Intellectual Property & Code of Conduct

The purpose of this document is to:

• keep programs respectful, safe and honest;
• explain clearly who owns what, so that nobody loses rights through a hidden clause;
• set fair rules for AI tools, third-party code, confidentiality and security;
• explain how concerns are investigated and what can happen.

It applies to all Gradopus Labs programs, communication channels, repositories and platforms. It is read together with the Student Terms & Conditions and the Project Submission & Assessment Policy.

Requirements in this document use "must" and "must not". Recommendations use "should".

Everyone must:

• treat others with respect, in messages, reviews, calls and code comments;
• give and receive feedback constructively, focusing on the work rather than the person;
• use the official communication channels for program matters;
• respect other people's time, and not expect replies outside reasonable hours;
• be honest about their work, progress and availability.

Reviewers and mentors must give feedback that is specific, fair and linked to the task's published criteria.

Harassment, bullying, threats and discrimination are not tolerated. This includes:

• unwelcome sexual comments, advances or images, and any other sexual harassment;
• insults, slurs or jokes about anyone's gender, gender identity, sexual orientation, caste, religion, region, language, disability, appearance or background;
• intimidation, repeated unwanted contact, or sharing someone's personal information without permission;
• retaliating against someone who reported a concern.

When working in a group, everyone must contribute fairly, credit each other's work accurately and resolve disagreements respectfully. Ask your mentor for help if a group problem cannot be resolved.

Harassment can be reported at any time under section 18, including directly, without first raising it with the person involved. To be confirmed: the person or committee who handles harassment complaints

• Your submissions must honestly show your own work and understanding.
• You must be able to explain, test and change the code you submit.
• You must credit material that is not yours (section 7).
• Honest mistakes, such as a forgotten credit, are treated differently from deliberate dishonesty (section 20).

You must not:

• copy another person's work, including another student's, and present it as your own;
• submit work written for you by someone else, paid or unpaid, or do another student's work for them;
• share your solutions so that others can submit them as their own, unless the task allows it;
• fabricate or alter evidence, such as commit history, screenshots, recordings, deployment URLs or demonstrations;
• misrepresent your role in a group project, your results or your certificate.

Using properly credited libraries, tutorials or templates, as a task allows, is not plagiarism.

AI tools can be useful, and using them is not automatically misconduct. The rules are:

• Follow each task brief. A brief states whether AI tools may be used and how. Use them only within those limits. To be confirmed: the default rule when a brief says nothing about AI tools
• Disclose your use as the task asks, for example a note in your README naming the tool and what it helped with.
• Understand, test and explain any generated code you submit. You are responsible for it, including its bugs, security problems and licence issues.
• Do not present AI output as your own where the task does not allow it or without the disclosure it requires.
• Do not paste confidential material (such as client code, private data or secrets) into an AI tool unless you have written permission to do so.

You will never be asked for your AI-tool account, password or private chat history. If a reviewer needs to understand how you used a tool, they may ask you to explain it.

Results from AI-detection or plagiarism-detection software are never treated, on their own, as proof of misconduct. A person must review the evidence and give you a chance to respond. Any such tool must be checked for reliability before it is used.

Gradopus Labs does not endorse any particular AI tool. To be confirmed: whether any AI tools are recommended or provided for programs

Credit any material you did not create, in the way the task asks and as its licence requires. This includes:

• tutorials, articles, videos and answers (for example from documentation or forums) that you followed or adapted;
• templates and starter projects;
• libraries and frameworks (usually covered by your dependency file, plus any notice the licence requires);
• datasets, images, icons and fonts;
• contributions from other people, including group members and anyone who helped you.

A simple credit in your README is usually enough, for example: "Navigation layout adapted from [tutorial name and link]". Where a licence sets out how credit must be given, follow the licence.

Open-source code is free to use only on the terms of its licence. Before you include it:

• check its licence, and do not use code that has no licence or that you do not have the right to use;
• keep the copyright and licence notices the licence requires;
• follow any conditions, for example some licences require that work built on them is shared under the same licence;
• make sure the licence allows the use you intend, especially for client or product work.

