Performing Bluetooth Security Assessment

Performing Bluetooth Security Assessment

Overview

This skill covers performing Bluetooth Low Energy (BLE) security assessments using the Python bleak library. BLE devices are ubiquitous in IoT, healthcare, fitness, and smart home applications, and many ship with weak or absent security controls. This assessment identifies unencrypted GATT characteristics, devices broadcasting sensitive data, known vulnerable device fingerprints, and improperly secured pairing configurations.

The agent uses bleak's asyncio API to discover nearby BLE devices, connect to target devices, enumerate all GATT services and characteristics, and analyze security properties of each characteristic. It flags characteristics that allow unauthenticated read/write access to sensitive data and identifies devices matching known vulnerable profiles.

When to Use

• When conducting security assessments that involve performing bluetooth security assessment
• When following incident response procedures for related security events
• When performing scheduled security testing or auditing activities
• When validating security controls through hands-on testing

Most Often Missed & How to Confirm

• Classic vs BLE scope: bleak only covers Bluetooth Low Energy. Bluetooth Classic (BR/EDR) devices and profiles (SDP, RFCOMM) won't appear in a BLE scan — assess them separately with hcitool, sdptool browse, and bettercap's ble.recon/Classic modules.
• Discoverable vs non-discoverable: a device not advertising is not absent. Non-discoverable peripherals and randomized resolvable private addresses (RPA) hide from passive scans; don't conclude "nothing here" from a single BleakScanner.discover() pass.
• Pairing mode matters: "Just Works" pairing provides no MITM/eavesdropping protection (TK=0) yet often presents as "paired/secure." Inspect the actual IO capabilities and auth requirements rather than trusting the connection state.
• Enumeration depth: flag characteristics with read/write/write-without-response reachable without authentication, and sensitive GATT services (Heart Rate 0x2A37, Device Information, Battery) that should require encryption but allow unauthenticated reads.
• How to confirm a finding: corroborate the bleak results with independent tools — hcitool lescan and gatttool --primary/--characteristics for service/characteristic enumeration, and bettercap (ble.enum) — then prove the weakness by actually performing an unauthenticated read/write of the flagged characteristic. A property listed as write in the GATT table is not confirmed exploitable until an unauthenticated write succeeds end-to-end.

Prerequisites

• Python 3.9 or later
• bleak library (pip install bleak)
• Bluetooth adapter supporting BLE (Bluetooth 4.0+)
• Linux: BlueZ 5.43+ with D-Bus permissions
• Windows: Windows 10 version 1709+ with Bluetooth support
• macOS: macOS 10.15+ with CoreBluetooth

Steps

1. Scan for BLE devices: Use BleakScanner to discover all advertising BLE devices within range. Capture device name, address (MAC), RSSI signal strength, and advertised service UUIDs.

2. Identify target devices: Filter discovered devices by name pattern, address, or minimum signal strength. Flag devices broadcasting default or well-known vulnerable names.

3. Connect and enumerate GATT services: Use BleakClient to connect to the target device and iterate over all GATT services. For each service, record the UUID, description, and contained characteristics.

4. Analyze characteristic properties: For each characteristic, examine its properties (read, write, write-without-response, notify, indicate). Flag characteristics that expose read or write access without requiring authentication or encryption.

5. Check for known vulnerable UUIDs: Compare discovered service and characteristic UUIDs against a database of known vulnerable or sensitive services (Heart Rate, Blood Pressure, Device Information, Battery Level) that should require encryption.

6. Detect unencrypted data exposure: Attempt to read characteristics that should be protected. Successful unauthenticated reads of sensitive data indicate missing security controls.

7. Generate security report: Compile all findings into a structured JSON report with severity classifications and remediation recommendations.

Expected Output

{
  "assessment_type": "ble_security_audit",
  "target_device": {
    "name": "SmartBand-XR",
    "address": "AA:BB:CC:DD:EE:FF",
    "rssi": -42
  },
  "services_found": 5,
  "characteristics_found": 18,
  "findings": [
    {
      "severity": "high",
      "finding": "Heart Rate Measurement readable without encryption",
      "uuid": "00002a37-0000-1000-8000-00805f9b34fb",
      "properties": ["read", "notify"],
      "remediation": "Enable encryption requirement on characteristic"
    }
  ],
  "risk_score": 7.5
}