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 onfire7777/universal-ai-skills-library --skill analyzing-network-packets-with-scapygit clone --depth 1 https://github.com/onfire7777/universal-ai-skills-libraryWrote 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/onfire7777/universal-ai-skills-library/analyzing-network-packets-with-scapy)<a href="https://agentmods.dev/skills/onfire7777/universal-ai-skills-library/analyzing-network-packets-with-scapy"><img src="https://agentmods.dev/badge/skills/onfire7777/universal-ai-skills-library/analyzing-network-packets-with-scapy/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/onfire7777/universal-ai-skills-library/analyzing-network-packets-with-scapy"><img src="https://agentmods.dev/badge/skills/onfire7777/universal-ai-skills-library/analyzing-network-packets-with-scapy.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 | $0.00039 | $0.00482 |
| Opus 5 | $0.00019 | $0.00241 |
| Sonnet 5 | $0.00008 | $0.00096 |
| Haiku 4.5 | $0.00004 | $0.00048 |
Grade A, and why
analyzing-network-packets-with-scapy 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.
This is a copy
88% identical to analyzing-network-packets-with-scapy — 36 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Analyzing Network Packets with Scapy
Overview
Scapy is a Python packet manipulation library that enables crafting, sending, sniffing, and dissecting network packets at granular protocol layers. This skill covers using Scapy for security-relevant tasks including TCP/UDP/ICMP packet crafting, pcap file analysis, protocol field extraction, SYN scan implementation, DNS query analysis, and detecting anomalous traffic patterns such as unusually fragmented packets or malformed headers.
When to Use
- When investigating security incidents that require analyzing network packets with scapy
- 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
Prerequisites
- Python 3.8+ with
scapylibrary installed (pip install scapy) - Root/administrator privileges for raw socket operations (sniffing, sending)
- Npcap (Windows) or libpcap (Linux) for packet capture
- Authorization to perform packet operations on target network
Steps
- Read and parse pcap/pcapng files with
rdpcap()for offline analysis - Extract protocol layers (IP, TCP, UDP, DNS, HTTP) and field values
- Compute traffic statistics: top talkers, protocol distribution, port frequency
- Detect SYN flood patterns by analyzing TCP flag ratios
- Identify DNS exfiltration indicators via query length and entropy analysis
- Craft custom probe packets for authorized network testing
- Export findings as structured JSON report
Expected Output
JSON report containing packet statistics, protocol distribution, top source/destination IPs, detected anomalies (SYN floods, DNS tunneling indicators, fragmentation attacks), and per-flow summaries.
What ships with it
3 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 · 52 lines · 39 tokens per session scan A 0906d2aca3cb
analyzing-network-packets-with-scapy is a skill published in the GitHub repository onfire7777/universal-ai-skills-library (16 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 482 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to analyzing-network-packets-with-scapy, differing in 36 lines, and is treated as a copy.
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