Vicarius is an AI-powered cybersecurity platform focused on identifying, prioritizing, and remediating software vulnerabilities. It utilizes advanced detection algorithms to analyze a company's software environment, providing actionable insights and solutions. By automating the vulnerability management process, Vicarius allows organizations to proactively safeguard their digital assets and minimize risks associated with cyber threats.

StopScam utilizes machine learning algorithms to analyze online content, detect suspicious patterns, and report scams effectively. Users can benefit from real-time alerts about potential fraud, ensuring their online interactions are secure. By providing educational resources, the AI also empowers users to avoid falling victim to scams.

Amplify Security is an AI-driven platform designed to enhance cybersecurity measures by utilizing machine learning algorithms for threat detection, incident response, and security analytics. It automates routine security tasks, allowing organizations to quickly identify and mitigate risks, ensuring comprehensive protection against evolving threats.

The self-parking car AI Agent utilizes advanced sensors and algorithms to assist vehicles in parking automatically. By processing real-time data from its surroundings, the AI can maneuver the vehicle into parking spots accurately, whether parallel or perpendicular. This technology reduces the risk of collisions and enhances the efficiency of the parking process, driving innovations in automotive convenience and safety for users.

Llama Guard is an AI-driven agent focused on cybersecurity. It continuously monitors network activity, identifies potential threats, and automatically responds to mitigate risks. By utilizing machine learning algorithms, Llama Guard adapts to new vulnerabilities, providing real-time protection for organizations. Its functionalities include threat analysis, incident response, and compliance management, making it an essential tool for safeguarding critical information and minimizing security breaches.

The AI Agent PPE Kit Detection uses advanced computer vision techniques to identify and verify the presence of PPE kits in various environments. This technology is crucial for organizations aiming to maintain safety protocols, especially in high-risk industries. The agent can analyze camera feeds in real-time, alerting managers if any personnel are not wearing required safety gear, thereby reducing the likelihood of workplace accidents.

Shield AI uses advanced artificial intelligence to power its autonomous drone systems, providing unmatched capabilities in defense, surveillance, and reconnaissance. Their autonomous agents are designed to operate in challenging environments, enabling military and security forces to enhance operational efficiency and safety.

RAG for Cybersecurity combines the power of large language models with vector-based retrieval to transform how security teams access and analyze cybersecurity information. Users begin by ingesting documents such as MITRE ATT&CK matrices, CVE entries, and security advisories. The framework then generates embeddings for each document and stores them in a vector database. When a user submits a query, RAG retrieves the most relevant document chunks, passes them to the LLM, and returns precise, context-rich responses. This approach ensures answers are grounded in authoritative sources, reducing hallucinations while improving accuracy. With customizable data pipelines and support for multiple embeddings and LLM providers, teams can tailor the system to their unique threat intelligence needs.

AI Agent with Cybersecurity is a versatile open-source AI framework designed to streamline and enhance security operations. It harnesses the power of large language models to perform threat hunting, vulnerability scanning, log analysis, malicious payload generation, and automated incident response. The agent can integrate with popular security APIs like Shodan, VulnDB, VirusTotal, and SIEM platforms. Its plugin-based architecture enables developers to extend capabilities for custom security workflows, such as phishing detection or compliance auditing. Deployable on-premise or in the cloud, it accelerates security teams' workflows, reducing manual effort, improving detection accuracy, and enabling faster remediation.

Radiant Security leverages powerful artificial intelligence to enhance cybersecurity by providing real-time threat detection, automated incident response, and compliance management. Its platform analyzes network activity to identify potential security threats and responds instantly to mitigate risks. By integrating machine learning, it continuously learns from new threats, ensuring that enterprises are always protected against the latest vulnerabilities.

Enkrypt AI offers robust solutions for secure document encryption, enabling users to protect their sensitive data effectively. This AI agent utilizes advanced algorithms to encrypt files, making them accessible only to authorized users. With features such as automatic encryption, user authentication, and easy sharing capabilities, Enkrypt AI empowers individuals and organizations to safeguard their information against unauthorized access and data breaches.

Offensive Graphs leverages advanced machine learning algorithms to seamlessly ingest diverse network data sources such as firewall rules, Active Directory configurations, cloud assets, and vulnerability scanner outputs. It automatically constructs comprehensive attack graphs that reveal the most effective lateral movement and privilege escalation paths an adversary might exploit. Users can interactively explore these graphs in a user-friendly web interface, apply filters by risk level or asset criticality, and drill down into detailed risk factors. The platform also prioritizes remediation tasks based on aggregated threat scores and generates customizable reports to support compliance and incident response. By automating complex threat modeling, Offensive Graphs significantly reduces manual effort while enhancing the accuracy and coverage of security assessments.

