Security checklist: what NOT to paste into a chatbot

Talk to a chatbot artificial intelligence It has become so commonplace that we often forget we're not chatting with a friend, but with a cloud-based system that stores and processes what we type. These assistants are incredibly useful for working, studying, or resolving doubts, but if we're not careful, they can also become a gateway to data leaks, identity theft, or legal problems.

That's why it's key to always keep one simple idea in mind: everything you paste or type into a public chatbot It can end up being read, analyzed, stored, and used to train models, shared with third parties, or affected by a security breach. If it's something you wouldn't say out loud in a crowded place or post on a public website, it probably... You shouldn't share it with AI either.Let's get started with this guide on:  Security checklist: what NOT to paste into a chatbot

How AI chatbots work and why they pose a risk to your privacy

AI-based chatbots, such as ChatGPT and other similar assistants, rely on large language models (LLM) that learn from enormous amounts of text. To improve over time, these platforms usually record the entire conversations: your questions, your answers, the files you upload, and even metadata associated with usage.

This information is normally stored in cloud serverswhere it is processed to train more accurate models, analyze usage patterns, or personalize responses. Although many companies apply some degree of anonymization, you should assume that You lose real control over that data at the moment you send them to the chatbot.

The problem is that those same servers are a very attractive target for cybercriminalsA security breach allows access to a large volume of private conversations, leaked credentials, personal data, or even sensitive corporate documents, which can then be sold on the dark web or used for financial fraud, extortion, or targeted attacks.

Furthermore, many AI providers make it clear in their policies that They use your conversations to continue training their models and even that human employees can review snippets to assess the system's quality. That means anything you write should be considered, de facto, potentially public information in the medium or long term.

Security checklist: personal information you should NOT paste into a chatbot

Before sharing anything, always ask yourself if that data could be used for to identify you, locate you, impersonate you, or harm you Somehow. If the answer is yes (or you're not even sure), it's best not to paste them into a public chatbot.

1. Personal data and official identifiers

Direct personal data is the raw material of identity theftYou should never type your own message into a chatbot. full name along with other identifiers such as date of birth, physical address, nationality and the like, much less mix several of them in the same conversation.

Even more sensitive are the data that are considered official identifiersNational identity card number, passport number, social security number, tax identification number, driver's license number, or other documents issued by the government. With this type of information, an attacker can apply for loans, contract services or open bank accounts to your name.

It's also a good idea to avoid sharing your [information] for free. personal phone numbers, private emails, or exact addressesAlthough they may seem harmless in isolation, when combined with other information found on social media or previous leaks, they facilitate the creation of highly convincing social engineering attacks.

2. Personal images and biometric data

This data can be used to train algorithms facial recognition, populate third-party databases or serve as raw material for the creation of deepfakesWith enough visual material, it is perfectly possible to generate fake but very realistic videos or photos with your face, which could be used to damage your reputation, impersonate you in video calls, or even to blackmail and extortion.

The images where they are seen are also sensitive. interiors of your house, car license plates, physical documents on the table or any other detail that might give clues about your private life, your habits, or your assets. Although it may not seem obvious, all that visual information can be cross-referenced and used against you.

3. Financial information and bank details

Anything related to your finances is especially tempting for cybercriminals. You should never hit a chatbot. credit or debit card numbers, CVC codes, IBAN or bank account numbersFull bank statements, bank screenshots, investment information, or payroll and tax details.

With public chatbots, you have no guarantees of no end-to-end encryption or secure deletion of data after use. If this data ends up exposed in a data breach or is accessed by a dishonest employee, you're opening the door to Unauthorized charges, fraudulent transfers, account hijacking or targeted phishing campaigns using your own real data.

If you need help with financial matters, simply ask questions. in general and anonymous termsNever use a chatbot as a substitute for secure online banking or an official customer service channel.

4. Usernames, passwords, PINs and verification codes

It may sound obvious, but it keeps happening: Never paste passwords into a chatbotNeither PIN codes, nor answers to security questions, nor two-factor authentication (2FA) codes that you receive via SMS, email, or authentication apps.

Some users fall into the temptation of asking AI to help them manage, remember or review your passwordsOthers include parts of their passwords or clues within a text they want the chatbot to review or translate. This is all a serious mistake: with enough fragments, an attacker can reconstruct or deduce credentials to access your accounts.

The appropriate place to store and manage passwords is a secure password managerNever a public chatbot or a document you intend to upload to the AI. If an AI assistant asks for credentials to operate on your behalf across other services, make sure it's a legitimate one. official and audited integrationand assess whether that level of access is really worth it.

5. Medical results and information about your health

It's very tempting to describe symptoms, diagnoses, or treatments in a chatbot for get a quick explanationHowever, generic AI tools are not covered by the same confidentiality guarantees that a hospital or a medical practice, nor do they necessarily comply with regulations such as HIPAA or GDPR at their highest level.

