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| # Name of your Project | ||
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| - **Team Name:** Armur A.I | ||
| - **Payment Address:** will share fiat address privately | ||
| - **[Level](https://github.com/w3f/Grants-Program/tree/master#level_slider-levels):** 3 | ||
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| ## Project Overview :page_facing_up: | ||
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| About Us - Armur A.I is a Techstars and Outlier Ventures backed startup focused on building A.I powered security tools to help secure blockchains. | ||
| Armur A.I is supported by Algorand and Aptos. | ||
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| Problem - Many static/ hard-coded tools exist to audit smart contracts but they're definitely not sufficient in being able to detect vulnerabilities or security issues and the issue with hard-coded tools is that everytime there's a new vulnerability, you have to extend the functionality of the tool by writing more code and this might sometimes conflict with the old functionality of the tool. The other option for web3 companies is to go for manual auditing, but this takes too long and is an extremely expensive approach (starting at $40K for a basic audit). | ||
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| Our unique solution - Using A.I models is a great approach because it's way more effective than static auditing tools because now you can simply train A.I models to be able to catch new reproted vulnerabilities rather than change the code or extend the code, this is an all new approach. A.I powered audit also provides "contextual" and descriptive information about the vulnerabilities and security issues in the code and this can really make it easy for tdevelopers to fix those issues. | ||
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| Why Polkadot ecosystem - At Armur A.I, we wnat to build for the Polkadot ecosystem by building a tool that enables A.I powered auditing of ink! smart contracts. | ||
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| Our Approach - We're using Open-Source A.I models and training them. Instead of using closed-source technologies like Open A.I, we're using A.I models that everyone has equal access to, such as - Falcon 40b, LLaMa2, GPT-NEO-X etc. | ||
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| ### Overview | ||
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| Please provide the following: | ||
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| - Armur A.I will enable A.I powered auditing of ink! smart contracts | ||
| - We've built a successful A.I powered auditing tool for solidity files (ethereum), we have a grant from Aptos to do this for Move smart contracts and are currently working on this. We now wanted to expand to Polkadot by building the capability to audit Ink! smart contracts. | ||
| - Our A.I models will be trained on Ink! smart contracts, common vulnerabilities and audit reports commonly found in the Polkadot eco-system. Since our A.I models are already trained on Solidity smart contracts, this means we would need less data from the ink! community to train our A.I models due to the "few shot learning" advantage. | ||
| - Our team has a deep expertise in Rust and everything from the Polkadot eco-system. The Founder (Akhil) has a 14-chapter course on Substrate on his **[Youtube Channel](https://youtube.com/playlist?list=PL5dTjWUk_cPYdb4j2RH8BHEAK3z_ZME1j)** and is also writing a book called "Rust for Blockchain Development" with **[Packt Publishing](https://www.packtpub.com/)** which has 2 entire chapters on Polkadot and Substrate. Our team believes that app-specific blockchains are the future and sooner or later, Polkadot will win and we want to be a strong part of the Polkadot eco-system. | ||
| Akhil also actively advises companies that are fast-tracked in the Substrate Builders' Program. | ||
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| ### Project Details | ||
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| - The product itself is really straightforward. Our alpha product demo is ready. We have trained open source A.I models on datasets that consist smart contracts and their vulnerabilities, smart contract audit reports etc. while a lot of data was available for solidity and so we were easily able to train A.I models for the same. We need help of the Polkadot community to create datasets for ink! smart contracts and audit reports so that we are able to classify common recurring vulnerabilities and also detect them in new contracts. | ||
| - Here's our product architecture image for more details - | ||
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| - **We have a detailed notion page on how we built our product and how it works, all the details are here on this page** - | ||
| **[product details](https://oil-polonium-2f2.notion.site/Armur-A-I-Product-Details-ae4b60dca0514ae5b74de649babcaeba?pvs=4)** | ||
| - The tool enables you to upload your smart contracts and audit them. But in the near future, you'll be able to connect your github or gitlab project to it and the tool will fork the code automatically, audit it and create a pull request. | ||
| - Product UI - | ||
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| ### Ecosystem Fit | ||
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| This will really be a much needed addition in the Polkadot ecosystem. Imagine if all the smart contracts flowing through all the parachains could be secured so that the entire ecosystem becomes way more secure, this will grow the ecosystem, generate trust and also increase the investors into the Polkadot ecosystem. | ||
