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Detecting Golden Ticket Forgery

Overview

A Golden Ticket attack (MITRE ATT&CK T1558.001) involves forging a Kerberos Ticket Granting Ticket (TGT) using the krbtgt account NTLM hash, granting unrestricted access to any service in the Active Directory domain. This skill detects Golden Ticket usage by analyzing Event ID 4769 for RC4 encryption type (0x17) in environments enforcing AES, identifying tickets with abnormal lifetimes exceeding domain policy, correlating TGS requests with missing corresponding TGT requests (Event ID 4768), and detecting krbtgt password age anomalies.

When to Use

Trigger phrases:

  • "detecting golden ticket forgery"

  • "Detect Kerberos Golden Ticket forgery by analyzing Windows Event ID 4769 for RC4"

  • When investigating security incidents that require detecting golden ticket forgery

  • When building detection rules or threat hunting queries for this domain

  • When SOC analysts need structured procedures for this analysis type

  • When validating security monitoring coverage for related attack techniques

When NOT to Use

  • When you lack proper authorization for testing
  • For production systems without change management
  • When the task requires legal or compliance expertise beyond technical scope

Prerequisites

  • Windows Domain Controller with Kerberos audit logging enabled
  • Splunk or Elastic SIEM ingesting Windows Security event logs
  • Python 3.8+ for offline event log analysis
  • Knowledge of domain Kerberos encryption policy (AES vs RC4)

Steps

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}
  1. Audit domain Kerberos encryption policy to establish AES-only baseline
  2. Forward Event IDs 4768 and 4769 to SIEM platform
  3. Detect RC4 (0x17) encryption in TGS requests where AES is enforced
  4. Identify TGS requests without corresponding TGT requests (forged ticket indicator)
  5. Alert on ticket lifetimes exceeding MaxTicketAge domain policy
  6. Monitor krbtgt account password age and last reset date
  7. Correlate findings with host/user context for risk scoring

Read the full file on GitHub · 122 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 122 lines · 71 tokens per session scan A e9e464055809

Subscribe to this mod's changes

detecting-golden-ticket-forgery is a skill published in the GitHub repository oyi77/1ai-skills (12 stars, last pushed today), licensed MIT. It adds 71 tokens to every session and 1,073 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.

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