Alternatives to GuardionAI

CrowdStrike Falcon is a cutting-edge cybersecurity platform that operates in the cloud, delivering robust defenses against a variety of cyber threats such as malware, ransomware, and complex attacks. By utilizing artificial intelligence and machine learning technologies, it enables real-time detection and response to potential security incidents, while offering features like endpoint protection, threat intelligence, and incident response. The system employs a lightweight agent that consistently scans endpoints for any indicators of malicious behavior, ensuring visibility and security with minimal effect on overall system performance. Falcon's cloud-based framework facilitates quick updates, adaptability, and swift threat responses across extensive and distributed networks. Its extensive suite of security functionalities empowers organizations to proactively prevent, identify, and address cyber risks, establishing it as an essential resource for contemporary enterprise cybersecurity. Additionally, its seamless integration with existing infrastructures enhances overall security posture while minimizing operational disruptions.

Heimdal® Endpoint Detection and Response is our proprietary multi-solution service providing unique prevention, threat-hunting, and remediation capabilities. It combines the most advanced threat-hunting technologies in existence: Heimdal Next-Gen Antivirus, Heimdal Privileged Access Management, Heimdal Application Control, Heimdal Ransomware Encryption Protection, Heimdal Patch & Asset Management, and Heimdal Threat Prevention. With 6 modules working together seamlessly under one convenient roof, all within one agent and one platform, Heimdal Endpoint Detection and Response grants you access to all the essential cybersecurity layers your business needs to protect itself against both known and unknown online and insider threats. Our state-of-the-art product empowers you to quickly and effortlessly respond to sophisticated malware with stunning accuracy, protecting your digital assets and your reputation in the process as well.

Snapper serves as a comprehensive security platform for AI agents, aimed at ensuring thorough governance and protection for organizations that utilize AI across various applications, networks, and systems. It implements runtime enforcement by scrutinizing every action an agent takes, such as tool interactions, API calls, and data access requests, prior to execution, utilizing a multi-layered policy-driven rule engine. Additionally, Snapper provides a holistic view of AI activity by analyzing network traffic, browser usage, DNS queries, and running processes to uncover unauthorized tools and hidden AI applications. It also proactively intercepts outgoing large language model requests via SDK wrappers and a network proxy, allowing it to assess, redact, and document sensitive information in real time. Enhancing its security features, Snapper possesses sophisticated threat detection mechanisms that can recognize prompt injection tactics, exploit chains, unusual behaviors, and complex attack patterns, leveraging behavioral baselines, kill chain analysis, and a composite trust scoring system for robust protection. Ultimately, Snapper represents a critical asset for organizations seeking to navigate the risks associated with AI deployment while maintaining operational integrity.

Akto is an open source, instant API security platform that takes only 60 secs to get started. Akto is used by security teams to maintain a continuous inventory of APIs, test APIs for vulnerabilities and find runtime issues. Akto offers tests for all OWASP top 10 and HackerOne Top 10 categories including BOLA, authentication, SSRF, XSS, security configurations, etc. Akto's powerful testing engine runs variety of business logic tests by reading traffic data to understand API traffic pattern leading to reduced false positives. Akto can integrate with multiple traffic sources - Burpsuite, AWS, postman, GCP, gateways, etc.

LangProtect serves as a cutting-edge security and governance platform specifically designed for AI, offering robust protection against issues such as prompt injections, jailbreaks, data leaks, and the generation of unsafe or non-compliant outputs in LLM and Generative AI applications. Tailored for production-grade GenAI environments, this platform implements real-time controls at the execution level of AI, meticulously examining prompts, model outputs, and function calls as they occur, enabling teams to intercept high-risk actions before they can affect end users or compromise sensitive information. By doing so, LangProtect ensures that potential threats are neutralized promptly, preserving the integrity of data and user interactions. Furthermore, LangProtect seamlessly integrates with existing LLM infrastructures through an API-first design that maintains low latency, accommodating various deployment models including cloud, hybrid, and on-premise solutions to meet the security and data residency requirements of enterprises. It is also equipped to safeguard contemporary architectures like RAG pipelines and agentic workflows, providing policy-driven enforcement, continuous monitoring, and governance that is ready for audits. This comprehensive approach ensures that organizations can confidently leverage AI technologies while minimizing risks associated with their deployment.

Straiker is an innovative security platform designed exclusively for safeguarding enterprise AI applications and autonomous agents, particularly addressing the emerging hazards posed by “agentic AI” systems that engage with various tools, APIs, and sensitive data. By offering comprehensive visibility and control throughout the entire AI stack, it analyzes behavioral signals from models, prompts, tools, identities, and infrastructure, which facilitates the immediate detection and prevention of AI-specific threats, including prompt injection, privilege escalation, data exfiltration, and the misuse of tools. The platform integrates continuous discovery, adversarial testing, and runtime protection through essential components such as Discover AI, Ascend AI, and Defend AI, working in harmony to identify all active agents, simulate potential attacks to reveal weaknesses, and implement real-time protective measures during operation. Its intricate, multi-layered architecture captures profound contextual signals from user interactions, network activities, and agent workflows, ensuring a robust defense against evolving threats. As AI technologies continue to advance, the necessity for such tailored security solutions will become increasingly critical for enterprises navigating this complex landscape.