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| - Auditors, smart contract developers, start ups will benefit a lot from our product. Both new entrants to the Polkadot ecosystem and the old players will benefit tremendously because now they will have a tool that can do atleast basic audits with the help of A.I models, this means developers don't have to wait weeks and spend a lot of money everytime they have a new smart contract or want to make any changes to their projects. This significantly increases the speed of development and leads to the growth of the Polkadot ecosystem. | ||
| - In the beginning, our target audience are the developers, in the sense the ink! smart contract developers that are building applications to launch on the polkadot ecosystem, but the parachains themselves can be the target audience if they'd like to integrate with us and make all smart contracts flowing through their chain secure by default or before they're uploaded. | ||
| - Our team has the necessary expertise in terms of A.I and also blockchain to be able to build this. | ||
| - Currently there are not products similar to ours in the Polkadot system | ||
| - In the other eco-systems such as Ethereum related chains and Aptos, we're the main company trying to implement this. | ||
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| ## Team :busts_in_silhouette: | ||
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| ### Team members | ||
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| - Akhil Sharma | ||
| - Jesper Kristensen | ||
| - Paul Slattery | ||
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| ### Contact | ||
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| - **Contact Name:** Akhil Sharma | ||
| - **Contact Email:** [email protected] | ||
| - **Website:** htts://www.armur.ai | ||
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| ### Legal Structure | ||
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| - **Registered Address:** 1209, North Orange Street, Wilmington, Delaware, Wilmington, Delaware 19801, United States | ||
| - **Registered Legal Entity:** Armur Technologies Inc. | ||
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| ### Team's experience | ||
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| We haven't applied for a web3 grant previously. This is our first Web3 grant. Our team consists of | ||
| - Akhil, who has been teaching blockchain technologies on his youtube, he was running a web3 development lab before this and is active in the web3 community. | ||
| - Jesper has two masters degrees and a PhD from Cornell with a specialization in blockchain | ||
| - Paul Slattery has led and managed tech teams of different sizes. He's currently a VP of Engineering at BCGX | ||
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| ### Team Code Repos | ||
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| - https://github.com/jesperkristensen58 | ||
| - https://github.com/AkhilSharma90 | ||
| - https://github.com/paul-slattery-akqa | ||
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| ### Team LinkedIn Profiles (if available) | ||
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| - https://www.linkedin.com/in/akhilsails/ | ||
| - https://www.linkedin.com/in/paulslattery/ | ||
| - https://www.linkedin.com/in/jespertoftkristensen/ | ||
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| ## Development Status :open_book: | ||
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| - We have an Alpha working product demo that has been already used by many companies, we have done more than 45 A.I powered audits until now for 45 different firms. | ||
| - This link has all the details of the implementation of our product - **[product details](https://oil-polonium-2f2.notion.site/Armur-A-I-Product-Details-ae4b60dca0514ae5b74de649babcaeba?pvs=4)** | ||
| - We have already shared the product roadmap and product UI screenshots above in the project details section. | ||
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| ## Development Roadmap :nut_and_bolt: | ||
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| ### Overview | ||
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| - **Total Estimated Duration:** 6 months | ||
| - **Full-Time Equivalent (FTE):** 4 | ||
| - **Total Costs:** USD 60,000 | ||
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| ### Milestone 1 - Creating Datasets | ||
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| - **Estimated duration:** 1 month | ||
| - **FTE:** 3 | ||
| - **Costs:** 15,000 USD | ||
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| | Number | Deliverable | Specification | | ||
| | -----: | ----------- | ------------- | | ||
| | **0a.** | License | Apache 2.0 / GPLv3 / MIT / Unlicense | | ||
| | **0b.** | Documentation | We will provide both **inline documentation** of the code and a basic **tutorial** that explains how a user can use the particular functionality that'll be built as part of this milestone | | ||
| | **0c.** | Testing and Testing Guide | Core functions will be fully covered by comprehensive unit tests to ensure functionality and robustness. In the guide, we will describe how to run these tests. | | ||
| | **0d.** | Docker | We will provide a Dockerfile(s) that can be used to test all the functionality delivered with this milestone. | | ||
| | 0e. | Article | We will publish an **article**/workshop that explains [...] (what was done/achieved as part of the grant). (Content, language and medium should reflect your target audience described above.) | | ||
| | 1. | Dataset Creation | The first month, we're going to focus on finding smart contracts, audit reports and converting them into the required format to train our A.I models, so this stage is basically "Dataset" creation | | ||
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| ### Milestone 2 Deploying A.I models | ||
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| - **Estimated duration:** 1 month | ||
| - **FTE:** 2 | ||
| - **Costs:** 5,000 USD | ||
