Security flaw accidentally gave one man control of 7,000 robot vacuums

A startling wake-up call for smart home security

A routine tinkering project turned into a sweeping privacy scare when a software developer accidentally gained control of approximately 7,000 robot vacuums. While building a custom app to drive his own device with a PlayStation controller, the engineer, Sammy Azdoufal, uncovered a backend security flaw that granted him access to other users' live camera feeds, microphone audio, maps, and device data.

The affected model, DJI's Romo robot vacuum, relies on cloud connectivity to function and store data. Azdoufal reported the vulnerability to the company immediately. DJI says it has since patched the issue and deployed fixes that did not require customer action. Even so, the episode underscores a hard truth about connected homes. Smart devices can be remarkably helpful, but they also create attractive targets for attackers and can expose intimate details of our lives.

"Let other users be the beta testers so the company will fix the issue before you buy it," Azdoufal suggested after reporting the flaw.

How a hobby project turned into a massive security discovery

It began as a simple idea. Azdoufal wanted to steer his new vacuum with a game controller for fun. To do that, he needed to understand how the robot communicated with the company's cloud servers and how the official app validated that he was the rightful owner of the device. He reportedly used an AI coding assistant to speed up reverse engineering.

Then the scope widened. Instead of receiving a token limited to his household, Azdoufal found that the cloud backend granted him broad access. The same credentials that authenticated his own vacuum opened the door to data and live streams from thousands of other robots across at least 24 countries. In other words, the service appeared to treat him as if he were the owner of many devices, not just his own.

The implications were immediate. With those permissions, he could see real-time video and listen via microphones, review 2D floor plans, check status data, and infer approximate locations from IP information. He emphasizes that he did not exploit the access beyond verifying the issue. He disclosed the problem quickly to minimize harm.

What, exactly, was at risk

Robot vacuums collect intimate information by design. To navigate and avoid hazards, modern models use cameras, microphones, lidar, and other sensors. They create persistent maps of rooms, identify furniture and floor types, and learn routines. That data can reveal when you are home, what your layout looks like, and where valuables might be located.

Centralized cloud control raises the stakes. When devices offload video, audio, maps, and telemetry to remote servers, any flaw in authentication can become a single point of failure. In this case, one misapplied token scope or permission check appears to have unlocked access at scale. A malicious actor could have used that access to surveil households, profile occupants, or plan physical intrusions without ever setting foot inside.

Access was silent and invisible to owners. Owners reportedly received no alerts when someone connected to their feeds. That lack of user transparency is common across many smart home ecosystems and remains a serious concern. Silent access is convenient for support tools, but it becomes a liability when security breaks down.

DJI's response and the patch timeline

The company says it acted quickly. DJI stated it identified a vulnerability impacting its DJI Home service during internal review in late January and began remediation immediately. According to the company, an initial patch rolled out on February 8, followed by a second update on February 10. The fix was deployed automatically. Users were not required to install anything manually.

Ongoing hardening efforts are promised. DJI says it will continue to implement additional security enhancements, though it has not specified which measures are next. Standard industry practices in these situations include tightening token scopes, adding layered authentication checks, and increasing internal monitoring for abnormal access patterns.

Disclosure helped reduce harm. Azdoufal chose not to exploit or publicize live device data and instead worked with journalists to notify the company. This type of coordinated disclosure can limit opportunistic abuse while giving manufacturers time to patch issues.

Why robot vacuums pose unique privacy risks

They live in your most private spaces. Unlike a smart light bulb or thermostat, a robot vacuum physically roams through bedrooms, offices, and nurseries. It sees daily routines, obstacles on the floor, and the shape of your home. Those details, aggregated over time, can paint a detailed picture of your life.

They are getting smarter and more connected. Newer models integrate powerful vision systems, on-device machine learning, and cloud analytics. That can improve performance, but it also means more sensitive data in motion and at rest. Some vendors retain maps and clips for training or user convenience, which increases the potential blast radius during a breach.

Small mistakes can have big consequences. A single misconfigured permission can expose thousands of households. When devices are tightly coupled to cloud backends, errors scale quickly. This latest incident is a stark reminder that convenience and connectivity need to be balanced with rigorous security engineering.

The bigger smart home privacy picture

Consumer trust is already strained. Recent debates over connected doorbells, virtual assistants, and cloud video retention have raised questions about how much control users have over their data. Even when companies promise deletion, law enforcement requests or backup policies can complicate matters.

Policy scrutiny will intensify. Some lawmakers have warned about risks tied to connected devices from foreign manufacturers. Others are pushing for broader IoT security standards regardless of origin. The core issue is not just where a device is built. It is how it authenticates, stores, encrypts, and deletes sensitive data over time.

Adoption keeps accelerating. More than half of U.S. households have at least one smart home device, and many plan to add more. As homes fill with cameras, microphones, and mobile robots, the attack surface grows. Without better defaults and clear transparency, incidents like this one will recur.