F5 AI Guardrails is an enterprise AI security platform that provides runtime protection for deployed AI models, agents, and applications across diverse environments. The solution is designed to address emerging AI risks by monitoring interactions, enforcing policies, and preventing malicious attempts to manipulate AI behavior. Organizations can use the platform to defend against prompt injection attacks, jailbreak techniques, data leakage incidents, and other adversarial threats targeting AI systems. Distributed data protection capabilities inspect AI interactions in real time and help enforce data loss prevention policies across applications and models. The platform includes automated compliance features that support frameworks and regulations such as GDPR, HIPAA, and the European Union AI Act. Advanced observability and auditing tools provide detailed records of AI activity, enabling stronger governance and accountability. F5 AI Guardrails also supports dynamic model routing and low-latency security controls to maintain operational performance while enforcing protections. Model-agnostic functionality allows organizations to secure both proprietary and open-source AI models using a unified approach. By integrating security, compliance, observability, and runtime protection, F5 AI Guardrails helps organizations confidently scale their AI initiatives.

Silmaril is an innovative defense mechanism against prompt injection that autonomously heals itself, aiming to safeguard AI systems from sophisticated, multi-layered threats that conventional barriers cannot mitigate. Unlike traditional methods that merely filter inputs, it envelops inference calls, assessing whether the sequence of actions is steering towards a detrimental result. By employing a multihead classifier, it evaluates user intentions, application contexts, and execution states simultaneously, which allows it to identify indirect injections, multi-turn attack sequences, context manipulation, and tool exploitation before any harm can occur. To enhance its protective capabilities, Silmaril incorporates autonomous threat-hunting agents that explore systems, identify weaknesses, and produce synthetic training data based on actual attack incidents. These findings facilitate automatic model retraining, allowing for the deployment of updated defenses in less than an hour, while simultaneously disseminating anonymized protective measures across all instances. Moreover, this proactive approach ensures that the system remains resilient against emerging threats, adapting continuously to the evolving landscape of cybersecurity challenges.

Proofpoint AI Security is an integrated solution aimed at assisting organizations in managing, monitoring, and safeguarding the deployment of AI technologies, including large language models and autonomous agents. This platform offers insight into both approved and unapproved AI activities, allowing security teams to identify unauthorized AI tools, track prompts and responses, and analyze AI interactions with sensitive information in real-time. By utilizing intent-based detection and behavioral analysis, it effectively spots anomalies, attempts at prompt injections, and potentially dangerous interactions, while simultaneously enforcing policies during operation to avert data breaches and misuse. Furthermore, it reconstructs comprehensive AI transactions from the initial user query to the actions and results produced by the agents, ensuring organizations maintain complete traceability and are prepared for audits. With its capabilities extending to endpoints, web browsers, and AI agent connections, it facilitates detailed access governance, guaranteeing that AI systems are restricted to utilizing and sharing only the necessary information. This comprehensive control enhances the overall security posture of the enterprise as it navigates the complexities of AI system integration.

Prisma AIRS AI Runtime Security is a specialized solution aimed at safeguarding applications, agents, models, and data that utilize LLM technology during their operational phases, providing real-time oversight, assurance, and governance throughout the AI lifecycle. This system continuously observes AI behavior, implementing protective measures that identify and mitigate threats which conventional security tools often overlook, such as prompt injection, harmful code, toxic outputs, data leakage, and unauthorized or unsafe actions. It empowers organizations to uncover all AI assets in operation, including shadow AI, while gaining insights into the interactions among agents, applications, and models across various environments. By consistently evaluating risk through the testing of AI systems, managing permissions, and monitoring the security posture in real-time, it incorporates controls that prevent manipulation and exposure during runtime engagements. With its adaptive defense mechanism, it protects against both evolving threats and zero-day vulnerabilities, leveraging real-time analysis of inputs, outputs, and execution processes. Ultimately, this innovative solution enhances an organization's ability to maintain a secure AI framework while promoting trust and compliance in AI deployments.

CrowdStrike Falcon AI Detection and Response (AIDR) serves as a comprehensive security solution aimed at safeguarding the quickly evolving AI attack landscape by offering immediate visibility, detection, and response capabilities across various AI systems, users, and their interactions. This platform grants a consolidated view of how both employees and AI agents engage with generative AI by elucidating the connections between users, prompts, models, agents, and the necessary infrastructure, while also recording in-depth runtime logs for purposes of monitoring, compliance, and investigation. By consistently overseeing AI operations across endpoints, cloud settings, and applications, organizations can gain insights into data movement within AI frameworks and how agents function within established limits. AIDR is adept at identifying and neutralizing AI-specific threats, including prompt injections, jailbreak attempts, malicious actors, harmful outputs, and unauthorized interactions, through the application of behavioral analysis alongside integrated threat intelligence. Additionally, the platform facilitates proactive threat management, allowing organizations to not only respond to incidents but also to anticipate potential vulnerabilities in their AI ecosystems.

Superagent is an open-source platform focused on AI safety and agent development, designed to assist developers and organizations in creating, deploying, and safeguarding AI-driven applications and assistants by incorporating essential safety measures, runtime security, and compliance controls into their agent workflows. It features purpose-trained models and APIs—such as Guard, Verify, and Redact—that effectively prevent prompt injections, malicious tool usage, data leaks, and unsafe outputs in real-time, while red-teaming tests evaluate production systems for vulnerabilities and provide actionable remediation strategies. Superagent seamlessly integrates with current AI systems at both inference and tool-call levels, enabling it to filter inputs and outputs, eliminate sensitive information like personally identifiable information (PII) and protected health information (PHI), enforce policy constraints, and prevent unauthorized actions before they can take place. Furthermore, it enhances security and engineering operations by offering comprehensive observability, live trace logs, policy controls, and detailed audit trails, ensuring that teams can maintain robust oversight of their AI systems at all times. Ultimately, Superagent empowers organizations to navigate the complexities of AI safety while facilitating the responsible use of innovative technologies.