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| | Number | Deliverable | Specification | | ||
| | -----: | ----------- | ------------- | | ||
| | **0a.** | License | Apache 2.0 / GPLv3 / MIT / Unlicense | | ||
| | **0b.** | Documentation | We will provide both **inline documentation** of the code and a basic **tutorial** that explains how a user can use the particular functionality that'll be built as part of this milestone | | ||
| | **0c.** | Testing and Testing Guide | Core functions will be fully covered by comprehensive unit tests to ensure functionality and robustness. In the guide, we will describe how to run these tests. | | ||
| | **0d.** | Docker | We will provide a Dockerfile(s) that can be used to test all the functionality delivered with this milestone. | | ||
| | 0e. | Article | We will publish an **article**/workshop that explains [...] (what was done/achieved as part of the grant). (Content, language and medium should reflect your target audience described above.) | | ||
| | 1. | A.I model selection and deployment | The second month, we're testing multiple A.I models and finding the ones that are most relevant for our usecase. Finally, we will deploy them so that we can train them. This requires A.I engineering and a bit of ML related Ops on the cloud | | ||
| | 2. | Vaildating and refining data sets| The data sets that we created as part of the first milestone, we will be refining them in this milestone before we start training. Refining basically means cleaning up data, ensuring everything is structured so that there are no issues when we train the models in the next milestone. | | ||
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| ### Milestone 3 Training the A.I Models | ||
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| - **Estimated duration:** 2 months | ||
| - **FTE:** 4 | ||
| - **Costs:** 20,000 USD | ||
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| | Number | Deliverable | Specification | | ||
| | -----: | ----------- | ------------- | | ||
| | **0a.** | License | Apache 2.0 / GPLv3 / MIT / Unlicense | | ||
| | **0b.** | Documentation | We will provide both **inline documentation** of the code and a basic **tutorial** that explains how a user can use the particular functionality that'll be built as part of this milestone | | ||
| | **0c.** | Testing and Testing Guide | Core functions will be fully covered by comprehensive unit tests to ensure functionality and robustness. In the guide, we will describe how to run these tests. | | ||
| | **0d.** | Docker | We will provide a Dockerfile(s) that can be used to test all the functionality delivered with this milestone. | | ||
| | 0e. | Article | We will publish an **article**/workshop that explains [...] (what was done/achieved as part of the grant). (Content, language and medium should reflect your target audience described above.) | | ||
| | 1. | Training models | In the previous milestones we have deployed the A.I model and also created datasets, now it's time to train the A.I models, this is a resource intensive undertaking that takes experienced A.I engineers, experience auditors to ensure right human feedback loop to the A.I model | | ||
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| ### Milestone 4 Testing the Models and refining output | ||
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| - **Estimated duration:** 2 months | ||
| - **FTE:** 4 | ||
| - **Costs:** 20,000 USD | ||
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| | Number | Deliverable | Specification | | ||
| | -----: | ----------- | ------------- | | ||
| | **0a.** | License | Apache 2.0 / GPLv3 / MIT / Unlicense | | ||
| | **0b.** | Documentation | We will provide both **inline documentation** of the code and a basic **tutorial** that explains how a user can use the particular functionality that'll be built as part of this milestone | | ||
| | **0c.** | Testing and Testing Guide | Core functions will be fully covered by comprehensive unit tests to ensure functionality and robustness. In the guide, we will describe how to run these tests. | | ||
| | **0d.** | Docker | We will provide a Dockerfile(s) that can be used to test all the functionality delivered with this milestone. | | ||
| | 0e. | Article | We will publish an **article**/workshop that explains [...] (what was done/achieved as part of the grant). (Content, language and medium should reflect your target audience described above.) | | ||
| | 1. | Refinement | This milestone is all about ensuring that the A.I models are giving a stable and correct output with good amount of accuracy. We ensure there are less false positives, less hallucination and the tool is in a good shape for public trials. At this stage we're also refining the training process further and even the datasets depending on the accuracy of the A.I model. | | ||
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| ## Future Plans | ||
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| Please include here | ||
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| - In the short term- we plan to enable auditors and developers to be able to audit their smart contracts automatically so they can focus more on writing the business logic. | ||
| - In the long term, we intend to make our tool way more advanced so that developers would need manual auditors for very few advanced use cases only and most of the checks can be done by the A.I tool. | ||
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| ## Additional Information :heavy_plus_sign: | ||
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| **How did you hear about the Grants Program?** Our Founder, Akhil has been active in the Polkadot ecosystem and also has a 14-chapter course on Substrate on his youtube. We all think Polkadot is the future. A grant seems like the best way forward for us to be involved with the Polkadot community more deeply. |