The AI angle: easier to build, easier to break

AI coding assistants lower barriers for tinkerers and attackers. Tools that help generate code and explain APIs can make it easier to connect products and personalize setups. The flip side is that people with modest experience can also probe cloud services and discover mistakes that once required deeper expertise.

Expect more accidental red team moments. As more hobbyists remix hardware and software, they will inevitably uncover latent vulnerabilities. That can be a net positive if companies welcome responsible reporting and respond quickly. It also means manufacturers need to assume that curious users will test every corner of their systems.

Security must keep pace with democratized development. Threat models should account for rapid, AI-assisted experimentation. Least privilege by default, strict token scoping, and continuous automated tests for authorization boundaries are no longer optional. They are table stakes.

What could have gone wrong if this landed in the wrong hands

Covert home surveillance. Continuous access to microphones and cameras could enable eavesdropping on conversations, capturing private moments, or monitoring routines without detection.

Physical security risks. Floor maps and device status can reveal when rooms are occupied, where high value items may be located, and when a home is likely empty. Combined with location hints, this could facilitate targeted crimes.

Harassment and stalking. Unauthorized access to a device inside a residence opens the door to stalking or coercion, especially when victims are unaware that a device is being misused.

Reputation and trust damage. Even a quickly patched incident can erode consumer confidence, which can have long term effects on adoption of helpful automation technologies.

What consumers can do right now

You should not have to be your own CISO, but a few steps help.

• Keep firmware and apps updated. Turn on automatic updates wherever possible so security fixes install quickly.
• Segment your home network. Place smart devices on a separate guest or IoT Wi-Fi network to limit lateral movement if one device is compromised.
• Review permissions and cloud settings. Disable unnecessary microphone or camera features if your robot offers them. Opt out of cloud storage or video upload when you can.
• Use strong, unique passwords and MFA. Protect device accounts and cloud portals with a password manager and enable multi factor authentication.
• Check vendor track records. Look for companies with transparent security policies, public vulnerability disclosure programs, and prompt patch histories.
• Be a late adopter for first gen products. Waiting a few months can let manufacturers harden systems and fix early bugs.

Buying checklist for privacy focused shoppers

Before bringing a robot into your home, ask:

• Does the device work locally without the cloud, or is cloud required?
• How long are maps, video, and audio retained, and where?
• Can I delete my data, and is deletion permanent?
• Is there a clear vulnerability disclosure policy and bug bounty?
• Does the app notify me when live access is active?

What manufacturers need to change

Security by design, not by patch. Avoid single tokens or credentials that grant broad access. Use fine grained, device scoped authorization and short lived tokens. Enforce server side checks that cannot be bypassed by client side manipulation.

Minimize and localize data. Process maps and media locally when feasible. When cloud services are necessary, encrypt data end to end and reduce retention to the shortest practical window. Make user deletion clear and trustworthy.

Monitor and test continuously. Adopt automated authorization tests, anomaly detection for unusual access patterns, and independent security audits. Publish transparency reports and timelines when incidents occur.

Empower users with visibility. Provide clear logs and real time notifications for remote access. Let owners see when streams are live, who accessed them, and from where, and offer easy controls to revoke access.

Regulators and standards can help

Labeling and baselines matter. IoT security labels and minimum baselines for authentication, encryption, and update policies can raise the floor across the industry. Clear, comparable labels help consumers make informed choices.

Data minimization and user rights. Rules that limit retention of sensitive home data and mandate straightforward deletion and export can reduce long term exposure. Consistent requirements across vendors would protect consumers without stifling innovation.

Coordinated vulnerability disclosure. Encouraging responsible reporting, shielding good faith researchers, and requiring timely remediation are practical steps to improve outcomes when inevitable flaws surface.

Home robots are coming fast. Security must keep up

The next wave will be even more capable. Companies are racing to bring more advanced home robots to market, including models that interact, manipulate objects, and learn from their environments. To perform these tasks, they will need deeper awareness of homes and routines.

The upside is real, and so are the risks. From cleaning to elder care, robots can add convenience and safety. But the stakes are higher than a light switch. The industry must treat privacy and security as core product features, not add ons.

This incident is a cautionary tale. One curious user, aided by modern coding tools, stumbled into access that could have become a surveillance nightmare. The quick patch is good news. The lesson is better defaults, better guardrails, and better accountability.

Key takeaways

• A single flaw exposed thousands of devices. A cloud authentication bug let a developer access live streams and maps from about 7,000 robot vacuums.
• DJI says it patched the issue quickly. Fixes were deployed automatically in early February, with no user action required.
• Robot vacuums collect sensitive data by design. Cameras, microphones, and detailed maps make them powerful tools and high value targets.
• AI tools are changing the security landscape. Easier reverse engineering raises the bar for manufacturers to implement least privilege and robust authorization.
• Consumers can reduce risk. Update devices, segment networks, review permissions, and choose vendors with strong security practices.
• Manufacturers and policymakers must do more. Security by design, data minimization, transparent access logs, and baseline standards are essential as home robots proliferate.