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Fahad R's avatar
Fahad R
proSingapore
Senior FullStack & AI Engineer | Product-Driven Solutions
$25k+
Earned
7x
Hired
5.0
Rating
30
Followers
Senior FullStack & AI Engineer | Product-Driven Solutions
Cover image for Check Med Products
Check Med Products
0
58
Cover image for Chronicler | An a16z funded Startup
Chronicler | An a16z funded Startup
2
43
Cover image for AuditionAid - AI Career Platform for Actors (Web & Mobile)
AuditionAid - AI Career Platform for Actors (Web & Mobile)
1
18
Cover image for Development of Daemora Autonomous AI Agent
Development of Daemora Autonomous AI Agent
1
19
Docker Compose(1)
Stephen Kisong'e's avatar
Stephen Kisong'e
Nairobi, Kenya
Cyber Security Analyst
Cyber Security Analyst
Cover image for Designed and documented a secure
Designed and documented a secure environment for running Robin, an AI-powered dark web OSINT tool, inside a compartmentalized Qubes OS and Qubes-Whonix setup. The environment was structured to separate research activity, Tor-routed traffic, sensitive credentials, untrusted content, and final reporting. Robin was deployed through Docker inside a dedicated research qube, with traffic routed through sys-whonix and sensitive notes stored separately in an offline vault qube. Disposable qubes were incorporated for opening potentially unsafe links and files. The setup was built around security by compartmentalization rather than relying on a single tool for protection. Particular attention was given to Docker mount restrictions, credential hygiene, network-boundary verification, lawful research scope, and keeping raw research data isolated from personal or client environments. The final result was a repeatable AI-assisted OSINT workflow that supports faster search refinement, result filtering, investigation summarization, and structured reporting while maintaining stronger operational security and clearer separation between collection, analysis, and final output.
0
200
Cover image for AI Agent Hacking & Security
AI Agent Hacking & Security Testing Explored how an AI agent can be manipulated through adversarial interactions, with a focus on AI agent hacking, prompt injection, sensitive data exposure, and unsafe agent behavior. The lab uses an AI agent connected to controlled internal data and tools, creating a realistic environment for testing how the agent responds when an attacker attempts to bypass its instructions, access information it should not reveal, or influence how it uses its capabilities. The assessment demonstrates the practical attack surface of modern AI agents and how seemingly simple interactions can become security issues when an agent has access to sensitive data or external capabilities. The testing was performed against fictional data in an isolated environment for authorized security research.
0
12
Cover image for Designed and implemented a hands-on
Designed and implemented a hands-on AI red teaming environment using Microsoft PyRIT to evaluate the security of a local Retrieval-Augmented Generation application. The project connected a Parrot OS testing environment to a Windows-based AnythingLLM RAG application, with DeepSeek running locally through LM Studio. I configured PyRIT to communicate with the AnythingLLM workspace through a custom HTTP target and used controlled adversarial objectives to examine how the application handled requests involving financial records, customer information, payroll data, and restricted credentials. The testing workflow included API connectivity validation, isolated Python environment setup, automated prompt execution, response collection, and evidence review. The lab was built entirely around fictional Kiso Secure business data, allowing realistic sensitive-data disclosure scenarios to be tested without using real customer information or credentials. The resulting workflow demonstrates how automated AI red teaming can be used to identify potential data leakage, retrieval-boundary weaknesses, and unsafe handling of sensitive information in AI-powered applications.
2
0
46
Cover image for Built a controlled Kiso Secure
Built a controlled Kiso Secure AI red teaming lab using Promptfoo to test a local RAG application for prompt injection, system prompt leakage, indirect prompt injection, and sensitive data exposure. The setup used AnythingLLM with a Kiso Secure knowledge base, automated adversarial testing, and a hardened workspace to compare security behavior before and after remediation.
