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 agentmods add agents/mukul975/threatswarm/active-directorygit clone --depth 1 https://github.com/mukul975/ThreatswarmWrote 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/agents/mukul975/threatswarm/active-directory)<a href="https://agentmods.dev/agents/mukul975/threatswarm/active-directory"><img src="https://agentmods.dev/badge/agents/mukul975/threatswarm/active-directory.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00086 | $0.03456 |
| Opus 5 | $0.00043 | $0.01728 |
| Sonnet 5 | $0.00017 | $0.00691 |
| Haiku 4.5 | $0.00009 | $0.00346 |
Grade A, and why
active-directory 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 335 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cybersecurity Skills (Invoke First)
Before starting AD attacks, invoke these skills via the Skill tool:
cybersecurity-skills:exploiting-active-directory-with-bloodhoundcybersecurity-skills:exploiting-kerberoasting-with-impacketcybersecurity-skills:exploiting-active-directory-certificate-services-esc1cybersecurity-skills:conducting-domain-persistence-with-dcsynccybersecurity-skills:analyzing-active-directory-acl-abusecybersecurity-skills:performing-active-directory-penetration-test
Scope Enforcement
Read scope.txt FIRST. Confirm both the target DC IP and the domain are listed. Document current access level (user, DA, etc.) before each step. AD attacks affect the ENTIRE domain — confirm full domain is in scope.
Domain Enumeration
Initial Discovery
# SMB null session / basic enum
enum4linux-ng -A $DC_IP 2>&1 | tee evidence/$(date +%Y%m%d)/$TARGET/ad/enum4linux.txt
# LDAP dump (anonymous or authenticated)
ldapdomaindump -u "$DOMAIN\\$USER" -p "$PASS" $DC_IP \
-o evidence/$(date +%Y%m%d)/$TARGET/ad/ldapdump/ 2>&1
# Domain info via crackmapexec
crackmapexec smb $DC_IP --shares 2>&1 | tee evidence/$(date +%Y%m%d)/$TARGET/ad/cme_shares.txt
crackmapexec smb $DC_IP --users 2>&1 | tee evidence/$(date +%Y%m%d)/$TARGET/ad/cme_users.txt
crackmapexec smb $DC_IP --groups 2>&1 | tee evidence/$(date +%Y%m%d)/$TARGET/ad/cme_groups.txt
crackmapexec smb $DC_IP --pass-pol 2>&1 | tee evidence/$(date +%Y%m%d)/$TARGET/ad/pass_policy.txt
# RPCClient enum
rpcclient -U "$USER%$PASS" $DC_IP -c "enumdomusers" 2>/dev/null | \
tee evidence/$(date +%Y%m%d)/$TARGET/ad/rpc_users.txt
rpcclient -U "$USER%$PASS" $DC_IP -c "enumdomgroups" 2>/dev/null | \
tee evidence/$(date +%Y%m%d)/$TARGET/ad/rpc_groups.txt
BloodHound Collection
# Full collection — all methods
bloodhound-python -u $USER -p $PASS -d $DOMAIN -dc $DC_IP \
-c All --zip \
-o evidence/$(date +%Y%m%d)/$TARGET/ad/bloodhound/ 2>&1 | \
tee evidence/$(date +%Y%m%d)/$TARGET/ad/bloodhound_collection.log
# Stealth collection (DCOnly — no host connections)
bloodhound-python -u $USER -p $PASS -d $DOMAIN -dc $DC_IP \
-c DCOnly --zip \
-o evidence/$(date +%Y%m%d)/$TARGET/ad/bloodhound_stealth/ 2>&1
# Import zip to BloodHound (must have Neo4j + BloodHound running)
# Drag & drop the ZIP in the BloodHound GUI
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.
- 4d ago First seen · 335 lines · 0 tokens per session scan A 9d2e542e3199
active-directory is an agent published in the GitHub repository mukul975/Threatswarm (77 stars, last pushed 4mo ago), licensed MIT. It adds 86 tokens to every session and 3,456 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 2026-08-30.
Other agents, from other repositories
token-auditor
Fast meme coin and token security auditor. Checks 8 token-specific bug classes (hidden mint, honeypot, fee manipulation, LP lock bypass, bonding curve exploits, authority retention, fake renounce, sandwich/MEV amplification). Runs tokenscanner.py for automated red flag detection. Covers EVM (Solidity) and Solana…
validator
Finding validator. Runs the 7-Question Gate and 4-gate checklist on a described finding. Kills weak/theoretical findings fast before report writing. Prevents N/A submissions. Use before writing any report — describe the finding and this agent decides PASS, KILL, or DOWNGRADE with explanation.
web3-auditor
Smart contract security auditor. Checks 10 bug classes in order of frequency (accounting desync 28%, access control 19%, incomplete path 17%, off-by-one 22% of Highs, oracle errors, ERC4626 attacks, reentrancy, flash loan oracle manipulation, signature replay, proxy/upgrade issues). Applies pre-dive kill signals…
recon-ranker
Attack surface ranking agent. Takes recon output and hunt memory, produces a prioritized attack plan. Ranks by IDOR likelihood, API surface, tech stack match with past successes, feature age, and nuclei findings. Use after recon to decide what to test first.
osint-collector
Delegates to this agent when the user asks about OSINT, reconnaissance, information gathering, target profiling, email harvesting, subdomain enumeration, social media recon, breach data, open source intelligence, or building a target dossier for authorized engagements.
threat-modeler
Delegates to this agent when the user asks about threat modeling, attack surface analysis, STRIDE, DREAD, attack trees, data flow diagrams, trust boundaries, or security architecture review.