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Agents35k · #5642

detecting-bluetooth-low-energy-attacks

Lets your agent detect and analyze attacks using low-energy Bluetooth. It monitors the security of IoT devices.

What it does

This tool helps find and analyze attacks on Bluetooth Low Energy (BLE) connections. It can identify if someone is trying to snoop, repeat commands, or intercept your communications.

When to use it

  • ✓When testing the security of smart devices (IoT, locks).
  • ✓When monitoring the environment for suspicious Bluetooth activity.
  • ✓When analyzing Bluetooth communication data to find vulnerabilities.

Example of what to ask your AI

“Check for eavesdropping or replay attacks on my Bluetooth devices.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/mukul975/Anthropic-Cybersecurity-Skills/blob/main/skills/detecting-bluetooth-low-energy-attacks/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/mukul975/Anthropic-Cybersecurity-Skills/blob/main/skills/detecting-bluetooth-low-energy-attacks/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

It uses special equipment (like Ubertooth One) to capture Bluetooth data and software to analyze this data for malicious activity.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-bluetooth-low-energy-attacks

Or download just the file:

curl -L https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/detecting-bluetooth-low-energy-attacks/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Detecting Bluetooth Low Energy Attacks

Disclaimer

This skill is intended for authorized security testing, penetration testing engagements, CTF competitions, and educational purposes only. Sniffing, intercepting, or manipulating Bluetooth communications without authorization may violate federal wiretapping laws and local regulations. Always obtain explicit written permission before conducting any wireless security assessment.

When to Use

Use this skill when:

  • Performing authorized BLE security assessments of IoT devices, medical devices, or smart locks
  • Monitoring a wireless environment for BLE-based replay attacks, spoofing, or unauthorized enumeration
  • Analyzing BLE packet captures to detect Man-in-the-Middle attacks or pairing exploitation
  • Enumerating GATT services and characteristics to identify insecure read/write permissions on BLE peripherals
  • Assessing BLE encryption strength and testing for crackable pairing exchanges
  • Building BLE intrusion detection capabilities for wireless security monitoring

Do not use for intercepting BLE communications without explicit authorization. Do not deploy BLE scanning tools in environments where wireless monitoring is prohibited.

Prerequisites

  • Ubertooth One hardware for passive BLE sniffing, or Nordic nRF52840 USB Dongle with nRF Sniffer firmware
  • Python 3.10+ with pip
  • bleak library: pip install bleak (cross-platform BLE GATT client)
  • Wireshark with BLE dissector plugins for packet analysis
  • crackle tool for BLE encryption analysis: built from source at github.com/mikeryan/crackle
  • ubertooth-btle CLI tools: apt install ubertooth (Linux) or build from source
  • Bluetooth 4.0+ adapter on the host system for bleak-based scanning
  • Linux recommended for full Ubertooth/nRF sniffer support

Workflow

Step 1: BLE Environment Discovery and Device Scanning

Scan the environment to identify BLE devices and their advertising data:

# Scan for BLE devices using bleak (cross-platform)
python -c "
import asyncio
from bleak import BleakScanner

async def scan():
    devices = await BleakScanner.discover(timeout=10.0)
    for d in devices:
        print(f'{d.address} | RSSI: {d.rssi} | Name: {d.name or \"Unknown\"}')
        for uuid in d.metadata.get('uuids', []):
            print(f'  Service: {uuid}')

asyncio.run(scan())
"

# Passive BLE sniffing with Ubertooth One (promiscuous mode)
ubertooth-btle -p -r capture.pcapng

# Follow a specific BLE connection
ubertooth-btle -f -t AA:BB:CC:DD:EE:FF -r connection.pcapng

# Use nRF Sniffer with Wireshark (via extcap interface)
wireshark -i nRF_Sniffer -k

Step 2: GATT Service and Characteristic Enumeration

Connect to target BLE peripherals and enumerate their GATT profile:

# Enumerate all services, characteristics, and descriptors
python -c "
import asyncio
from bleak import BleakClient

async def enum_gatt(address):
    async with BleakClient(address) as client:
        print(f'Connected: {client.is_connected}')
        for service in client.services:
            print(f'Service: {service.uuid} - {service.description}')
            for char in service.characteristics:
                props = ','.join(char.properties)
                print(f'  Char: {char.uuid} | Props: {props}')
                for desc in char.descriptors:
                    val = await client.read_gatt_descriptor(desc.handle)
                    print(f'    Desc: {desc.uuid} = {val}')

asyncio.run(enum_gatt('AA:BB:CC:DD:EE:FF'))
"

Security-relevant findings during GATT enumeration:

  • Characteristics with write-without-response or write without authentication
  • Readable characteristics exposing device configuration, credentials, or firmware versions
  • Missing Client Characteristic Configuration Descriptor (CCCD) protection on notification characteristics

Step 3: BLE Packet Capture and Analysis

Capture BLE traffic for offline analysis:

# Capture with Ubertooth in PcapNG format (recommended)
ubertooth-btle -f -r capture.pcapng

# Capture in PCAP/PPI format for crackle compatibility
ubertooth-btle -f -c capture_ppi.pcap

# Analyze capture in Wireshark
wireshark capture.pcapng
# Apply display filter: btle
# Filter connection requests: btle.advertising_header.pdu_type == 0x05
# Filter data packets: btle.data_header

# Extract pairing information with tshark
tshark -r capture.pcapng -Y "btle.control_opcode == 0x01" -T fields \
  -e btle.master_bd_addr -e btle.slave_bd_addr

…

FAQ

Do I need special equipment?

Yes, you will need hardware like the Ubertooth One or an nRF52840 dongle, and you'll need to install specific software on your computer.

Can I use this on any Bluetooth device?

This tool focuses on Bluetooth Low Energy (BLE). It also requires explicit permission for security testing.

Is it difficult to use?

It requires technical knowledge to set up the hardware and use the commands. It's not a tool for beginners without guidance.

Details

Original description by the author

Detects and analyzes Bluetooth Low Energy (BLE) security attacks including sniffing, replay attacks, GATT enumeration abuse, and Man-in-the-Middle interception. Uses Ubertooth One and nRF52840 sniffers for packet capture, the bleak Python library for GATT service enumeration, and crackle for BLE encryption cracking. Use when assessing IoT device BLE security, monitoring for BLE-based attacks on wi

repo: mukul975/Anthropic-Cybersecurity-Skills

Popularity

GitHub stars
35k
Ranking position
#5642
License
Apache-2.0
Updated
8/31/2026

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