Sharing is especially risky Medical reports, test results, specific diagnoses, ongoing treatments, medical records or details about family members' illnesses. If that information is leaked, it could affect your privacy, your access to health insurance, your working life and even give rise to very subtle forms of discrimination.

Furthermore, a chatbot is in no way a substitute for a healthcare professional. AI can to hallucinate, to invent diagnoses or give dangerous advice without understanding the full context. For health issues, it's prudent to use AI only for general and non-personalized informationand reserve clinical details for secure medical channels.

6. Intimate thoughts, beliefs, and very personal aspects

As chatbots sound increasingly “human,” it’s easy for them to become a kind of digital confessorSome people express their deepest fears, relationship conflicts, still private sexual orientations, traumas, political ideology, or very personal religious beliefs there.

The problem is that if those conversations are leaked or processed unethically, they could be used to psychological profiles, manipulation campaigns, blackmail or indirect discrimination. Although this possibility may seem remote, the rule of thumb is clear: Don't tell a chatbot anything that would devastate you if you saw it published publicly..

This also includes very detailed information about your family, friends or childrenYou have no right to expose their privacy on a system you cannot control, and you could be putting them at risk without them even knowing it.

7. Corporate information and confidential data of your company

One of the most common leaks nowadays occurs when someone copies and pastes into a chatbot internal company documents so that they can be summarized, translated, or turned into a presentation. These texts usually contain everything: customer data, business figures, source code, strategic plans, contracts, meeting minutes, internal manuals, or sensitive emails.

Sharing this type of content in a public chatbot can pose a violation of trade secrets, of non-disclosure agreements (NDAs) and even data protection laws. Large companies like Samsung, Apple, JPMorgan, and Google have come to restrict or prohibit the use of public chatbots precisely because of incidents of this type.

Special mention should be made of the source codeUploading significant snippets of proprietary software to a chatbot can effectively turn it into one. part of the AI ​​training setlosing control over its dissemination. The same happens with internal processes, security protocols, business strategies or product ideas not yet launched: if you feed them into AI, you lose your monopoly on that information.

8. Original creative work and unpublished ideas

Chatbots are great for shaping texts, scripts, marketing campaigns, or business ideas. However, if you share an entire chatbot, it can be problematic. an unpublished novel, a still-secret creative campaign, or the design of a new productYou must assume that some of that content may reappear, transformed, in responses to other users or in future versions of the model.

This greatly complicates the protection of the intellectual propertyAlthough many platforms promise some respect for copyright, in practice it is difficult to prove that a specific idea has been "taken" from your conversations, and you also cannot guarantee that your content will not end up in the hands of human reviewers or external partners.

If you have a business idea, a prototype, or an artistic concept that you haven't yet registered, think very carefully about it. What level of detail are you going to share? with AI. Working with general descriptions and without revealing critical details is much safer than directly pasting your entire work.

Technical security risks: what can go wrong when using chatbots

Beyond what users share, chatbots can become a risk to the company that deploys them if they are not designed with security from the startThere are several fronts to consider.

Privacy, insecure storage, and regulatory compliance

Business chatbots typically handle personal data: names, emails, purchase histories, support claims, or, in sensitive sectors, information medical, financial or bankingIf this data is stored without proper encryption, on poorly configured servers, or without strict access controls, any breach can become a legal, economic and reputational disaster.

Regulations such as GDPR in Europe, CCPA in California, HIPAA in healthcare, or SOC 2 Systems audits require very specific measures: control over what data is collected, what it is used for, how long it is stored, who can access it, and how it can be deleted. A chatbot that ignores these obligations exposes the organization to multimillion-dollar fines and class-action lawsuits.

We also need to take into account the data retention policiesSome providers delete conversations after a few months; others store them for years or allow users to delete them manually. If this policy isn't properly defined and reviewed, it's easy to accumulate large volumes of unnecessary sensitive information that, in the event of a breach, amplifies the impact.

Disinformation, hallucinations, and brand management

LLMs can fabricate data with complete confidence in themselves, which is known as hallucinationFor a company, a chatbot that responds with erroneous or misleading information not only frustrates customers but can also lead to... high-profile legal cases, such as the airline chatbot that promised a refund policy that didn't actually exist.

In addition, the chatbot is usually the first point of contact for many customers with the brandIf their responses are rude, inappropriate, off-color, or simply incorrect, the reputational damage can be significant. That's why corporate chatbots must have... conversational protection measures that limit the topics, style, and range of allowed responses.

A good practice is to use enhanced recovery generation (RAG)where the model bases its responses on a verified and up-to-date knowledge base instead of improvising. Combined with content filters, human review in sensitive cases, and thorough testing, the risk of public hallucinations can be drastically reduced.

Malicious prompt injection and exits

The call prompt injection This involves the user writing a message specifically designed to bypass the chatbot's internal instructions. For example, in an order management system, an attacker could try to include a hidden order in a text field to bypass the chatbot's internal instructions. manipulate prices, reveal internal data, or perform unwanted actions.

