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.
npx skills add 26zl/cybersec-toolkit --skill deploying-active-directory-honeytokensgit clone --depth 1 https://github.com/26zl/cybersec-toolkitWrote 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.
[](https://agentmods.dev/skills/26zl/cybersec-toolkit/deploying-active-directory-honeytokens)<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/deploying-active-directory-honeytokens"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/deploying-active-directory-honeytokens/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.
<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/deploying-active-directory-honeytokens"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/deploying-active-directory-honeytokens.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 5 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high YARA Match · line 63 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.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00101 | $0.02416 |
| Opus 5 | $0.00051 | $0.01208 |
| Sonnet 5 | $0.00020 | $0.00483 |
| Haiku 4.5 | $0.00010 | $0.00242 |
Grade A, and why
deploying-active-directory-honeytokens 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 7d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- deploying-active-directory-honeytokens — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploying Active Directory Honeytokens
When to Use
- When deploying deception-based detection in Active Directory environments
- When detecting Kerberoasting attacks via fake SPN honeytokens (honeyroasting)
- When creating tripwire accounts to detect credential theft and lateral movement
- When building decoy GPOs to detect Group Policy Preference password harvesting
- When creating deceptive BloodHound paths to misdirect and detect attackers
- When supplementing existing AD monitoring with high-fidelity detection signals
Prerequisites
- Domain Admin or delegated AD administration privileges
- Active Directory domain (Windows Server 2016+ recommended)
- Windows Event Log forwarding to SIEM (Splunk, Sentinel, Elastic)
- PowerShell 5.1+ with ActiveDirectory module
- Group Policy Management Console (GPMC)
- Understanding of AD security, Kerberos, and BloodHound attack paths
Background
Why AD Honeytokens
Traditional signature-based detection misses novel attack techniques. Honeytokens provide high-fidelity detection with near-zero false positives because any interaction with a decoy object is inherently suspicious. In Active Directory:
- Fake privileged accounts detect credential dumping (DCSync, NTDS.dit extraction)
- Fake SPNs detect Kerberoasting reconnaissance (TGS requests for nonexistent services)
- Decoy GPOs detect Group Policy Preference password harvesting
- Fake BloodHound paths mislead attackers using graph-based AD analysis
Key Detection Event IDs
| Event ID | Description | Honeytoken Use |
|---|---|---|
| 4769 | Kerberos TGS ticket requested | Detect Kerberoast against honey SPN |
| 4625 | Failed logon attempt | Detect use of fake credentials from decoy GPO |
| 4662 | Directory service object accessed | Detect DACL read on honeytoken user |
| 5136 | Directory service object modified | Detect modification of decoy GPO |
| 5137 | Directory service object created | Detect GPO creation mimicking decoy |
| 4768 | Kerberos TGT requested | Detect AS-REP roasting of honey account |
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 261 lines · 101 tokens per session scan A 0118316a1533
deploying-active-directory-honeytokens is a skill published in the GitHub repository 26zl/cybersec-toolkit (54 stars, last pushed today), licensed MIT. It adds 101 tokens to every session and 2,416 once invoked, about $0.0005 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 2026-09-03.
Other skills, from other repositories
deploying-active-directory-honeytokens
Deploys deception-based honeytokens in Active Directory including fake privileged accounts with AdminCount=1, fake SPNs for Kerberoasting detection (honeyroasting), decoy GPOs with cpassword traps, and fake BloodHound paths. Monitors Windows Security Event IDs 4769, 4625, 4662, 5136 for honeytoken interaction. Use…
deploying-active-directory-honeytokens
Deploys deception-based honeytokens in Active Directory including fake privileged accounts with AdminCount=1, fake SPNs for Kerberoasting detection (honeyroasting), decoy GPOs with cpassword traps, and fake BloodHound paths. Monitors Windows Security Event IDs 4769, 4625, 4662, 5136 for honeytoken interaction. Use…
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ad-exploitation
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ad-recon
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