Can Hackers Take the Wheel? The Real Cybersecurity Risks of Self‑Driving Cars

Picture this: you’re cruising in a self-driving car, coffee in hand, eyes on the horizon. Then a thought hits—if this car makes decisions by itself and talks to the internet, could someone else talk to it too? Could a hacker take the wheel?

That question isn’t paranoia. It’s smart. Autonomous vehicles (AVs) blend complex software, AI, sensors, and connectivity into a rolling computer with real-world consequences. And while the tech promises safer roads and less stress, it also introduces new kinds of risk.

In this guide, we’ll break down how autonomous cars work, where cyber threats actually lie, what real-world hacks have taught us, and how the auto industry is defending against attacks. No fear-mongering, no jargon soup—just a clear, practical look at the cybersecurity of self-driving cars and what it means for you.

Let’s drive in.

How Self‑Driving Cars Think and Talk: The Attack Surface, Explained

To understand the risk, it helps to know what’s under the hood—digitally speaking.

The digital stack of an autonomous car

Self-driving systems combine a few core pieces:

Sensors: LiDAR, radar, cameras, ultrasonic sensors, GPS, IMU (inertial measurement).
Compute: Onboard high-performance computers running perception, prediction, and planning.
Control: Electronic control units (ECUs) for steering, braking, throttle.
Networks: In-vehicle networks like CAN/CAN-FD, Ethernet, LIN, FlexRay connecting ECUs.
Software: Millions of lines of code plus machine learning models.
Connectivity: Cellular (LTE/5G), Wi‑Fi, Bluetooth, GPS, sometimes V2X for vehicle-to-everything communication.
Cloud: Map updates, telematics, over‑the‑air (OTA) firmware updates, remote diagnostics.

If a laptop is a computer on your desk, an autonomous vehicle is a computer on wheels—with a physical world interface.

Where connectivity opens doors—for good and for risk

Connectivity enables great features: live traffic, remote start, software updates. It also expands the “attack surface”—the places an attacker could try to gain access.

Common entry points include:

Cellular connections and telematics units
OTA update systems
Companion mobile apps and APIs
Bluetooth and Wi‑Fi
V2X radios (DSRC or C‑V2X) where deployed
Physical ports like OBD‑II
Third-party dongles (insurance, fleet trackers)
Cloud services tied to the vehicle

Here’s why that matters: if a vulnerability exists in one place, skilled attackers may pivot through in-vehicle networks to more sensitive systems. That’s hard to do on modern designs—but not impossible, as history shows.

The Cybersecurity Risks of Connected and AI‑Driven Vehicles

Self-driving cars aren’t “hackable” in a single monolithic way. Different threats target different layers. Let’s break those down.

1) Remote control via telematics or infotainment

Infotainment systems are internet-connected computers. If an attacker exploits a software bug in a cellular modem, a browser component, or a media service, they could gain a foothold. From there, the goal would be to reach safety-critical ECUs—steering, braking—through the vehicle’s internal network.

Modern vehicles use gateways, segmentation, and firewalls to stop this. But misconfigurations or unpatched bugs can create openings.

Famous example: the 2015 Jeep Cherokee hack where researchers remotely controlled steering and brakes via the cellular-connected head unit. The automaker issued a recall after the disclosure. You can read the original report in Wired’s coverage of that research by Charlie Miller and Chris Valasek: Wired: Hackers Remotely Kill a Jeep on the Highway.

2) Sensor spoofing and tricking the AI

Autonomous systems rely on sensor input. If that input is manipulated, the system may make unsafe choices.

Known techniques include:

GPS spoofing: Faking satellite signals to mislead location/speed. Researchers at the University of Texas demonstrated GPS spoofing against vehicles and ships; see their work on GPS spoofing in the physical world: UT Austin Radionavigation Lab.
LiDAR/radar spoofing: Injecting phantom objects or masking real ones using crafted signals or projectors. A notable study shows “phantom” images can trick ADAS to brake: Ben-Gurion University: Phantom of the ADAS.
Adversarial examples: Subtle patterns on signs or road markings designed to fool vision models. See the classic “robust physical-world” attacks on image classifiers: Robust Physical-World Attacks on ML Models.

Well-designed AVs use sensor fusion and plausibility checks to reduce risk. If LiDAR says “object ahead” but radar disagrees, the system can cross-check. Still, the area remains active research.