In contexts where the chatbot interacts with databases or back-end systems, the risk extends beyond the conversation itself. If the architecture is not properly isolated, a malicious input could generate dangerous queries, such as the classic example of SQL injection within a seemingly innocent text (for example, an order number that actually contains a statement to delete tables).

Mitigating these attacks requires applying strict input validations (regular expressions, whitelists of allowed formats), clearly separate what is “user text” from what are “instructions to the model” and, of course, never blindly trust that the chatbot will directly generate queries or commands that will be executed without review.

Denial of service and uncontrolled costs

Advanced AI models are very demanding in terms of computing resourcesA denial-of-service (DoS) attack against a chatbot is based on sending it a large number of simultaneous requests to saturate the infrastructure, cause outages, unacceptable response times, or exhaust the quotas contracted with the provider.

When the chatbot is built on cloud services such as Watson, Dialogflow, or other commercial LLMsConsumption is typically billed by the number of requests or by the number of tokens processed. A sustained attack not only renders the service unusable for legitimate users, but can also skyrocket costs in a matter of hours if appropriate limits have not been established.

The defense involves applying the same mechanisms as for any public API: rate limiting, anomalous pattern detection, web application firewalls (WAFs)real-time monitoring and contingency plans that allow for controlled service shutdowns if the situation gets out of control.

Best practices and security measures for using chatbots responsibly

Although all of this may sound worrying, it is perfectly possible Use chatbots safelyWhether as an individual user or within an organization, the key lies in combining prudent habits with robust technical measures.

Data minimization and anonymization

As a user, your best weapon is common sense: Share only what is absolutely necessaryIf the chatbot can still help you without knowing your name, address, or your company's real name, don't give them to it. Rephrase your questions so they are more relevant. as generic as possible without losing usefulness.

Before pasting a long text (a contract, a report, an email), do a preview to Remove or replace proper names, document numbers, addresses, emails or phone numbersYou can use generic markers like “Client X”, “Company Y”, or “Date Z”. And don't forget to also check for hidden metadata or embedded information in the files you're going to upload.

When working with academic or research material, avoid introducing unpublished data, confidential results, or information protected by ethical standardsIn work environments, always review internal policies on AI use before sharing anything related to the organization.

Configure privacy settings and understand the policies of each platform

Each AI provider has its own privacy policies and settings optionsMany allow you to disable, totally or partially, the use of your conversations to train their models. temporary chat modes that do not save the history or manually delete your past dialogues.

Take a few minutes to review these settings: disable data usage for training when possible, use the chatbot's "incognito" mode if offered, and periodically delete conversations that contain sensitive information. Keep in mind, however, that deletion is not always immediate and that some providers retain copies for legal or technical reasons.

It is also worth at least skimming the data retention policy: how long conversations are stored, whether they are shared with third parties (analytics partners, researchers, external developers) and what rights you have to request their deletion or export.

Technical security in business chatbots

If you're part of an organization that wants to deploy its own chatbot, security must be a core principle from the design stage. Start by implementing role-based access control (RBAC)Not all users need to see or edit the same thing, and the chatbot should not access more data than is essential for each use case.

Make sure all communication is done through HTTPS and robust encryptionboth in transit and at rest. It protects APIs with proper authentication and authorization, segments databases to minimize the impact of a potential breach, and carefully logs who accesses what and when.

Security audits must be periodic and systematicPenetration testing, code reviews, configuration analysis, prompt injection attack simulations, etc. The sooner vulnerabilities are detected, the cheaper and easier they will be to fix. And don't forget the continuous monitoring to detect anomalous behavior, both in traffic and in chatbot responses.

User training and cybersecurity culture

Often, the weakest link isn't the technology, but the people. That's why it's essential. train employees and collaborators on the responsible use of chatbots: what can and cannot be shared, how to anonymize data, how to identify dubious or potentially harmful responses, and who to contact if they suspect an incident.

IT and cybersecurity managers should provide clear guidelines, practical examples and internal policies accessible information on the use of AI in the company. A good goal is that, even if someone tries to misuse the chatbot, the information itself system protection measures make it virtually impossible.

In parallel, developers working with these systems need a specific training in software security applied to AI: understanding typical attack vectors, secure design of back-end integrations, protection against DoS attacks, and good data management practices.

Adopting this mindset from the outset transforms AI into a a reliable and profitable ally, instead of a constant source of scares and risks that are difficult to control.

Using AI chatbots intelligently means understanding what information should never leave your private sphere, what technical risks lie behind a simple conversation, and what tools you have to minimize them. Keeping personal, financial, medical, corporate, and creative data under control, combining minimization and anonymization, demanding good security practices from providers, and building a culture of digital prudence allows you to harness the full potential of conversational AI without turning your life or your company into a high-risk experiment.