What Are the Risks of Uncensored AI Models Like FreedomGPT? The Dangers of Unrestricted AI

Key takeaways

• An uncensored model removes refusals but not errors, so it can produce confident wrong answers and harmful instructions without warning.
• Organisations should set an approved-AI-tools policy, since staff pasting client data into unvetted chatbots is the biggest practical risk.
• Individuals should check where prompts are stored and avoid sharing personal or work data with any tool they have not vetted.

"Uncensored" sounds like a feature, and for some research uses it can be. This page explains what those models are, where the real risks lie for individuals and companies, and what to do about them.

What is FreedomGPT and what makes an AI model "uncensored"?

FreedomGPT is a chatbot app marketed as an uncensored alternative to ChatGPT. It started in 2023 as a downloadable app running an open-source model on the user's own computer. Its current website describes desktop apps that give access to many third-party and open-source models side by side, plus its own "Liberty" model, which it says answers without censorship.

An "uncensored" model is usually an open-weight model that has been fine-tuned to stop refusing requests, or released without the safety training mainstream providers add. That changes three things:

• Fewer refusals: it will attempt requests that a mainstream assistant declines.
• Less moderation: there may be no system checking inputs or outputs for abuse.
• Same weaknesses: it still hallucinates, still carries bias from its training data, and is often a smaller, less accurate model than leading commercial ones.

For more background on the app itself, see our ChatGPT vs FreedomGPT comparison.

Why do people use uncensored AI models?

Most users are not criminals. Common reasons include:

• Frustration with over-refusal: mainstream assistants sometimes refuse harmless requests, such as fiction with dark themes or blunt medical questions.
• Local and private use: running an open model offline means prompts never leave the machine.
• Research: safety researchers study how models behave without guardrails, and red teams test their own systems.
• Ideology: some users believe AI output should not be filtered at all.

These are understandable motivations. The problem is that removing filters removes them for everyone, including people with harmful intent, and removes a safety net for honest users too.

What are the main risks of uncensored AI models?

The risks fall into six groups. Some affect the person using the tool; others affect everyone else.

1. Harmful and abusive content

Without refusals, a model will produce harassment, extremist propaganda or sexual content on request. Some outputs, such as instructions that could cause physical harm, can be dangerous even when they are partly wrong. Content that would breach platform rules or Indian law is still the responsibility of the person who generates and spreads it.

2. Misinformation delivered with confidence

Uncensored models are not more truthful; they are only less cautious. Smaller fine-tuned models often hallucinate more, and they rarely add the "check with a professional" caveats a mainstream assistant would. OWASP lists misinformation as one of its Top 10 risks for LLM applications (2025), alongside prompt injection and sensitive information disclosure. At scale, the same tools can mass-produce convincing fake news, reviews and social media posts.

3. Lower barriers for scams and cybercrime

The biggest practical security impact is not "AI writes malware". It is that anyone can now produce fluent, well-targeted fraud messages in English, Hindi or any other language, with no spelling mistakes to give them away. Criminal forums have advertised purpose-built models for this since 2023. Defenders should assume phishing emails, fake job offers, fake customer support chats and investment-scam scripts will look more professional than before. We cover this shift in more depth in how criminals are using AI for phishing, malware and deepfakes.

4. Privacy claims you cannot verify

Some uncensored AI apps promise strong privacy. Ask how those promises work. If a service routes your prompts to third-party model providers, your data passes through more parties, not fewer. Read the privacy policy, check where data is processed, and assume that anything you type into a cloud service may be stored. A model running entirely offline on your own computer is the private option, but then you are responsible for the security of that machine and the files you downloaded.

5. Malware in model files and installers

Uncensored models are often shared through forums, torrent sites and unofficial mirrors. Some model file formats can execute code when loaded (Python pickle files are the classic example), and fake installers are a common way to spread information-stealing malware. Download only from the developer's official site or a reputable model hub, prefer the safetensors format, check hashes, and scan files before running them.

6. Legal and workplace exposure

In India, sharing obscene material, impersonating others or publishing defamatory content can attract liability under the IT Act and other laws, whether a human or an AI wrote the first draft. Pasting customer or employee personal data into an unapproved AI tool can also create obligations under the Digital Personal Data Protection Act. At work, using a tool your employer has not approved can breach policy even if nothing bad happens.

What should organisations do about uncensored AI tools?

Treat uncensored AI apps as a form of shadow IT. You cannot stop staff from hearing about them, but you can make the safe path the easy one.

1. Publish an AI acceptable-use policy that lists approved tools and states what data may never be entered into any AI service.
2. Provide an approved assistant with business data protections, so people are not tempted by unvetted apps.
3. Control unapproved apps with your web proxy, CASB or endpoint controls, and block unsigned AI installers through application allow-listing.
4. Use data loss prevention rules to detect personal data, source code or secrets being pasted into AI websites.
5. Update phishing training: staff should stop relying on bad grammar as a warning sign and instead verify unusual requests through a second channel.
6. Strengthen controls attackers target: phishing-resistant MFA, payment-change verification and quick reporting routes.
7. Govern internal AI projects with a recognised framework such as the NIST AI Risk Management Framework, and test your own AI applications against the OWASP LLM risks.

How can individuals use AI tools safely?

• Do not paste passwords, Aadhaar or PAN numbers, bank details, or other people's personal information into any chatbot.
• Verify any factual, medical, legal or financial claim from an AI against a reliable source before acting on it.
• Install AI apps only from official sources, and be wary of "free premium" or "cracked" versions.
• Remember that you are responsible for what you publish, even if a model wrote it.
• If you are researching model safety, do it in an isolated environment and follow your institution's or employer's rules.

Is there a middle ground between censored and uncensored AI?

Yes. The useful debate is not "filters or no filters" but which safeguards are proportionate. Mainstream providers have reduced unnecessary refusals over time, open-weight models let researchers and companies run AI privately, and organisations can add their own guardrails on top of a model to suit their use case. Good AI governance keeps the benefits of openness, such as transparency and local control, while keeping protections against the clearly harmful uses. Our overview of how countries are regulating AI shows how different governments are drawing that line.

Your next step

If you manage IT or security for an organisation, check this week whether you have an AI acceptable-use policy and whether your proxy logs show traffic to unapproved AI services. If you want to build the skills to assess and secure AI systems properly, including prompt injection, data leakage and model supply chain risks, our AI and LLM security course covers them with hands-on labs.

Related reading

• FreedomGPT Explained: The Uncensored AI Chatbot, How It Works, Risks and Alternatives
• How Secure Is FreedomGPT? An In-Depth Analysis of Its Privacy, Security Features, and Potential Risks