OpenBox serves as a robust AI governance platform tailored for enterprises, aiming to ensure that AI systems remain transparent, auditable, and securely deployable on a large scale by instituting real-time monitoring of every action taken by agents and interactions within the system. By offering a cohesive governance framework, it amalgamates identity, policy, risk management, and compliance into a singular runtime environment, thereby addressing the common issue of fragmentation associated with using multiple tools and allowing organizations to maintain standardized oversight over AI activities. Seamlessly integrating with current AI workflows via a streamlined SDK, it necessitates no modifications to existing architectures while providing immediate insights into the operational behavior, decision-making processes, and inter-system communications of AI agents. Furthermore, OpenBox proactively supervises and assesses each action prior to its execution, implementing policy enforcement and regulatory evaluations instantaneously to avert any non-compliant or high-risk activities, ensuring a more preventative approach rather than simply responding to issues post-factum. This proactive stance not only enhances compliance but also fosters a culture of accountability in AI operations.

ZenGuard AI serves as a dedicated security platform aimed at safeguarding AI-powered customer service agents from various potential threats, thereby ensuring their safe and efficient operation. With contributions from specialists associated with top technology firms like Google, Meta, and Amazon, ZenGuard offers rapid security measures that address the risks linked to AI agents based on large language models. It effectively protects these AI systems against prompt injection attacks by identifying and neutralizing any attempts at manipulation, which is crucial for maintaining the integrity of LLM operations. The platform also focuses on detecting and managing sensitive data to avert data breaches while ensuring adherence to privacy laws. Furthermore, it enforces content regulations by preventing AI agents from engaging in discussions on restricted topics, which helps uphold brand reputation and user security. Additionally, ZenGuard features an intuitive interface for configuring policies, allowing for immediate adjustments to security measures as needed. This adaptability is essential in a constantly evolving digital landscape where threats to AI systems can emerge unexpectedly.

Lasso is an enterprise AI security platform built to secure AI agents, generative AI applications, and emerging agentic systems across complex business environments. The solution delivers end-to-end visibility into AI deployments by discovering, cataloging, and continuously monitoring AI assets throughout their lifecycle. Organizations can use the platform to identify models, prompts, tools, guardrails, and configurations while maintaining an up-to-date inventory of AI resources. Automated AI red teaming capabilities help uncover vulnerabilities, weaknesses, and attack vectors before they can be exploited in production environments. Runtime enforcement mechanisms monitor interactions in real time, ensuring AI systems operate within approved policies and security boundaries. The platform’s intent-based analysis approach helps detect threats that traditional security tools may miss due to the non-deterministic nature of AI behavior. Lasso also supports AI detection and response workflows that help security teams investigate incidents and mitigate risks more effectively. Enterprise-ready performance, scalability, and governance features make the platform suitable for organizations adopting AI at scale. By providing continuous visibility, protection, and risk management, Lasso helps businesses innovate confidently while reducing exposure to AI-related threats.

Operant AI offers comprehensive protection for all layers of contemporary applications, spanning from infrastructure to APIs. With a straightforward deployment that takes only minutes, Operant ensures complete security visibility and runtime controls, effectively thwarting a variety of both common and critical cyber threats such as data exfiltration, data poisoning, zero-day vulnerabilities, lateral movement, cryptomining, prompt injection, and beyond. This is achieved with no need for instrumentation, no drift, and minimal disruption for Development, Security, and Operations teams. Furthermore, Operant's in-line runtime safeguarding of all data in use during every interaction, from infrastructure to APIs, elevates the defense mechanisms for your cloud-native applications while requiring zero instrumentation, no alterations to application code, and no additional integrations, thus streamlining the security process significantly.

asqav is a cutting-edge platform focused on AI governance and security, aimed at ensuring that AI agents are always prepared for audits by offering real-time oversight, enforcement, and a reliable record of each action performed by the agents. It features a streamlined SDK that empowers developers to embed governance functionalities directly into their AI agents with minimal code, facilitating comprehensive monitoring throughout the entire lifecycle of AI activities. Additionally, the platform incorporates behavioral analysis to identify potential problems like drift, rate limits, and scope breaches, as well as sophisticated threat detection mechanisms that can recognize issues such as prompt injections, leaks of sensitive information, harmful outputs, and other dangers. Policy enforcement is achieved through customizable “policy gates,” which implement specific rules for each agent, conduct preflight assessments, and provide dynamic approvals before any actions are taken, thereby guaranteeing that agents function within established parameters. Furthermore, asqav enhances security with automated incident response features, allowing for the suspension, isolation, or escalation of agents deemed risky, all of which contribute to a robust framework for maintaining AI accountability and safety. In this way, asqav not only safeguards AI operations but also promotes trust in their deployment across various sectors.

iDox.ai Guardrail serves as an immediate security measure for AI applications, designed to safeguard sensitive information from being exposed during generative AI tasks. This innovative solution functions at the endpoint, intercepting user prompts, uploaded files, and any AI interactions prior to data transmission from the device. Guardrail employs policy-driven mechanisms to identify and prevent the leakage of sensitive information, including personally identifiable information (PII), protected health information (PHI), payment card information (PCI), intellectual property, and other confidential business data. In contrast to conventional data loss prevention (DLP) systems, Guardrail is tailored specifically for AI applications. It continuously observes user engagement with AI platforms like ChatGPT, Microsoft Copilot, and Claude, applying protective measures in real-time to ensure security. Among its key features are: - Continuous monitoring of prompts and file submissions - Detection of sensitive data with AI awareness - Real-time anonymization and sanitization processes - Defense against risks associated with AI agents, such as unauthorized file access incidents (e.g., OpenClaw) - Implementation of website whitelisting and strict policy enforcement. Additionally, Guardrail enhances user confidence in utilizing AI technologies while ensuring compliance with data privacy regulations.

