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Offensive Krack Fragattacks

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SnailSploit
offensive-krack-fragattacks

KRACK (CVE-2017-13077..082) and FragAttacks (CVE-2020-24586..588 + 26139-26147) — key reinstallation, fragmentation, and aggregation attacks against WPA2 supplicants. Covers Vanhoef's test scripts, viability against modern patched stacks (mostly mitigated post-2021), residual unpatched embedded devices and IoT vendors, and the practical limitations of these attacks in modern engagements. Use when assessing legacy supplicants, embedded clients, or vendors with poor patch cadence.

Overview

PublisherSnailSploit
RepositoryClaude-Red
Skill nameoffensive-krack-fragattacks
Stars
7.4K
Forks
967
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by SnailSploit on GitHub. Read the source before you install it.

Installation

Install the Offensive Krack Fragattacks AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/SnailSploit/Claude-Red/tree/main/Skills/wireless/offensive-krack-fragattacks
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/SnailSploit/Claude-Red.git /tmp/Claude-Red
mkdir -p .claude/skills
cp -r /tmp/Claude-Red/Skills/wireless/offensive-krack-fragattacks .claude/skills/offensive-krack-fragattacks
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Offensive Krack Fragattacks in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Offensive Krack Fragattacks on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Offensive Krack Fragattacks is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

KRACK & FragAttacks

Two attack families against WPA2 client implementations. Both well-disclosed (KRACK 2017, FragAttacks 2021) and largely patched on modern OSes — but the embedded/IoT long tail keeps them in scope for many engagements.

When These Apply

FamilyTargetPatch Status
KRACKWPA2 supplicants in 4-way handshake / GTK / FT / TDLSMajor OSes patched 2017–2018
FragAttacksFrame fragmentation/aggregation across WPA2/3Most stacks patched 2021–2022

Probability of success today is high only against:

  • Embedded OEM devices (cameras, sensors, point-of-sale)
  • Old Android phones (<8 unpatched)
  • Industrial / SCADA Wi-Fi clients
  • Wi-Fi-enabled toys, smart bulbs, no-name IoT

Modern Win11 / iOS 16+ / Android 13+ / hostapd-2.10 are mitigated.

KRACK — Key Reinstallation

The 4-way handshake's M3 retransmission causes the supplicant to reinstall the same PTK with reset nonce/replay counters. Frames encrypted under the reused keystream become decryptable.

bash
# Vanhoef's official test scripts
git clone https://github.com/vanhoefm/krackattacks-scripts
cd krackattacks-scripts/krackattack
sudo ./krack-test-client.py --interface wlan0
# Tests the supplicant on a connected client

Output identifies which CVE variants the client is vulnerable to.

Practical Outcomes

When successful:

  • Decryption of WPA2-encrypted frames between client and AP
  • TKIP downgrade enables packet injection
  • Recovery of session keys for the duration of the affected key cycle

Not a PSK recovery — you don't get the wireless password from KRACK.

FragAttacks — Frame Splicing

FragAttacks abuse 802.11 fragmentation and aggregation to inject frames that mix encrypted and plaintext fragments, or to splice attacker-controlled fragments into legitimate frames.

bash
git clone https://github.com/vanhoefm/fragattacks
cd fragattacks
sudo ./test-fragattacks.py wlan0 --interface wlan0
# Suite of ~12 tests covering each variant
CVEMechanism
CVE-2020-24588A-MSDU spoofing — inject crafted A-MSDU subframes
CVE-2020-24587Mixed-key fragment cache poisoning
CVE-2020-24586Decoupled fragment cache → reuse
CVE-2020-26139Forwarding plaintext frames before authentication
CVE-2020-26140Accepting plaintext frames in protected network

Practical Outcomes

  • Inject malicious frames that the client treats as legitimate (HTTP redirect, DNS poison)
  • Read decrypted fragments from cached state
  • Cross-protect data exfil via crafted A-MSDU

Targeting Workflow

  1. Identify the in-scope client (MAC, OS, vendor)
  2. Estimate patch likelihood — if modern OS, likely patched; if embedded, likely vulnerable
  3. Run the test suite from a controlled AP setup
  4. Report each vulnerable variant separately with the matching CVE
bash
# Rogue AP that drives the test
sudo hostapd-mana /tmp/krack_test_ap.conf

# Force client to associate (deauth from real AP, or social-engineer)
sudo aireplay-ng --deauth 5 -a <real-BSSID> -c <client-MAC> wlan0mon

# Run test once associated
sudo ./krack-test-client.py --interface wlan0

Detection

  • WIPS may flag deauth-driven roams to attacker AP
  • Test scripts generate distinctive frame patterns; modern WIPS recognizes Vanhoef's tooling
  • Successful exploitation is essentially silent at protocol level

Reporting

For each vulnerable CVE:

  • Client model + firmware version (be specific)
  • Variant tested + result (vulnerable / patched / partial)
  • Practical impact in the engagement context (decryption only, or injection viable?)
  • Remediation: vendor patch URL, mitigation (WPA3 + PMF blocks most)

Key References

Frequently asked questions

What does the Offensive Krack Fragattacks AI skill do?

KRACK (CVE-2017-13077..082) and FragAttacks (CVE-2020-24586..588 + 26139-26147) — key reinstallation, fragmentation, and aggregation attacks against WPA2 supplicants. Covers Vanhoef's test scripts, viability against modern patched stacks (mostly mitigated post-2021), residual unpatched embedded devices and IoT vendors, and the practical limitations of these attacks in modern engagements. Use when assessing legacy supplicants, embedded clients, or vendors with poor patch cadence.

Why use Offensive Krack Fragattacks on TypingMind?

Because you install it once and use it with any model. Offensive Krack Fragattacks is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Offensive Krack Fragattacks in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SnailSploit/Claude-Red/tree/main/Skills/wireless/offensive-krack-fragattacks. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Offensive Krack Fragattacks?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Offensive Krack Fragattacks?

As many as you like. As long as a model supports skills, you can use Offensive Krack Fragattacks with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Offensive Krack Fragattacks AI skill free?

Yes. It is published on GitHub by SnailSploit under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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