2
0
81
Docker Compose(1)
Pratik Patil's avatar
Pratik Patil
Mumbai, India
AI Integration for Existing Systems | Agents & SaaS
New to Contra
AI Integration for Existing Systems | Agents & SaaS
Cover image for School Website & Self-Hosted ERP
School Website & Self-Hosted ERP
0
3
Cover image for School ERP Mobile App: Admin, Teacher & Parent
School ERP Mobile App: Admin, Teacher & Parent
0
2
Cover image for Self-Healing AI Browser Agent for Data Extraction
Self-Healing AI Browser Agent for Data Extraction
0
1
Cover image for AI Comment Intent Classifier for Social Media
AI Comment Intent Classifier for Social Media
0
3
Docker Compose(1)
Douglas Schlenker's avatar
Douglas Schlenker
proKanata, Canada
Building great software that has a positive impact
1x
Hired
1
Followers
Building great software that has a positive impact
Cover image for sliced bread
sliced bread
0
21
Cover image for Pay Down Production Defects
Pay Down Production Defects
0
38
Cover image for Measuring & Increasing Team Productivity
Measuring & Increasing Team Productivity
0
29
Cover image for GitHub Codespace Template
GitHub Codespace Template
0
66
Docker Compose(1)
Calista Lee's avatar
Calista Lee
Indonesia
Conversion-focused Designer | Web Developer | Game Designer
5.0
Rating
Conversion-focused Designer | Web Developer | Game Designer
Cover image for Salena Xu: Portfolio Site
Salena Xu: Portfolio Site
0
38
Cover image for Game Screenshot Redesign for Increased Installs
Game Screenshot Redesign for Increased Installs
0
12
Cover image for Visual Redesign Boosts Game Installs by 48%
Visual Redesign Boosts Game Installs by 48%
0
4
Cover image for Scora: Offline Pool Digital Scoreboard
Scora: Offline Pool Digital Scoreboard
0
32
Docker Compose(1)
Leonardo Dutra's avatar
Leonardo Dutra
Fortaleza - Zone 1, Brazil
Building high-performance Go APIs and observability
Building high-performance Go APIs and observability
Cover image for Modernizing Legacy Java with IaC (Security & Portability)
Modernizing Legacy Java with IaC (Security & Portability)
0
8
Cover image for DNS Custom Tool — Policy-Based Resolver in Go
DNS Custom Tool — Policy-Based Resolver in Go
0
6
Cover image for Cross-Platform Diagnostic Tool Development
Cross-Platform Diagnostic Tool Development
0
7
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Muaz Saad ur Rehman's avatar
Muaz Saad ur Rehman
Rawalpindi, Pakistan
I build 9-agent AI systems that generate leads on autopilot
New to Contra
I build 9-agent AI systems that generate leads on autopilot
Cover image for I built an AI system
I built an AI system that finds and contacts business leads automatically — every day, while you sleep. A client in the UK runs a waste removal marketplace. He needed contractors to join his platform but had no way to find them at scale. So I built him a system that does it automatically. Every morning at 6am, without anyone touching a button: The system scrapes Checkatrade, the UK Environment Agency, Gumtree, and Yell for waste removal contractors Each lead gets scored out of 10 based on reviews, licensing, and contact details Bad data gets cleaned out automatically Personalised outreach messages are prepared for the best leads The client opens his dashboard, sees who's ready to contact, and sends an SMS in one click The database now has 2,300+ verified contractor leads and grows every day. The whole thing runs on 9 AI agents that work like a real team. There's a CEO agent that reads instructions in plain English and delegates to specialists — a Lead Scorer, Deduplication Agent, Outreach Agent, Reporting Agent, and more. The client can type something like "find the top 50 contractors in East London and prepare messages for them" and it happens automatically in a few minutes. No technical knowledge needed on his end. Just a dashboard and a send button. What I used: Claude AI · Paperclip · Python · Node.js · PostgreSQL · Twilio SMS · Docker · Custom scrapers This kind of system works for any business that needs to: Find leads from multiple sources automatically Score and filter them by quality Reach out at scale without a sales team If that sounds like something your business needs, let's talk.
1
115
Cover image for AI-Powered Business Content Generator: Documents
AI-Powered Business Content Generator: Documents to Publish-Ready Content in Minutes
0
61
Cover image for AI CAM: Multi-Agent Content Automation
AI CAM: Multi-Agent Content Automation That Turns Documents Into Publish-Ready Marketing Copy
0
66
Cover image for Nemotron-3 120B Deployed on NVIDIA
Nemotron-3 120B Deployed on NVIDIA Blackwell DGX Spark — 16.4 tokens/sec in Under 2 Hours
0
53
Docker Compose(1)