TrojAI is a comprehensive AI security solution built to address the unique risks associated with generative AI, large language models, and autonomous AI agents. The platform helps organizations identify, assess, and mitigate vulnerabilities before AI systems are deployed into production environments. Through its security testing capabilities, TrojAI uncovers weaknesses that could lead to prompt injection, data leakage, jailbreak attacks, tool misuse, or unauthorized behavior. Runtime protection features continuously monitor AI applications and agent activities to detect and block threats as they occur. The platform also helps organizations align with security frameworks such as OWASP, NIST, and MITRE, simplifying governance and compliance initiatives. TrojAI Detect focuses on securing AI models during development and testing phases, helping teams strengthen models before release. TrojAI Defend provides real-time protection for deployed AI systems, reducing the risk of operational disruptions and security incidents. Flexible deployment options allow organizations to integrate the platform into cloud, hybrid, or self-hosted environments while maintaining control over sensitive data. By combining proactive testing with continuous monitoring, TrojAI helps enterprises build and operate secure AI ecosystems.

EarlyCore serves as a dedicated security platform tailored for AI agents, streamlining the processes of pre-production attack testing, real-time surveillance, and compliance documentation throughout the entire lifecycle of the agents. It evaluates agents against a myriad of attack vectors, such as prompt injection, jailbreaking, data theft, tool misuse, and supply chain vulnerabilities. Once deployed, it continuously monitors each agent's actions, establishes typical behavioral patterns, and identifies anomalies in real time, with alerts sent via Slack, email, or webhooks. The platform automatically generates compliance documentation aligned with standards like ISO 42001, NIST AI RMF, EU AI Act, SOC 2, and GDPR, ensuring that users remain audit-ready at all times. With a rapid deployment time of just 15 minutes and no need for code alterations, it offers seamless integration with services like AWS Bedrock, Gemini Enterprise Agent Platform, LangChain, among others. It also provides multi-tenant support, making it an ideal choice for agencies and Managed Security Service Providers (MSSPs). Designed specifically for security teams, agencies, and MSSPs, EarlyCore empowers organizations to secure AI agents efficiently at scale while maintaining high compliance and security standards.

Cisco AI Defense represents an all-encompassing security framework aimed at empowering businesses to securely create, implement, and leverage AI technologies. It effectively tackles significant security issues like shadow AI, which refers to the unauthorized utilization of third-party generative AI applications, alongside enhancing application security by ensuring comprehensive visibility into AI resources and instituting controls to avert data breaches and reduce potential threats. Among its principal features are AI Access, which allows for the management of third-party AI applications; AI Model and Application Validation, which performs automated assessments for vulnerabilities; AI Runtime Protection, which provides real-time safeguards against adversarial threats; and AI Cloud Visibility, which catalogs AI models and data sources across various distributed settings. By harnessing Cisco's capabilities in network-layer visibility and ongoing threat intelligence enhancements, AI Defense guarantees strong defense against the continuously changing risks associated with AI technology, thus fostering a safer environment for innovation and growth. Moreover, this solution not only protects existing assets but also promotes a proactive approach to identifying and mitigating future threats.

Notenic serves as a runtime orchestration and governance platform aimed at managing and securing autonomous AI agents, also known as "digital labor," in real-time scenarios where failures could lead to significant regulatory, legal, or operational repercussions. Functioning as an infrastructure layer, it integrates directly into the execution path of AI systems to enforce strict governance protocols prior to any interaction with systems of record, thus avoiding the limitations of post-output filters or controls applied at the prompt level. The platform incorporates a zero-trust runtime architecture characterized by foundational principles such as zero-persistence, which ensures no data is retained after each session, and execution-path control that enforces policies right at the moment actions are taken. This design also emphasizes independence from model context, effectively preventing any adversarial inputs from compromising governed behavior. In addition, Notenic offers a comprehensive control plane that encompasses the management of AI agents, treating them as operational units with clearly defined roles and appropriate oversight, which enhances organizational efficiency and accountability. This robust framework ultimately ensures that AI operations are conducted within a secure and compliant environment.

Cortex AgentiX is an advanced AI agent orchestration platform from Palo Alto Networks that transforms how security teams automate and respond to threats. Built as the next generation of Cortex XSOAR®, it enables organizations to deploy AI agents that function as always-on digital teammates. These agents leverage billions of prior playbook executions to plan, reason, and execute complex security workflows with confidence. Cortex AgentiX provides flexibility through a comprehensive catalog of prebuilt agents as well as no-code tools for creating custom agents. The platform allows security leaders to define when agents operate autonomously and when human oversight is required. Strong access controls and permissions ensure agents follow the same governance rules as human analysts. Cortex AgentiX delivers complete transparency into agent behavior, eliminating black-box decision-making. Native support for natural language automation simplifies the creation of executable workflows. With over 1,000 prebuilt integrations, the platform connects easily to existing security tools. Cortex AgentiX helps organizations scale security operations while maintaining control, accountability, and compliance.

