Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add ogrodev/fsociety/plugin install elliotWrote 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/ogrodev/fsociety/network-recon)<a href="https://agentmods.dev/skills/ogrodev/fsociety/network-recon"><img src="https://agentmods.dev/badge/skills/ogrodev/fsociety/network-recon/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/ogrodev/fsociety/network-recon"><img src="https://agentmods.dev/badge/skills/ogrodev/fsociety/network-recon.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00314 | $0.03394 |
| Opus 5.5 | $0.00126 | $0.01358 |
| Sonnet 5.5 | $0.00063 | $0.00679 |
| Haiku 4.5 | $0.00031 | $0.00339 |
Grade A, and why
network-recon 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 2mo 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 — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Network Reconnaissance
Network reconnaissance is the systematic process of discovering hosts, mapping open ports, fingerprinting services and operating systems, and identifying vulnerabilities across target networks. It is the foundation of every penetration test -- everything downstream (web testing, exploitation, lateral movement) depends on the quality of your initial network recon.
Reconnaissance Methodology
Follow this sequence. Each phase feeds the next. Skip phases only when scope explicitly restricts them.
Phase 1 -- Passive Reconnaissance
Gather intelligence without sending a single packet to the target. This phase has zero detection risk.
Objectives: Identify IP ranges, ASNs, known services, historical scan data, DNS records.
# Passive subdomain enumeration
subfinder -d target.com -silent -o subdomains.txt
# OSINT-based port data (Shodan, Censys)
# Use ctx_execute or Hexstrike MCP tools for API queries
Integration: Store discovered targets immediately.
node ${CLAUDE_PLUGIN_ROOT}/scripts/target-intel.js add "target.com" network "passive-subdomains" "$(wc -l < subdomains.txt) subdomains found" --source "subfinder"
Phase 2 -- Host Discovery
Determine which hosts are alive before port scanning. Scanning dead hosts wastes time and generates noise.
Tool Selection:
- Same LAN: ARP scan (most reliable, cannot be firewalled)
- Remote targets: TCP SYN ping + ICMP + UDP combined
- Firewall-heavy: TCP ping on known-open ports (80, 443)
Load: ToolSearch -> select:mcp__hexstrike-ai__arp_scan_discovery (LAN targets)
# ARP discovery (local network only)
arp-scan --localnet --interface eth0
# Nmap host discovery combinations
nmap -sn -PE -PP -PS80,443,22 -PU53,161 -T3 10.0.0.0/24 # Standard
nmap -sn -PS80,443,8080,22,25 10.0.0.0/24 # TCP-only (ICMP blocked)
nmap -sn -PR 10.0.0.0/24 # ARP only (local subnet)
See references/host-discovery.md for complete host discovery methodology.
What ships with it
7 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.
- 2mo ago First seen · 325 lines · 314 tokens per session scan A 48dd9f145bc9
network-recon is a skill published in the GitHub repository ogrodev/fsociety (20 stars, last pushed 7mo ago), licensed MIT. It adds 314 tokens to every session and 3,394 once invoked, about $0.0013 per session on Opus 5.5. 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.
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