Aident.ai leverages advanced machine learning models to authenticate identities by comparing user selfies with government-issued ID photos. The platform features multi-step document scanning with OCR to extract and verify personal data, AI-driven liveness detection to prevent spoofing attacks, and automated fraud analysis that flags suspicious submissions in real time. Developers can integrate Aident using RESTful APIs or SDKs for iOS, Android, and JavaScript, enabling flexible deployment across web and mobile applications. Built-in compliance modules support global KYC and AML regulations, including GDPR and eIDAS. Aident’s dashboard offers live monitoring, detailed audit logs, and customizable workflows to optimize onboarding efficiency, reduce operational costs, and enhance security for businesses in finance, e-commerce, crypto, and more.

Ostorlab leverages machine learning and automated scanning engines to perform end-to-end mobile app security assessments. Developers upload app binaries or connect repositories, and Ostorlab’s AI performs static code analysis, dynamic runtime testing, and network traffic inspection. The platform highlights critical, high, and medium-risk issues, offers remediation guidance, and integrates into development workflows for continuous monitoring and compliance management.

Deep Threat Model leverages GPT-driven algorithms to analyze your application’s architecture and automatically generate comprehensive threat model diagrams. After specifying the application name and a brief description, the tool identifies assets, categorizes trust boundaries, and enumerates threat actors. It then maps potential attack vectors and suggests security controls, outputting the results in editable Mermaid or PlantUML notation. The AI engine ensures consistency across diagrams, flagging missing controls and highlighting high-risk components. Diagrams can be exported, refined manually, or integrated into CI/CD pipelines for continual security reviews. This streamlined approach reduces manual effort, minimizes errors in threat identification, and accelerates security documentation for development and compliance teams.

VIPER is a comprehensive AI Red Team Platform that empowers organizations to conduct advanced adversary emulation and penetration testing. Combining AI-guided decision-making with a suite of built-in modules, VIPER automates the creation of attack chains based on targeted objectives, executes customized vulnerability scans, and orchestrates post-exploitation activities across multiple endpoints. Its intelligent orchestration engine adapts tactics in real-time, optimizing payload delivery and lateral movement strategies. Users manage sessions through a secure web interface, collaborate in live environments, and generate detailed analytical reports automatically. With support for custom module integrations and flexible deployment on Linux, VIPER streamlines red team operations, reduces manual overhead, and enhances organizational resilience against evolving cyber threats.

Privasea is an AI-driven agent designed to protect user data and online privacy. It utilizes machine learning and proactive monitoring to detect potential threats, manage data breaches, and offer personalized privacy solutions. Users can navigate their online presence securely, with features designed for real-time alerts for suspicious activities, secure data management, and privacy management across various platforms. Privasea is ideal for users concerned about data privacy and looking for a reliable way to safeguard their online activities.

Amplifier Security leverages artificial intelligence to provide dynamic threat detection, real-time monitoring, and detailed reporting for businesses. Its AI-driven features allow for faster identification of vulnerabilities and automatic responses to potential breaches. This ensures comprehensive security management, enhancing organizational resilience against persistent cyber threats.

Secure Agent Augmentation provides a Python SDK and set of helper modules to wrap AI agent tool calls with security controls. It supports integration with popular LLM frameworks like LangChain and Semantic Kernel, and connects to secret vaults (e.g., HashiCorp Vault, AWS Secrets Manager). Encryption-at-rest and in-transit, role-based access control, and audit trails ensure that agents can augment their reasoning with internal knowledge bases and APIs without exposing sensitive data. Developers define secured tool endpoints, configure authentication policies, and initialize an augmented agent instance to run secure queries against private data sources.

Agentic-IAM leverages a large language model to transform natural language prompts into AWS identity and access management configurations. Users describe desired roles, permissions, and security requirements in plain English, and the agent crafts least-privilege IAM policies, builds CloudFormation templates, flags potential vulnerabilities, and optionally deploys changes via AWS APIs. Policy drafts can be reviewed, refined, and versioned automatically. Integration with AWS CLI and SDK ensures seamless end-to-end automation of IAM tasks, from initial design through application and audit.