MCP Defender is an innovative open-source desktop application that serves as an AI firewall, specifically designed to oversee and safeguard communications related to the Model Context Protocol (MCP). By functioning as a secure proxy between AI applications and MCP servers, it meticulously analyzes all communications in real-time to detect potential threats. This application automatically scans and secures all MCP tool calls, leveraging advanced LLM capabilities to identify malicious activities effectively. Users have the flexibility to manage the signatures utilized during the scanning process, enabling tailored security measures that fit their specific needs. MCP Defender excels in recognizing and preventing a range of AI security threats, such as prompt injection, credential theft, arbitrary code execution, and remote command injection. It seamlessly integrates with numerous AI applications, including Cursor, Claude, Visual Studio Code, and Windsurf, with plans for expanded compatibility in the future. The application provides intelligent threat detection and promptly alerts users as soon as it detects any malicious actions perpetrated by AI applications, ensuring a robust defense against evolving threats. Ultimately, MCP Defender empowers users with enhanced security and peace of mind in their AI interactions.

DryRun Security is an AI Native SAST and Agentic Code Security engine built to improve application security without burying teams in alerts. Traditional SAST flags patterns. DryRun Security adds context. Our proprietary Contextual Security Analysis engine reasons about code intent, exploitability, and impact, so AppSec focuses on what matters. In pull requests, the Code Review Agent posts PR comments and checks within moments of a push, with guidance developers can act on immediately. It uses specialized analyzers for common vulnerability classes like XSS, SQL injection, SSRF, IDOR, mass assignment, and secrets. For guardrails that match your environment, teams write Natural Language Code Policies in plain English and the Custom Policy Agent enforces them on every PR. When you need a deeper read, DeepScan Agent produces a prioritized full-repo report in about an hour, surfacing complex logic, authentication and authorization flaws, secrets exposure, and business-risk vulnerabilities. Code Insights Agent helps teams see trends across repos and produce audit-ready reporting faster. DryRun Security is designed for GitHub and GitLab permissioned workflows. It protects security with private LLM capabilities, avoids sending code to public AI systems, processes with ephemeral services, and retains only findings and minimal metadata for reporting.

middleBrick is a frictionless security scanner specifically crafted for APIs and AI models, catering to the needs of high-performance engineering teams. Unlike conventional scanners that necessitate intricate agents or user credentials, middleBrick offers a thorough security evaluation in less than 60 seconds by merely examining an endpoint URL. Its coverage encompasses 14 essential security categories: the complete OWASP API Top 10 (including BOLA/IDOR, BFLA, Mass Assignment, and SSRF); AI/LLM Security, featuring 18 adversarial probes aimed at detecting prompt injection, jailbreaks, and data leakage; and Web3 & DeFi, which includes specialized scans for JSON-RPC nodes across Ethereum, Solana, and Cosmos, as well as ensuring the integrity of price oracles. Designed to seamlessly integrate into contemporary workflows, middleBrick supports a GitHub Action, a command-line interface (CLI), and an MCP server compatible with Claude and Cursor. This tool not only delivers prioritized security findings but also provides actionable remediation steps, empowering developers to deploy secure code without delay. Think of middleBrick as the vigilant "smoke alarm" for your API ecosystem, consistently monitoring and only notifying you when significant threats arise. Its swift and efficient operation makes it an indispensable asset for modern development teams.

GolfMCP serves as an open-source framework aimed at simplifying the development and deployment of production-ready Model Context Protocol (MCP) servers, which empowers organizations to construct a secure and scalable infrastructure for AI agents without the hassle of boilerplate code. Developers can effortlessly define tools, prompts, and resources using straightforward Python files, while Golf takes care of essential tasks like routing, authentication, telemetry, and observability, allowing you to concentrate on the core logic rather than underlying plumbing. The platform incorporates enterprise-level authentication methods such as JWT, OAuth Server, and API keys, along with automatic telemetry and a file-based organization that removes the need for decorators or manual schema configurations. It also features built-in utilities that facilitate interactions with large language models (LLMs), comprehensive error logging, OpenTelemetry integration, and deployment tools like a command-line interface with commands for initializing, building, and running projects. Furthermore, Golf includes the Golf Firewall, a robust security layer tailored for MCP servers that enforces strict token validation to enhance the overall security framework. This extensive functionality ensures that developers are equipped with everything they need to create efficient AI-driven applications.

AQtive Guard serves as a comprehensive cybersecurity solution designed to assist organizations in safeguarding and overseeing their cryptographic assets alongside non-human identities (NHIs) like AI agents, keys, certificates, algorithms, and machine identities throughout their IT infrastructure. The platform provides ongoing discovery and immediate visibility into both NHIs and cryptographic elements, seamlessly integrating with current security tools, cloud services, and repositories to deliver a cohesive understanding of security status. By leveraging cutting-edge AI and extensive quantitative models, AQtive Guard evaluates vulnerabilities, ranks risks, and presents actionable insights with automated remediation workflows that address issues and uphold policies such as credential rotation and certificate renewal. Furthermore, the platform ensures compliance with the latest standards, including emerging NIST cryptographic protocols, while facilitating the lifecycle management of cryptographic assets to mitigate risks associated with both present and future threats. In this way, AQtive Guard not only fortifies security but also enhances organizational resilience against evolving cyber challenges.

