AI Model Development for Code Vulnerability Detection

@pkundu25

I am an experienced IT professional and a Data Science practitioner. Your job caught my eye and looks to be quite interesting to me as I did similar work in recent past. I have developed various simple to complex algorithms pertaining to ML/DL/NLP/Computer Vision from exploratory data analysis (EDA) to model building till deployment. I have good hands-on experience in data engineering and product development for industrial use cases. I am well conversant with Generative AI and hands-on experience in developing AI applications using LangChain and LLMs. I am confident that I will be able to help you by developing Machine Learning model for code vulnerability detection as part of PoC. Notable Projects successfully completed: - Text2SQL - Semantic search engine - Recommendation engine - Unsupervised preventive maintenance model - Topic modeling - Text classification - OCR image recognition and text extraction Relevant Skills: - Agentic AI - ChatGPT - Amazon Bedrock - LangChain - SQL - ML algorithms - Numpy, pandas, scikit learn - TensorFlow - Google Colab - OpenCV Let's have a chat to understand the project objective and the dataset in details. I assure you the best quality results and ensure the customer satisfaction. Looking forward to hearing from you soon. Thanks for the opportunity.

@malkesh3m

⭐ Hi, My availability is immediate. I read your project post on Python/AI/ML Developer for experimental proof of concept (PoC) project that involves reading vulnerable source code and training a supervised AI model to identify code vulnerabilities. We are experienced full-stack Python developers with skill sets in - Python, Django, Flask, FastAPI, Jupyter Notebook, Selenium, Data Visualization, ETL - React, JavaScript, jQuery, TypeScript, NextJS, React Native - NodeJS, ExpressJS - Web App Development, Data Science, Web/API Scrapping - API Development, Authentication, Authorization - SQLAlchemy, PostegresDB, MySQL, SQLite, SQLServer, Datasets - Web hosting, Docker, Azure, AWS, GPC, Digital Ocean, GoDaddy, Web Hosting - Python Libraries: NumPy, pandas, scikit-learn, tensorflow, etc. Please send a message So we can quickly discuss your project and proceed further. I am looking forward to hearing from you. Thanks

@rajat23091969

Hello CCSF , We went through your project description and it seems like our team is a great fit for this job. We are an expert team which have many years of experience on Job Skills. Lets connect in chat so that We discuss further. Regards

@rajendrac3

Hi, I have worked on fine-tuning LLM models like Llama3.1 which can be used in your case to detect vulnerabilities. We can use use NLP models since it is a supervised learning. I have trained such models as well in the past. I have more than 7 years of experience in the field of AI/ML. I can share my LinkedIn when we discuss more over chat. Thanks

@strahinjaj9

Hey there! Diving into the world of vulnerable source code to train an AI model for spotting SQL injections, XSS, and buffer overflows sounds like an exciting challenge! The most critical aspect here seems to be ensuring our model accurately identifies vulnerabilities while maintaining high precision — a balancing act I'm familiar with. To start, we need to carefully select and tokenize the training data to ensure our LLM gets a clear learning path. I’ve worked on similar projects utilizing supervised learning models, emphasizing relevant data concoction to boost model effectiveness. Here's a bit about how I align with your project needs: ✅ **Familiarity with tokenization for LLM training:** Having worked on various NLP projects, I'm adept at creating efficient tokenization pipelines. ✅ **Mid-level proficiency in Python:** Python is my bread and butter, and I've tackled a bunch of projects (including PoCs) that required similar skills. ✅ **Experience in working with supervised learning models:** I've helped deploy models in production that needed meticulous training and evaluations to meet performance benchmarks. I can hit the ground running and assist in getting your PoC off the ground right away. Let's connect on a call to chat more about how we can make this project a success. Looking forward to hearing from you! Cheers, Strahinja

@shashank165

Hi Team, Case Study: AI-Powered Code Vulnerability Detection System I recently developed a supervised learning model trained on tokenized vulnerable source code to identify critical security flaws such as SQL injection, XSS, and buffer overflow. By leveraging Python and advanced tokenization techniques, the PoC demonstrated technical feasibility for automated vulnerability detection. To begin with you project I will gather and label vulnerable source code snippets containing SQL injection, XSS, and buffer overflow vulnerabilities and preprocess the code into tokenized datasets optimized for LLM training. I can present my detailed solution approach once you initiate the chat! I am confident enough that I can assist you in this project effectively as I have completed similar projects previously. But before we begin I have few key questions to be asked- 1. What specific programming languages should the model focus on for vulnerability detection (e.g., Java, Python, PHP)? 2. Are there any pre-existing datasets of labeled vulnerable code, or should the dataset be curated from scratch? 3. What is the expected volume and diversity of the training dataset? 4. Are there any specific LLM architectures preferred for this task? Please answer the following and we can jump on the detailed discussion to outline the next steps. Regards, Shashank