Publishing code in a public repository does not mean anyone may reuse it freely. Without a licence, other people generally do not have permission to reuse it. If you choose a licence for your own work, choose one that is compatible with the code you included.

If you are unsure whether a licence allows something, ask your mentor before using the code.

Pre-existing materials are code, libraries, designs, templates, documentation and other work that you created or obtained before, or independently of, a program.

• You keep any rights you have in them. Gradopus Labs does not claim them.
• You may use them in a submission if you have the right to and the task allows it. Mark them as pre-existing where the task asks.
• Using them in a submission only gives Gradopus Labs permission to review and keep a record of them (section 10).
• You must not include materials that belong to an employer, client, college or anyone else unless you are authorised to.

Student-created work means the code, designs, documentation and other deliverables you produce in response to program tasks.

• Submitting work does not transfer ownership. Uploading code to a repository or submitting a link to Gradopus Labs does not, by itself, give Gradopus Labs ownership of it.
• Permission to review. By submitting work, you allow Gradopus Labs to store, access, review and assess it, and to keep a record of it, only for running the program, verifying completion and certificates, handling disputes and keeping records the law requires.
• Ownership of work created during a program depends on applicable law, the licences of any material it includes, any written agreement, and the actual circumstances. Gradopus Labs does not claim ownership of your student-created work unless a separate written agreement says so (section 11). To be confirmed: whether any program will ask for ownership or a licence of student-created work
• You cannot transfer rights you do not own. Third-party and open-source parts of your work stay with their owners (section 8).

Some projects, such as work on a real product or for a client, may need a specific agreement about ownership or licensing. Such an agreement must:

• be in writing, separate from these general policies, and given to you before you start the work it covers;
• identify the project and the deliverables it covers;
• state clearly whether it transfers ownership or grants a licence, and the scope of that licence;
• state the intended use of the work;
• state any payment or other benefit;
• say what you may still show in your portfolio (section 12).

No ownership is transferred until you have read and signed such an agreement. A general policy, such as this one, is not a substitute for a separately required written agreement.

Gradopus Labs materials include the Gradopus Labs name and logo, task briefs, lessons, starter code, templates, internal documentation, and materials supplied by Gradopus Labs or its authorised clients.

• They belong to Gradopus Labs, its licensors or its clients.
• You may use them only for your program.
• You must not resell, republish or share them, or use the Gradopus Labs name or logo in a way that suggests endorsement, except as permitted in writing.
• To be confirmed: whether students may keep Gradopus Labs starter code in a public portfolio repository

Your portfolio:

• Each task brief states whether its work may be published publicly, for example in a public repository, a live deployment or a portfolio.
• Where publication is allowed, you may publish your own work and describe your contribution accurately.
• You must not publish confidential client information, credentials, private datasets, restricted source code or other confidential material.
• Where a project is confidential, you may still describe, in general terms, the skills you used and the kind of work you did, for example on your CV.

Gradopus Labs using your work, name or image:

• Gradopus Labs will not use your work, name, photograph, testimonial or project in its marketing or on its website without your separate, specific written permission.
• A permission to display work will say what will be shown, where, and for how long, and how you can withdraw it for future use.
• Permission to display work is not a transfer of ownership, and it never grants unlimited rights by implication.
• Refusing or withdrawing permission will not affect your assessment, certificate or treatment in a program.

During a program you may receive information that is not public, such as private repositories, unreleased product details, internal documents, or information belonging to Gradopus Labs, a client or another student. You must:

• use it only for your program tasks;
• not share, publish, copy or upload it anywhere outside the program, including into AI tools without permission;
• return or delete it, and give up any access to it, when the program ends or when asked.

This duty does not cover information that is already public through no fault of yours. Gradopus Labs takes reasonable steps to keep confidential information secure, but cannot promise absolute security.

Reporting is always allowed. Nothing in this document prevents you from reporting conduct you reasonably believe is unlawful to an appropriate authority, raising a genuine grievance, seeking legal advice, or disclosing information where the law requires it.