Bricklayer AI represents a cutting-edge autonomous security team designed to elevate Security Operations Centers (SOCs) by efficiently handling alerts from endpoints, cloud environments, and SIEM systems. Its innovative multi-agent framework replicates the workflows of human teams, which facilitates seamless collaboration between AI analysts, incident responders, and human specialists. Among its standout features are automated triage of alerts, prompt incident responses, and comprehensive threat intelligence analysis, all operable via natural language commands. The platform integrates smoothly with pre-existing tools and processes, enabling organizations to create tailored API integrations that can pull data from their entire technological ecosystem. By utilizing Bricklayer AI, organizations can lower their monitoring expenses, enhance the speed of threat detection and response, and expand operations without requiring additional personnel. Moreover, its focus on action-oriented tasking guarantees that each alert is thoroughly investigated, feedback is effectively communicated, and responses are provided in real time, ultimately fostering a more proactive security posture. This ensures that organizations remain vigilant against emerging threats while streamlining their security operations.

VoltusWave is an advanced platform for enterprise AI agent workforces that transcends the limitations of standalone automation tools by integrating intelligent agents within a comprehensive execution framework capable of managing end-to-end business processes. This platform offers a cohesive environment where AI agents can interpret documents, make informed decisions, carry out workflows, and address exceptions, all while ensuring full audit trails and human intervention capabilities are in place. It operates through six interconnected engines, which include process orchestration, rules enforcement, document generation, integration infrastructure, no-code application development, and a regulated AI agent workforce, empowering organizations to efficiently manage intricate operations like procure-to-pay or enterprise-to-cash cycles with minimal human input. These AI agents function across all operational layers, dealing with tasks related to documents, approvals, reconciliations, compliance verification, and customer communications, while a robust rules engine guarantees that every action adheres to established guidelines with complete version control and traceability. This holistic approach not only streamlines processes but also enhances overall efficiency and accountability within the organization.

WebOrion Protector Plus is an advanced firewall powered by GPU technology, specifically designed to safeguard generative AI applications with essential mission-critical protection. It delivers real-time defenses against emerging threats, including prompt injection attacks, sensitive data leaks, and content hallucinations. Among its notable features are defenses against prompt injection, protection of intellectual property and personally identifiable information (PII) from unauthorized access, and content moderation to ensure that responses from large language models (LLMs) are both accurate and relevant. Additionally, it implements user input rate limiting to reduce the risk of security vulnerabilities and excessive resource consumption. Central to its robust capabilities is ShieldPrompt, an intricate defense mechanism that incorporates context evaluation through LLM analysis of user prompts, employs canary checks by integrating deceptive prompts to identify possible data breaches, and prevents jailbreak attempts by utilizing Byte Pair Encoding (BPE) tokenization combined with adaptive dropout techniques. This comprehensive approach not only fortifies security but also enhances the overall reliability and integrity of generative AI systems.

Workplace usage of AI tools such as ChatGPT, Copilot, Claude, and DeepSeek has surged, frequently occurring without the necessary oversight from IT departments. An alarming 78% of employees acknowledge utilizing ChatGPT for professional purposes, thereby exposing sensitive information like financial data, API keys, passwords, source code, and personal records to potential risks. Traditional Data Loss Prevention (DLP) solutions and proxies are inadequately equipped to handle this new form of threat. Enter ZeusLock, a DLP solution specifically designed for the AI-driven landscape. It seamlessly identifies and prevents sensitive data from being transmitted to any AI service, ensuring security. The installation process is rapid, taking merely two minutes through a browser extension and a workstation agent, and it effectively protects web applications, integrated development environments (IDEs), command terminals, and AI agents via its Multi-Channel Protection (MCP) system. When a threat is identified, ZeusLock either notifies the user or blocks the action, depending on established policies, while meticulously recording every incident for comprehensive auditing. Additionally, it offers protection against various attacks, including Prompt Injection and Jailbreak attacks, as well as unauthorized shadow AI applications like DeepSeek. The detection capabilities operate locally, utilizing a machine learning API based in Europe to guarantee data sovereignty, all while maintaining zero latency and ensuring no hindrance to productivity. This innovative approach not only fortifies data security but also empowers organizations to embrace AI tools with confidence.

General Analysis serves as a cutting-edge AI security platform designed to aid security teams in adversarially testing, monitoring, and safeguarding AI agents and systems that are actively deployed. Its primary objective is to enable organizations to grasp AI-related risks, avert potential incidents, and secure various real-world AI applications, which include employee copilots, coding agents, customer support tools, healthcare assistants, legal aids, financial copilots, and creative workflows. By mapping out AI applications and agents through an extensive range of parameters such as prompts, retrieval methods, tools, MCP servers, browser activities, permissions, repositories, cloud accounts, SaaS workflows, and business processes, it effectively identifies context-aware attacks that highlight vulnerabilities within the system. The platform's automated red teaming employs adaptable attacker models that respond to target behaviors and generate complex multi-step exploit chains, providing security teams with the ability to discover vulnerabilities that traditional static prompt sets or endpoint-only testing might overlook. Ultimately, General Analysis empowers organizations to enhance their AI security posture while ensuring that their deployments remain resilient against evolving threats.

nono is a novel open-source sandbox that utilizes kernel enforcement to create a secure environment for AI coding agents and LLM tasks. In contrast to traditional policy-based guardrails that merely monitor and filter operations, nono leverages operating system security features—specifically Landlock on Linux and Seatbelt on macOS—to render unauthorized operations impossible at the syscall level. With just a single command, you can encapsulate any AI agent, including Claude Code, OpenCode, OpenClaw, or any command-line interface process. The system automatically enforces a default-deny policy for filesystem access, restricts harmful commands (such as rm, dd, chmod, and sudo), isolates sensitive credentials and API keys, and extends all imposed restrictions to any child processes, ensuring there's no avenue for escape once limitations are set. Built-in profiles allow for rapid deployment, and secrets can be injected from the system keystore in a secure manner, with automatic zeroization upon exit. Additionally, future enhancements such as audit logging, atomic rollbacks, and Sigstore-attested policy signing are planned, offering robust tracking and security features. It operates under the Apache 2.0 license and is developed by the same creator behind Sigstore, further emphasizing its credibility and reliability in securing AI workloads.

