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 commands/ogrodev/fsociety/ty-dorkgit clone --depth 1 https://github.com/ogrodev/fsocietyWrote 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/commands/ogrodev/fsociety/ty-dork)<a href="https://agentmods.dev/commands/ogrodev/fsociety/ty-dork"><img src="https://agentmods.dev/badge/commands/ogrodev/fsociety/ty-dork.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 | $0.00012 | $0.00592 |
| Opus 5 | $0.00006 | $0.00296 |
| Sonnet 5 | $0.00002 | $0.00118 |
| Haiku 4.5 | $0.00001 | $0.00059 |
Grade A, and why
ty-dork scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Via curl to search API** (fallback): How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are executing a Google dorking operation for the tyrell data exfiltration plugin.
Step 1 — Generate Dork Queries
Run the hunt engine to produce optimized Google dork queries for the target:
node "${CLAUDE_PLUGIN_ROOT}/scripts/hunt-engine.js" dork $ARGUMENTS
The script returns a list of dork objects with fields: dork (the raw query string), category, rationale, and expected_filetype.
Step 2 — Execute Dorks
For each dork query returned, attempt execution via available search tooling:
- Via MCP web search tool (preferred): Submit the raw dork string as a search query and retrieve results.
- Via curl to search API (fallback):
curl -s "https://customsearch.googleapis.com/customsearch/v1?key=${GOOGLE_API_KEY}&cx=${GOOGLE_CX}&q=<url-encoded-dork>" | jq '.items[] | {title: .title, link: .link, snippet: .snippet}'
Respect rate limits — introduce a short pause between consecutive dork executions if running many queries.
Step 3 — Filter and Triage Results
From each set of search results, identify high-value hits:
- URLs ending in
.sql,.csv,.xlsx,.json,.bak,.dump,.tar.gzare immediate priorities. - Admin panel URLs (
/phpmyadmin,/adminer,/db-admin,/_plugin/kibana) warrant further investigation. - Publicly indexed S3 buckets, GCS buckets, or Azure Blob containers containing database files.
- Config files exposing connection strings (
.env,config.php,database.yml).
Step 4 — Log Findings
For each significant result, log it with the source-tracker:
node "${CLAUDE_PLUGIN_ROOT}/scripts/source-tracker.js" add \
--type dork \
--url "<result-url>" \
--category "<category>" \
--dork "<original-dork-string>" \
--notes "<what was found>"
Step 5 — Present Results
Output a structured report grouped by category:
Exposed Databases
- List URLs with brief description
Credentials / Config Files
- List URLs with brief description
Data Dumps
- List URLs with file types and estimated relevance
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.
- today First seen · 70 lines · 12 tokens per session scan A 97973ebaec4a
ty-dork is a command published in the GitHub repository ogrodev/fsociety (20 stars, last pushed 5mo ago), licensed MIT. It adds 12 tokens to every session and 592 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
pentest
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pentest-attacks
Define the attack profile for an engagement — select which attack categories and skills to use. Saves to .pentest-attacks.json. If run before /pentest:pentest, the orchestrator will respect the selection. If run standalone, does not launch a pentest.
pentest-kali
Connect to a Metasploit-Kali Server (MKS) REST API — verifies connectivity, discovers available Kali tools, and configures agents to prefer MKS endpoints over local Bash equivalents.
pentest-scope
Define or update engagement scope — saves scope to disk without launching a pentest. Can be run before or during an engagement. If a pentest is active and the target changes drastically, warns the operator and suggests a new engagement.
pentest-exit
Close pentest session — summarizes findings, ensures outputs are saved, lifts isolation, and prompts for /clear.
bb-ad
Active Directory enumeration and attack techniques. Includes LDAP enumeration, Kerberos attacks (Kerberoasting, AS-REP Roasting), SMB attacks, and domain privilege escalation. Use this when targeting Windows domain environments.