The Automated Vulnerability Scanning with Agentic AI project leverages large language models to autonomously plan, execute, and report on security assessments. By integrating tools like Bandit for static analysis, Nmap for network enumeration, and CVE databases for vulnerability matching, the agent creates a step-by-step scanning workflow. It analyzes code repositories for insecure patterns, probes network ports for exposed services, correlates findings with known vulnerabilities, and generates an actionable report with risk ratings and remediation guidance. Users can customize scanning pipelines, define target scopes, and integrate results into existing CI/CD pipelines. This LLM-driven agentic framework reduces manual effort and accelerates the discovery and mitigation of security risks across applications and infrastructure.

Patrolling-Zoo offers a flexible framework enabling users to create and experiment with multi-agent patrolling tasks in Python. The library includes a variety of grid-based and graph-based environments, each simulating surveillance, monitoring, and coverage scenarios. Users can configure the number of agents, map size, topology, reward functions, and observation spaces. Through compatibility with PettingZoo and Gym APIs, it supports seamless integration with popular reinforcement learning algorithms. This environment facilitates benchmarking and comparing MARL techniques under consistent settings. By providing standard scenarios and tools to customize new ones, Patrolling-Zoo accelerates research in autonomous robotics, security surveillance, search-and-rescue operations, and efficient area coverage using multi-agent coordination strategies.

AIShieldNet offers a comprehensive cybersecurity solution powered by advanced AI and machine learning algorithms. It provides real-time analysis and threat detection to protect against zero-day ransomware, phishing attacks, malware, and viruses. With a cloud-based architecture, it offloads processing from endpoints, enabling efficient and swift threat mitigation. The platform supports file analysis including Excel, Word documents, and PDFs to ensure no hidden threats escape unaddressed. It also features customizable defense modes and a user-friendly SaaS reporting dashboard for monitoring and fine-tuning security measures.

Cat's Eye is an AI-driven system engineered to enhance the security of educational institutions by identifying and mitigating bullying and violent behavior. By receiving audio and visual inputs, the system analyzes data for signs of conflict, triggering real-time alerts to school staff. This timely intervention enables schools to act immediately, ensuring a safer environment for students. The product also provides detailed incident reports for comprehensive analysis, supporting effective resolution and long-term prevention strategies.

Overwatch Data is an AI-driven intelligence platform designed to monitor and analyze data streams from various sources, including news, social media, and the deep web. It provides real-time, actionable insights tailored for security, fraud detection, and strategic teams, helping them make informed decisions by cutting through noise and delivering the most critical information directly.

Samsung Ballie is an innovative AI agent that seamlessly integrates with your home environment to offer a range of functionalities including security monitoring, smart device control, and personalized communication. Equipped with advanced sensors and machine learning capabilities, Ballie can navigate your home, monitor activities, and even interact with family members through voice commands. It learns user preferences over time, providing a custom-tailored experience that enhances home life.