Gray Swan is a comprehensive AI security and evaluation platform designed to empower organizations to implement AI solutions confidently while safeguarding LLM applications, agents, and model deployments against evolving threats, policy breaches, and harmful content. It seamlessly integrates with any LLM provider, enhancing security measures without interrupting existing workflows, and combines automated adversarial testing, ongoing red teaming, runtime supervision, and adaptive defenses. By leveraging threat intelligence from over 15,000 adversarial researchers and more than three million simulated attack attempts generated through its Arena, Gray Swan goes beyond merely identifying known threats to help teams uncover vulnerabilities prior to their documentation in public databases. Its primary offerings include Shade, a cutting-edge AI vulnerability assessment platform that continuously evaluates LLMs akin to a dedicated security researcher operating around the clock, and Cygnal, which acts as a protective layer for real-time AI interactions and monitoring. With these tools, organizations can proactively anticipate and mitigate risks associated with AI deployments.

Enhance your observability framework to swiftly identify data and machine learning challenges, facilitate ongoing enhancements, and prevent expensive incidents. Begin with dependable data by consistently monitoring data-in-motion to catch any quality concerns. Accurately detect shifts in data and models while recognizing discrepancies between training and serving datasets, allowing for timely retraining. Continuously track essential performance metrics to uncover any decline in model accuracy. It's crucial to identify and mitigate risky behaviors in generative AI applications to prevent data leaks and protect these systems from malicious attacks. Foster improvements in AI applications through user feedback, diligent monitoring, and collaboration across teams. With purpose-built agents, you can integrate in just minutes, allowing for the analysis of raw data without the need for movement or duplication, thereby ensuring both privacy and security. Onboard the WhyLabs SaaS Platform for a variety of use cases, utilizing a proprietary privacy-preserving integration that is security-approved for both healthcare and banking sectors, making it a versatile solution for sensitive environments. Additionally, this approach not only streamlines workflows but also enhances overall operational efficiency.

The Apigene MCP Gateway serves as the essential runtime layer that links AI agents to APIs and MCP servers via the Model Context Protocol. By presenting agent tools, context, skills, and instructions as a unified remote MCP endpoint that is fully managed and regulated, it transforms MCP into a fully-fledged native solution rather than a mere experimental tool. Apigene offers a comprehensive agent foundation layer encapsulated within a single MCP Gateway, enabling agents to connect securely with APIs and MCP servers without the need for bespoke glue code or framework-specific adaptations. Teams can effortlessly construct AI agents using conversational interfaces, specifying which APIs and MCP servers the agents can access, outlining their reasoning processes, and dictating their actions—all without writing code. Additionally, it features intelligent tool selection that effectively pairs the appropriate API or MCP tool with each request, while also allowing for multi-platform deployment across numerous environments, including ChatGPT, Claude, Cursor, Gemini, VS Code, internal copilots, enterprise AI systems, and custom applications. This powerful integration streamlines the development process, making it easier for teams to leverage AI in their projects.

Barndoor serves as a robust management layer for data and access, ensuring that artificial intelligence systems interact securely with enterprise data and infrastructure. Acting as a unified control center, it oversees AI agents and applications, empowering organizations to set policies, automatically enforce access rules, and retain comprehensive oversight of AI tool operations within business frameworks. Moving beyond traditional identity-based permissions, Barndoor employs context-aware governance, which allows administrators to dictate the allowed actions of an AI agent by considering variables such as the user in charge of the agent, the system being accessed, the nature of the data, and the task at hand. This system assesses each AI request in real time to apply policies before actions are undertaken, thereby thwarting unsafe or unauthorized operations from affecting internal systems or altering sensitive data. Furthermore, by integrating such a nuanced approach to governance, organizations can enhance both security and compliance, ultimately fostering a more trustworthy AI ecosystem.

TrendAI Vision One™ is a comprehensive AI-powered cybersecurity platform designed to protect enterprises in an increasingly complex threat landscape. Built by Trend Micro, it delivers unified visibility across endpoints, cloud environments, networks, and data systems. The platform leverages advanced AI analytics to identify, prioritize, and respond to security risks based on their potential business impact. It enables organizations to detect threats in real time and automate response workflows for faster mitigation. TrendAI Vision One™ combines capabilities such as extended detection and response (XDR), SIEM, and SOAR into a single integrated solution. It also provides robust protection for AI systems, ensuring secure development, deployment, and governance of AI applications. The platform helps organizations reduce alert fatigue while improving operational efficiency. Its threat intelligence is powered by one of the world’s largest cybersecurity research networks. Businesses can use the platform to proactively manage cyber risk and strengthen resilience. Overall, TrendAI Vision One™ empowers enterprises to innovate securely while staying ahead of modern cyber threats.