3) Supply chain and software dependencies

Modern cars include hundreds of third-party components, open-source libraries, and vendor firmware. A bug in any one can create a vulnerable path. That’s why SBOMs (software bills of materials), patch management, and secure update processes are becoming mandatory.

Regulators and standards bodies now expect automakers to manage this risk, notably with ISO/SAE 21434 and UNECE WP.29 R155/R156 (more on those below).

4) Mobile apps and account takeover

If your vehicle ties to a mobile app—for unlocking, summoning, or climate control—then your car’s security partially depends on your account security. Weak passwords, reused credentials, or SMS-based 2FA can create opportunities for attackers. Protect the account like you would online banking.

5) Physical access and aftermarket devices

An attacker with physical access has more options. For example, plugging into the OBD‑II port or installing a compromised dongle. That’s one reason fleets lock diagnostic ports and manage accessories tightly.

6) Cloud and backend compromise

Connected vehicles talk to cloud services. If a backend is breached, large-scale attacks become possible—think mass credential resets, malicious OTA updates (if code signing is bypassed), or data exfiltration. Automakers run their cloud with strict security controls, but the risk is real and attracts advanced threat actors.

Real‑World Car Hacks: What Actually Happened (and What Changed)

Here are some of the most instructive, credible examples—and how they moved the industry forward.

Jeep Cherokee (2015): Researchers remotely exploited the Uconnect infotainment system via cellular, then pivoted to control steering and braking. FCA recalled 1.4 million vehicles. It was a turning point in automotive cybersecurity awareness. Source: Wired coverage.
BMW ConnectedDrive (2015): The ADAC (German automobile club) found that BMW’s ConnectedDrive used unencrypted communications that could be spoofed to unlock doors. BMW patched the issue quickly. Coverage: BMW press release archive.
Tesla research (2016–2020): Tencent Keen Security Lab demonstrated multiple vulnerabilities, including remote control of vehicle functions and Autopilot lane-keeping manipulation. Tesla patched via over-the-air updates and has a robust bug bounty program. See Keen Security Lab research and Tesla’s Bug Bounty.
Tire Pressure Monitoring Systems (TPMS) (2010): Researchers showed TPMS RF communications could be spoofed, causing false warnings and potential driver distraction. Academic paper via USENIX: Security and Privacy Vulnerabilities of TPMS.
V2X security foundations: To prevent spoofed messages in vehicle-to-infrastructure communication, the US developed a Security Credential Management System (SCMS) for signing V2X messages. See the USDOT explainer: USDOT V2X Security.

These aren’t hypotheticals. They led to systemic changes: signed OTA updates, stronger segmentation, encrypted comms, gateway ECUs, and formal cybersecurity engineering programs across the industry.

Could Hackers Actually Control a Self‑Driving Car?

Short answer: It’s possible under specific conditions, but it’s getting harder every year.

Here’s the nuance:

An attacker would typically need an exploitable vulnerability in a remote interface (cellular, Wi‑Fi, app API), then a way to pivot from non-safety domains (infotainment/telematics) to safety-critical ECUs.
Modern vehicles use gateway firewalls, domain separation, and strict message validation to block that pivot.
Critical functions often require additional safeguards: state checks, speed thresholds, driver presence detection, or redundant safety monitors that can override the main controller.
AV stacks add another layer of defense: if a critical anomaly is detected, the vehicle may default to a safe stop.

That said, software is complex, and perfect security doesn’t exist. The industry’s goal is layered defenses and fast, remote patching when vulnerabilities are discovered. It’s a continuous race—much like cybersecurity in aviation and cloud.

For balanced perspective: widespread “carjacking by internet” isn’t something we see in the wild today, but research shows it’s not fantasy if complacency sets in. Security-by-design and constant vigilance are key.

How Automakers Secure Self‑Driving Technology

Cybersecurity isn’t a bolt-on. It’s a product discipline built into the car’s life cycle—from concept to decommissioning.

Security by design and standards

ISO/SAE 21434: The global standard for automotive cybersecurity engineering. It defines processes for risk assessment, design, verification, and incident response across the vehicle life cycle. Overview: ISO/SAE 21434.
UNECE WP.29 R155/R156: Regulations requiring a Cybersecurity Management System (R155) and secure Software Update Management System (R156) for vehicles in many markets (EU, Japan, others). Summary: UNECE R155/R156.