To be confirmed: any client confidentiality obligations that apply to specific programs; these will be stated in the internship details or a written agreement.

You must:

• keep API keys, tokens, passwords, private keys, certificates and other secrets out of repositories, submissions, screenshots and recordings, for example by using environment variables that are not committed;
• never share your passwords or other credentials, or use anyone else's;
• avoid collecting, downloading or exposing personal data that a task does not need;
• use test or made-up data in task projects unless the task requires real data;
• tell your mentor immediately if a secret or confidential information is exposed (section 18), so it can be changed or contained. An honest, prompt report is never treated as misconduct in itself.

Gradopus Labs will never ask for your GitHub password, AI-tool password, payment PIN or OTP.

You must not:

• access, or try to access, any system, account, repository, API or data you are not authorised to use;
• scan, probe or attack any system, including Gradopus Labs systems, without explicit written authorisation;
• write, upload or submit malicious code, such as malware, backdoors or code designed to steal data;
• obtain, steal, phish for or misuse anyone's credentials;
• overload or disrupt any system, for example through denial-of-service activity;
• bypass security controls, licence restrictions or usage limits;
• use program resources for anything unlawful or for activities unrelated to the program.

• Use only the accounts, systems, APIs and environments you have been given or are entitled to use, and follow their terms of service.
• Test security features only in environments you own or that a task explicitly provides for testing, and only within the scope the task allows.
• Do not run untrusted code on shared or provided systems.
• Keep development and test data separate from real data.
• Remove or close test resources you create, such as cloud deployments, when the task no longer needs them.
• Gradopus Labs does not claim any security certification for its systems.

Please report promptly:

• security weaknesses in any Gradopus Labs system: report them and do not exploit, share or keep testing them;
• accidental exposure of secrets or confidential information;
• suspected misconduct, including harassment, plagiarism or misuse of systems.

Report to your mentor, or to support.gradopuslabs@gmail.com. You will not be penalised for a report made in good faith, including a good-faith security report that follows this section.

When a concern is raised:

1. It is looked into by someone who is not personally involved, where possible.
2. The person concerned is told in writing what the concern is and the evidence for it.
3. They have a fair opportunity to respond. To be confirmed: the time allowed to respond
4. A decision is made on the evidence and explained in writing, with reasons.
5. Information about the case is shared only with those who need to know.

Where there is an immediate risk to people, systems or confidential information, access may be suspended while the concern is investigated. A suspension is not a finding that anyone did anything wrong.

Consequences depend on how serious the conduct was, whether it was deliberate or repeated, and its effect. Possible outcomes, from least to most serious, include:

• guidance or a reminder of the rules;
• a request to correct a submission, for example adding a missing credit;
• reassessment, or a requirement to redo a task;
• rejection of a submission;
• temporary restriction of access to systems or repositories;
• ending your participation in a program, under the Student Terms & Conditions;
• revocation of a certificate, but only through the process in the Certificate Issuance & Verification Policy.

There are no fines or financial penalties. Disciplinary rules will never be used to punish someone for raising a genuine complaint, criticising Gradopus Labs, or reporting a concern lawfully.

You can ask for a decision under this document to be reconsidered, or raise a grievance, as described in the Student Terms & Conditions, by writing to support.gradopuslabs@gmail.com. Appeals are decided, where possible, by someone not involved in the original decision. Using this process does not affect any other remedy available to you under law.

We may update this document. The current version is always published with its version number and effective date. Changes will not apply retrospectively to conduct before the change, or to ownership of work already created.

• General and conduct concerns: support.gradopuslabs@gmail.com
• Harassment complaints: support.gradopuslabs@gmail.com
• Security reports: support.gradopuslabs@gmail.com

• Internship Policy
• Student Terms & Conditions
• Privacy Policy
• Project Submission & Assessment Policy
• Certificate Issuance & Verification Policy
• Payment, Refund & Stipend Policy

• Version 1.1, 23 October 2026: Added the operator's location and the official support email address (support.gradopuslabs@gmail.com). Effective date still to be set after legal review.
• Version 1.0, 21 October 2026: First published version. Effective date to be set after legal review.