AI Security: Is Hugging Face Safe to Use?

⚠️ Over 2.2 million AI models on Hugging Face were scanned for threats by VirusTotal.
🔍 VirusTotal uses over 70 malware engines to find bad behaviors in AI models.
🤖 Hugging Face now shows security scan results publicly on each model’s page.
🛡️ AI security is not just an option anymore; there are real risks like hidden shells, bad data, and remote code running.
🔧 Platforms like Bot-Engine now automatically put in checked models, lowering risk for users who are not tech experts.

Open-source AI tools have made machine learning available to more people. Anyone—from new businesses to big companies—can now use models with little technical skill. But this ease creates big security holes. Recent work between Hugging Face and VirusTotal is a big step forward in AI security. This helps make sure powerful tools do not come with hidden dangers.

Why AI Security Matters Now More Than Ever

Many industries now use AI. It is not only data scientists and engineers who are using it. AI models are quickly being used in:

Customer service through chatbots
Making marketing text
Email automation and outreach
Social media auto-responders
Tools that change voice to text and summarize text

And thanks to platforms like Bot-Engine, users can do all this without much technical skill. But, like any open platform, this convenience has big risks.

Imagine if you use a language model in your sales process, and then find out it is leaking private customer information. Or maybe it has hidden code that sends data to an unknown server. Also, it might give very rude or wrong answers because of bad training data. These things are real; they have happened.

Without good protection, if you use a model that has not been checked in your work, it can:

Leak private customer or company information
Do things it is not supposed to
Give wrong or rude answers
Talk to other systems you do not know about

And in business, even a small mistake can make you lose client trust, face legal trouble, or lose money.

What Is Hugging Face?

Hugging Face has become the main place for machine learning models. It first focused on NLP (Natural Language Processing). But the platform now covers many areas, including:

Text generation & translation
Sentiment analysis
Image classification & detection
Voice-to-text and text-to-audio generation
Models that learn from different types of data

The platform lets anyone upload, share, and even adjust models. Just as GitHub changed how people shared open-source software, Hugging Face offers “model-as-code.” This helps developers and entrepreneurs work faster with AI parts.

In 2024, Hugging Face now has over 2.2 million publicly shared models. This includes powerful versions of BERT, GPT, T5, and custom AI models that create text. But with so many people adding content and small pieces of open-source code, there is a bigger risk of bad models being there without anyone knowing.

And unlike usual software sites that get strong security checks, many AI models were shared without being properly checked. This created ways for people to attack systems.

What Is VirusTotal?

VirusTotal is a well-known security platform. It uses over 70 antivirus programs, malware testing tools, and unusual activity detectors. Its first goal was to scan files for viruses using many tools, gathering information and pointing out harmful or strange actions.

Google’s Chronicle owns VirusTotal. It offers a detailed analysis. Security researchers and threat analysts used this mainly before. Now, it also works for AI.

In short, VirusTotal lets users:

Scan files, links, and programs
Combine reports on what things do from different tools
Let researchers share information through public pages
Show how scanned items are linked, what odd things they do, and what networks they connect to

And when used for AI models on Hugging Face, it lets users check files linked to the models. This is not just for actual malware, but for any action that could cause problems in your work after you add the model.

Inside the Partnership: Hugging Face + VirusTotal

In a big step in early 2024, Hugging Face worked with VirusTotal. They decided to scan every model as it is uploaded to find possible dangers. This means:

Automated Scanning at Upload: As soon as a model is added to Hugging Face, it gets scanned. It uses VirusTotal’s more than 70 detection tools.
Retroactive Scanning: This effort was not just for new models. Over 2.2 million existing models were also scanned. This shows Hugging Face wants the whole platform to be safe.
Public Transparency: Results from VirusTotal scans are now public on each model’s Hugging Face page. This lets users quickly check if it is safe.
Behavioral Inspection: Beyond just antivirus warnings, the scans help find risks from hidden code in scripts or linked files that come with models.

And this level of clear information is very important. It does not just warn about bad files. It helps people who are not experts choose AI parts more wisely and safely.

🔗 Source: Google Cloud Security (2024)

Impact: Building Trust in the AI System

Security is no longer a small topic; it is key for people to use AI. And thanks to this linking of systems, Hugging Face becomes a more trustworthy source for:

Developers who use models in their applications
Researchers who use model data from others
Businesses who put models into client services
Non-coders who use ready-made automations through tools like Make.com or GoHighLevel

Also, showing model security publicly sets a common rule. This makes how safe a model is as clear as how good the code is. Now, instead of thinking AI models are safe, users can check antivirus results, strange actions, or even where the model came from, right on its page.

This makes Hugging Face more than just an open site. It becomes a checked system. And it does this without making it less open or harder to use.

Why This Is Very Important for Bot-Engine Users

Bot-Engine customers work where AI is useful and user experience is key. Whether you are:

Using customer bots 24/7
Running sales assistants that speak many languages
Using smart tools for new users
Automating searches in internal knowledge bases

AI security is a basic need. These bots talk to users directly. So, any problem hurts your brand right away.

