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.

Backmesh is a thoroughly tested Backend as a Service (BaaS) that offers an LLM API Gatekeeper, allowing your app to securely call LLM APIs. Using JWT authentication, configurable rate limits, and API resource access control, Backmesh ensures that only authorized users have access while preventing API abuse. Additionally, it provides LLM user analytics without extra packages, enabling identification of usage patterns, cost reduction, and improvements in user satisfaction.

NoPromptInjections is an advanced AI tool designed to detect and mitigate prompt injection attacks. It ensures the integrity and security of AI systems by preventing malicious inputs that could compromise their functionality. This tool is essential for developers and organizations looking to protect their AI-powered applications from potential threats, offering a robust solution to maintain data accuracy and system reliability.