Regulatory pressure has made cybersecurity a “must-pass” gate for type approval in numerous countries.

In-vehicle defenses

Segmentation and gateways: Separate infotainment from drivetrain. Enforce allowlists. Rate-limit and sanitize messages across domains.
Secure boot and hardware roots of trust: Ensure ECUs run only signed, verified firmware. Thwart persistent malware.
Cryptography on in-vehicle networks: CAN was designed without security; newer approaches add message authentication (e.g., AUTOSAR SecOC, CAN‑FD with MACs) and secure on-vehicle Ethernet.
Intrusion detection systems (IDS): Monitor network traffic for anomalies (unexpected diagnostics, spoofed IDs).
Hypervisors and isolation: Partition safety and non-safety workloads on the same hardware with strong isolation.
Safety monitors: Independent microcontrollers that can override or safely bring the car to a stop if the primary system misbehaves.

Sensor and AI resilience

Sensor fusion and plausibility checks: Cross-validate LiDAR, radar, and vision. Reject impossible combinations (e.g., “object appears at 100 mph from nowhere”).
Map and localization sanity: Compare live observations with HD maps; alert on mismatches.
Adversarial robustness: Train and test models against adversarial patterns; use confidence thresholds and fallback behaviors.
Redundancy: Multiple sensing modalities reduce single-point failures.

OTA updates that don’t become attack vectors

Code signing and verification: Only cryptographically signed firmware is accepted.
Staged rollouts and rollback protection: Limit blast radius, prevent downgrade attacks.
Secure update channels: TLS with pinning, device-bound keys, hardware-backed key storage.

For a good high-level guide, see NHTSA’s best practices: NHTSA Cybersecurity Best Practices for the Safety of Modern Vehicles.

Cloud and data security

Zero-trust architecture: Strong service identity and least privilege between cloud components.
Continuous monitoring: SIEM, anomaly detection, and alerting for backend services and fleet telemetry.
SBOM and vulnerability management: Track dependencies, prioritize fixes, and patch fast when CVEs hit.

People and process

Threat analysis and risk assessment (TARA) early in design.
Secure SDLC: Code review, static/dynamic analysis, fuzzing, and third-party pen testing.
PSIRT: A product security incident response team to triage, fix, and communicate vulnerabilites quickly.
Bug bounties: Incentivize responsible disclosure. Tesla, BMW, GM, and others run or participate in programs. Example: Tesla Bug Bounty.

The headline: The playbook is maturing. The auto industry is moving closer to aerospace-level rigor, because the stakes demand it.

What This Means for Drivers, Riders, and Fleets

You can’t control the code inside your car, but you can control your risk posture. A few practical steps go a long way.

For everyday drivers

Keep software updated: Accept OTA updates from your automaker. They often include security fixes.
Secure your account: Use a strong, unique password and hardware or app-based 2FA for vehicle apps. Avoid SMS if stronger options exist.
Limit aftermarket add‑ons: Be cautious with OBD‑II dongles, trackers, and third-party accessories. If you must, buy from reputable vendors and remove devices you don’t actively use.
Review privacy and connectivity settings: Turn off services you don’t need. Remove old driver profiles and app authorizations.
Be Bluetooth‑smart: Pair only with devices you trust. Delete old pairings. Disable discoverability when not needed.
Physical security still matters: Lock the car, store keys in a signal-blocking pouch if relay attacks are a concern, and don’t leave diagnostic ports accessible.
Watch for weird behavior: Unusual alerts, sudden reboots, or phantom lock/unlock events warrant a service check.

For fleets, mobility services, and AV operators

Demand standard compliance: Require ISO/SAE 21434 and UNECE R155/R156 compliance in procurement.
Control the stack: Validate suppliers, require SBOMs, and insist on signed OTA pipelines with rollback control.
Lock down devices: Use MDM for driver phones, control app permissions, and limit USB/Bluetooth ports in fleet configurations.
Network segmentation: If vehicles connect to enterprise networks, keep them segmented and monitored.
Log and monitor: Collect telematics, security events, and update status; set thresholds for anomaly alerts.
Train staff: Phishing and social engineering can lead to account takeover. Make security hygiene routine.
Build an IR plan: Practice response for lost credentials, compromised dongles, or suspected vehicle tampering.