Bot-Engine uses many models from Hugging Face. It gets models for summarizing, translating, sorting, checking tone, and more. And the VirusTotal linking means:

Every model used already gets checked by many security tools.
Finding threats is automatic and always up to date.
Teams can now check scan results before using new systems.

And you can relax, it is built into the technology.

Beyond Viruses: The Hidden Threats in ML Models

"Virus" might make you think of old-school trojans or ransomware. But AI model threats are often more complex and risky. Some things found include:

🐚 Shell Scripts & Reverse Shells: Bad code hidden in scripts that load models can let attackers get into your system right away.
🪤 Pickle File Exploits: Python objects saved through pickle can run any code when loaded. This causes things to happen that you do not expect (or that are bad).
🧬 Data Poisoning: Attacks during model training can put in biases or bad actions that only show up when the model is used.
🎭 Redirected download links: Model pages that look normal but are changed to get bad programs from other places.
📦 Hidden payloads in scripts/data: Models that seem normal but show more hidden parts when you bring them in.

And these tactics can avoid simple checks and not be found. This happens unless platforms use a detailed scanning and watching what things do. This is just what Hugging Face and VirusTotal are making possible.

🔗 Source: Google Cloud Security (2024)

Being Clear About Model Safety for Many Models

Now, when browsing models on Hugging Face, you will see information from VirusTotal about scan results. These details include:

A short report of bad actions found
How many tools passed or failed a file/script
Old scan data
Links to detailed reports on VirusTotal’s own site

This lets any user—tech expert or not—check a model before putting it into their work. This might not seem like a big deal. But it actually gives everyone in a business the power to check ML models.

How One Thing Affects Many Others Across AI Platforms

When a big name like Hugging Face makes security important, others will follow. This moves outward to:

Model marketplaces
Sites that bring together AI tools from others
Companies that run AI models for others
No-code automation tools

End-users will want to see the same clear security information everywhere they use AI. For platforms, this becomes something they must do to compete. AI that is easy to use is not enough anymore. Users now ask: Is this AI secure by default?

We think other AI companies will do the same. They will start requiring scans, checking where models came from, and labeling what they do. This will help them meet Hugging Face's new standard.

Practical AI Security Tips for Entrepreneurs

If you are automating systems that talk to clients or making work more personal, here’s how to make your AI systems safer:

✅ Download from Checked Publishers: Stick to well-known, checked developers or groups on Hugging Face.
🔒 Only Use Scanned Models: Make sure model pages show VirusTotal scans with no problems.
🌐 Limit Model Internet Access: Use firewall rules or special containers so models do not ask for things online when they do not need to.
⚠️ Watch What Your API Does: Set up warnings for things like too many replies, too much use, or changes in content.
⚙️ Use Permissions Based on What a User Can Do: Do not let your models get to things they do not need (like file systems or databases).

How Bot-Engine Puts Secure AI Inside

Security is not just about uploading. Bot-Engine makes sure AI is safe when used. The platform adds many safety steps to each automated task, including:

🔁 Model Checking: All models are scanned and tracked using information from Hugging Face and VirusTotal.
🧱 Input Filtering: Bots clean and arrange user input to stop bad code or strange answers.
👀 Safety for Different Regions: Bots are set up based on where they are used and rules in different places (e.g., EU data rules).
📜 Logs You Can Follow: Every interaction and how it acts is recorded to fix problems and undo changes.
⚠️ Automated Alerts: A sudden rise in use or strange actions sets off warnings for your team.

✅ Bot-Engine Security Layers Include:

VirusTotal-sourced scans per model
Limits on API use and what it can do
Different roles for safe access
Clear records of where models came from
Regular updates and security checks

What Comes Next in AI Security?

This is just the start. Expect the next tools to keep models safe to include:

🤖 AI Tools that Watch Behavior: Checks 24/7 for changes in how chatbots act or speak.
🧪 Testing with Bad Prompts: Test with bad or wrong prompts.
🔍 Checks on Training Data History: Show where and how the data used to train models was put together.
🧠 Tools to Score Ethics: Check answers for unfairness, false information, or ethical problems.
🔐 Safe Testing Areas: Run risky AI tasks in separate cloud spaces.

As AI continues to become part of daily work, these tools will help us have both speed and safety.

Security as Innovation, Not Interruption

Security does not have to stop new ideas—it should help it. By putting safety checks everywhere, Hugging Face and VirusTotal prove it is possible to grow open AI without bringing in danger.

For teams using tools like Bot-Engine, these changes do not just make them less worried. They make them more sure. AI is ready for important daily work. And now the safety measures are ready too.

Ready to automate securely with multilingual AI bots? Build your first safe Bot-Engine automation today.
Unsure whether your models are putting your data at risk? Request a free AI security audit.

Citations

Google Cloud Security. (2024). Collaborating with Hugging Face to bring AI model scanning to VirusTotal. Retrieved from https://cloud.google.com/security