Enterprise copilots and low-code/no-code platforms have revolutionized the process of developing robust business AI applications and bots, making it quicker and more accessible than ever. With the advent of generative AI, individuals from various technical backgrounds can now foster innovation, streamline repetitive tasks, and design efficient workflows with ease. Much like the public cloud, while these AI and low-code solutions safeguard the foundational infrastructure, they do not protect the resources or data that are built on top of it. As a multitude of applications, automations, and copilots are being developed, the risks associated with prompt injection, RAG poisoning, and data leaks significantly escalate. In contrast to traditional software development, the use of copilots and low-code platforms often overlooks the crucial phases of testing, security analysis, and performance evaluation. By empowering both professional and citizen developers, organizations can enable the creation of tailored solutions that adhere to security and compliance requirements. We invite you to discuss how your team can effectively harness the power of copilots and low-code development to drive your business forward. This collaboration could lead to innovative solutions that not only meet your needs but also enhance overall operational efficiency.

Nebulock is an advanced threat hunting platform powered by AI, specifically engineered to proactively uncover concealed security threats throughout an organization’s complete technological infrastructure. By perpetually analyzing telemetry data from various sources such as endpoints, identity frameworks, cloud environments, networks, and SaaS applications, it correlates signals across these different layers to detect attacks that conventional tools may overlook. Utilizing agentic AI, Nebulock automates the entire threat hunting process by forming hypotheses, validating them against real-time data, and converting findings into confirmed behavioral detection rules without the need for human intervention. Its fundamental architecture incorporates a contextual "behavior graph" that establishes a baseline of typical activities, allowing it to identify anomalies by comparing events along a unified timeline, which enhances the accuracy of detecting insider threats, credential misuse, and lateral movements. Unlike traditional methods, Nebulock prioritizes behavior-based detection over static indicators, ensuring a more dynamic approach to security. This innovative platform not only improves operational efficiency but also significantly elevates the organization's overall security posture.

Mindgard, the leading cybersecurity platform for AI, specialises in securing AI/ML models, encompassing LLMs and GenAI for both in-house and third-party solutions. Rooted in the academic prowess of Lancaster University and launched in 2022, Mindgard has rapidly become a key player in the field by tackling the complex vulnerabilities associated with AI technologies. Our flagship service, Mindgard AI Security Labs, reflects our dedication to innovation, automating AI security testing and threat assessments to identify and remedy adversarial threats that traditional methods might miss due to their complexity. Our platform is supported by the largest, commercially available AI threat library, enabling organizations to proactively protect their AI assets across their entire lifecycle. Mindgard seamlessly integrates with existing security ecosystem platforms, enabling Security Operations Centers (SOCs) to rapidly onboard AI/ML solutions and manage AI-specific vulnerabilities and hence risk.

NeuralTrust is a leading platform to secure and scale LLM agents and applications. It is the fastest open-source AI Gateway in the market, providing zero-trust security for seamless tool connectivity and zero-trust security. Automated red teaming can detect vulnerabilities and hallucinations. Key Features - TrustGate : The fastest open source AI gateway, enabling enterprise to scale LLMs with zero-trust security and advanced traffic management. - TrustTest : A comprehensive adversarial testing framework that detects vulnerabilities and jailbreaks. It also ensures the security and reliability of LLM. - TrustLens : A real-time AI monitoring and observability tool that provides deep analytics and insights into LLM behaviors.

AccuroAI is an advanced platform focused on enterprise-level AI security, data protection, and governance, created to provide organizations with comprehensive oversight and management of AI tool usage within their environments. This platform consistently identifies and catalogs both approved and unauthorized AI applications, covering various areas including browsers, SaaS solutions, networks, and autonomous agents, while meticulously tracing every interaction back to the specific user, application, and intent. By functioning in real time between users and AI models, it scrutinizes both prompts and responses to identify and mitigate risks such as the exposure of sensitive information, prompt injection threats, and the generation of harmful outputs. Furthermore, it implements dynamic data loss prevention techniques that detect and redact sensitive material, including personally identifiable information, financial details, source code, and health records, ensuring that these do not reach the model while maintaining seamless workflow processes. AccuroAI also consolidates regulatory oversight with a comprehensive policy engine that ensures governance is consistently applied across both human interactions and agent activities. Through these features, organizations can enhance their security posture while effectively managing the complexities of AI deployment.

Axoflow is a security data curation pipeline designed to collect, process, and route security data from various sources to multiple destinations. It is used by security operations centers, managed security service providers, and enterprise security teams to manage large volumes of security data across diverse environments. The platform prepares and optimizes security data for ingestion into systems such as Splunk, Google SecOps, and Microsoft Sentinel. The platform uses an AI-augmented decision tree to classify and normalize security data. It collects data from sources such as syslog, Windows systems, cloud services, Kubernetes environments, and applications through connectors that require no maintenance. Pre-processing operations include parsing, deduplication, normalization, anonymization, and enrichment with geo-IP and threat intelligence data. Integrated storage solutions, AxoLake and AxoStore, provide tiered data lake capabilities and federated search functionality. Processed data is routed to destinations such as SIEMs, data lakes, message queues, and archive storage using smart policy-based routing. Axoflow is built on technology developed by the creators of syslog-ng and operates at large scales in enterprise environments. It offers visibility into data pipelines with detailed metrics on performance and data flow. The platform supports both cloud-native and on-premises deployments and is compatible with technologies such as syslog and OpenTelemetry. It provides observability down to the syslog layer and centralized fleet management across distributed collection points.