Small steps compound into real resilience.

The Stakes: Why Securing Autonomous Vehicles Is Non‑Negotiable

The benefits of autonomy are compelling: fewer crashes, smoother traffic, mobility for people who can’t drive today. But cyber and safety are now intertwined.

Cyber is physical: A car isn’t a laptop. A compromised vehicle can cause kinetic harm. The risk calculus is different.
Scale cuts both ways: OTA updates can patch millions of cars overnight. But the same distribution channel must be ironclad to prevent malicious updates.
Attackers follow money and leverage: Ransomware against fleets, extortion tied to disruption, or supply chain compromises can pack outsized impact.
AI introduces new edges: We must treat sensor spoofing and adversarial ML as part of the security perimeter, not an academic oddity.

The good news: the field is moving fast, with regulation, standards, and real engineering muscle behind it. If we do this right, cybersecurity becomes a core safety feature—like airbags for the digital age.

Key Takeaways

Self-driving cars are highly connected computers on wheels. That connectivity creates convenience—and new cyber risks.
Real-world hacks have happened, but each one has pushed the industry to implement stronger defenses and rapid patching.
Can hackers take control? It’s possible under specific conditions, but defenses like segmentation, secure boot, IDS, and safety monitors make it increasingly difficult.
Automakers now follow rigorous standards (ISO/SAE 21434, UNECE R155/R156) and best practices from NHTSA to manage cyber risk end to end.
You play a role: update promptly, secure your accounts, minimize unvetted accessories, and stay alert for unusual behavior.

Curious to go deeper into the tech and the policy shaping it? Keep exploring—there’s a lot more under the hood.

FAQs: People Also Ask

Can someone hack my self‑driving car remotely?

It’s not common, and modern designs make it hard. Remote compromise would require a chain of vulnerabilities and bypassing multiple defenses. That said, past research shows it’s possible if systems aren’t patched or properly segmented. Keep your vehicle updated and secure your app accounts.

What are the biggest cybersecurity risks for autonomous cars?

Remote exploits via telematics/infotainment
Sensor spoofing and adversarial inputs
Vulnerabilities in third-party components
Mobile app and API weaknesses
Cloud/backend compromises
Physical access through OBD‑II or aftermarket devices

How do self‑driving cars defend against hackers?

With layers of defense: secure boot, signed OTA updates, gateway segmentation, IDS, cryptography on in-vehicle networks, sensor fusion checks, safety monitors, and strict cloud security. Standards like ISO/SAE 21434 and regulations like UNECE R155/R156 guide these controls.

Are over‑the‑air (OTA) updates safe?

When done right, yes. OTA systems should use end-to-end encryption, code signing, rollback protection, and staged rollouts. They actually improve safety by delivering patches quickly. See guidance from NHTSA.

Could a hacker take over steering or braking?

Research has shown it’s possible under certain conditions, usually by chaining multiple vulnerabilities. Modern vehicles add layers—gateways, message validation, safety controllers—that make this much harder. If an anomaly is detected, the vehicle should default to a safe state.

Can signs or stickers trick a self‑driving car?

Some studies show adversarial patterns can fool vision systems in controlled settings. Real systems use sensor fusion, confidence thresholds, and map checks to reduce this risk. See examples of physical-world ML attacks: arXiv: 1707.08945.

Is it safe to pair my phone with my car?

Generally yes, with good hygiene. Pair only trusted devices, delete old pairings, and keep your phone updated. Avoid pairing in public spaces if you can, and don’t accept unknown connection prompts.

What should I do if I suspect my car was hacked?

Power-cycle the infotainment system and see if the behavior persists.
Remove third-party dongles and accessories.
Change passwords on related apps; enable stronger 2FA.
Contact your automaker or dealer and file a support ticket.
If you believe safety is at risk, stop driving and request service.

What regulations cover automotive cybersecurity?

Key ones include UNECE WP.29 R155 (Cybersecurity Management System) and R156 (Software Updates). Many automakers also align with ISO/SAE 21434. NHTSA publishes best practices in the U.S.: NHTSA Vehicle Cybersecurity.

If you remember one thing, make it this: cybersecurity is now a core safety feature of self-driving cars. Ask your automaker how they build and maintain it, keep your software up to date, and treat your car’s login like a bank account. Want more deep dives on future tech and security? Stick around for the next article or subscribe for updates.

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