Top ZeusLock Alternatives

Enkrypt AI is an agentic AI security and compliance platform that helps enterprises identify, mitigate, monitor, and govern risks associated with AI models, applications, agents, and supporting infrastructure. The platform is designed to cover AI security threats and compliance requirements across different models and modalities while allowing organizations to continuously evaluate AI systems as they evolve. Its dynamic red teaming capabilities generate use-case-specific attacks that adapt in real time to uncover security, safety, compliance, and brand risks beyond those identified through static testing. Enkrypt AI can test for threats including prompt injection, jailbreaking, data leakage, model inversion, adversarial attacks, drip attacks, unsafe actuation, policy violations, and misuse by end users. It also evaluates AI quality and safety risks such as hallucinations, model drift, bias and discrimination, toxic content, deceptive behavior, misleading outputs, lack of explainability, and brand misalignment. Real-time guardrails detect and stop risky interactions as they occur while adapting to new prompts, behaviors, and emerging threats. Continuous monitoring gives security and compliance teams visibility into AI risks, protection effectiveness, and areas requiring action as models and applications change. Enkrypt AI's compliance functionality converts internal policies and external regulatory requirements into automated guardrails and generates evidence that can support audits and compliance programs. The product portfolio includes Agent Red Teaming, Agent Guardrails, an Agent Policy Engine, AI Data Risk Audit, MCP Scanner, and MCP Gateway for protecting AI agents, their data, and their connections to tools and infrastructure. Enkrypt AI supports use cases including customer-facing AI agents, frontier models, AI compliance and auditing, third-party AI risk, secure AI development, data risk assessment, and MCP security.

Tenable One AI Exposure is a powerful, agentless solution that forms part of the Tenable One exposure management platform, aimed at improving visibility, context, and oversight of generative AI tools such as ChatGPT Enterprise and Microsoft Copilot. This innovative tool enables organizations to monitor user interactions with AI technologies, offering valuable insights into who is utilizing them, the types of data involved, and the workflows being executed, all while pinpointing and mitigating potential risks like misconfigurations, insecure integrations, and the risk of sensitive information leakage, including personally identifiable information (PII), payment card information (PCI), and proprietary business data. In addition, it provides robust protection against various threats such as prompt injections, jailbreak attempts, and breaches of policy by deploying security measures that seamlessly integrate into everyday operations. Designed to be compatible with leading AI platforms and capable of being deployed in mere minutes without any downtime, Tenable AI Exposure plays a critical role in governing AI usage, making it a vital aspect of an organization’s broader cyber risk management approach, which ultimately leads to safer and more compliant AI practices. By embedding these security protocols, organizations are not only able to protect themselves from vulnerabilities but also promote a culture that prioritizes responsible AI usage and fosters trust among stakeholders. This proactive stance ensures that both innovation and security can coexist harmoniously in the fast-evolving landscape of artificial intelligence.

F5 AI Guardrails is a comprehensive AI security and governance solution built to protect AI applications, large language models, autonomous agents, and the sensitive data they access. The platform delivers runtime security controls that help organizations manage the growing risks associated with AI deployments in production environments. It provides protection against adversarial threats such as prompt injection, jailbreak attacks, harmful content generation, unauthorized actions, and model manipulation attempts. Organizations can define and enforce security policies that govern how AI systems interact with users, applications, and enterprise data sources. Real-time inspection and distributed data protection capabilities help prevent sensitive information exposure, policy violations, and compliance breaches across AI ecosystems. The platform supports customizable guardrails that can be tailored to specific operational, regulatory, and business requirements. Automated compliance tools assist organizations in aligning AI operations with frameworks such as GDPR, HIPAA, and the European Union AI Act while maintaining detailed audit trails. Advanced observability features provide continuous visibility into AI interactions, allowing teams to investigate incidents, assess risks, and strengthen governance practices. Dynamic model routing and low-latency security enforcement ensure that protection measures do not negatively impact application performance. The solution is designed to work across a wide range of enterprise and open-source AI models, making it adaptable to evolving technology environments. By combining threat mitigation, data protection, compliance management, and operational visibility, F5 AI Guardrails enables organizations to deploy and scale AI systems with greater confidence and control.

WebOrion Protector Plus represents a cutting-edge firewall solution that harnesses GPU technology to protect generative AI applications with critical security measures. It offers immediate defenses against rising threats, such as prompt injection attacks, unauthorized data exposure, and misleading content generation. Key features include safeguards against prompt injections, the protection of intellectual property and personally identifiable information (PII) from unauthorized access, and content moderation to ensure the accuracy and relevance of responses generated by large language models. Furthermore, the system employs user input rate limiting to mitigate potential security flaws and manage resource use effectively. At the heart of its security framework is ShieldPrompt, a sophisticated defense system that assesses context through LLM analysis of user inputs, conducts canary checks by incorporating deceptive prompts to detect potential data leaks, and thwarts jailbreak attempts through advanced techniques like Byte Pair Encoding (BPE) tokenization paired with adaptive dropout strategies. This holistic methodology not only strengthens the security posture but also significantly boosts the trustworthiness and reliability of generative AI systems, ensuring they can perform optimally in a secure environment. Consequently, organizations can confidently deploy these AI solutions while minimizing risks associated with data breaches and inaccuracies.

CrowdStrike Falcon AI Detection and Response (AIDR) is an all-encompassing security solution designed to protect against the rapidly shifting landscape of AI-related attacks by providing real-time visibility, detection, and response capabilities across diverse AI systems, users, and their interactions. This innovative platform offers a unified perspective on how both human employees and AI agents utilize generative AI, clarifying the relationships among users, prompts, models, agents, and the supporting infrastructure, while maintaining extensive runtime logs for monitoring, compliance, and investigative needs. By continuously tracking AI activities across various endpoints, cloud environments, and applications, organizations can uncover insights into data flows within AI systems and understand the operational boundaries of agents. AIDR excels at recognizing and mitigating AI-specific threats, such as prompt injections, jailbreak attempts, malicious actors, harmful outputs, and unauthorized interactions, leveraging behavioral analysis and integrated threat intelligence. Furthermore, the platform enhances proactive threat management, enabling organizations not only to react to incidents but also to foresee and address potential vulnerabilities within their AI environments. As a result, AIDR empowers organizations to maintain a robust security posture in the face of evolving AI threats while fostering trust in their AI implementations.

iDox.ai Guardrail acts as an immediate protective layer for AI applications, aimed at preventing the exposure of sensitive data during generative AI activities. This cutting-edge solution operates at the endpoint level, intercepting user prompts, uploaded documents, and all forms of AI interactions before any data is sent from the user's device. Guardrail utilizes policy-based strategies to detect and block the unauthorized dissemination of sensitive information, such as personally identifiable information (PII), protected health information (PHI), payment card information (PCI), intellectual property, and various other confidential business details. Unlike traditional data loss prevention (DLP) systems, Guardrail is specifically designed for AI applications, constantly monitoring user interactions with platforms like ChatGPT, Microsoft Copilot, and Claude, while implementing protective measures in real-time to maintain security. Its notable features include continuous oversight of user prompts and file submissions, the capability to recognize sensitive data with AI awareness, immediate anonymization and sanitization of data, protection against risks posed by AI agents—such as unauthorized access incidents (like OpenClaw)—and the enforcement of website whitelisting along with strict policy implementation. Moreover, Guardrail not only bolsters user trust in AI technologies but also aligns with data privacy regulations, ensuring that users can engage with AI tools without concerns about compromising their sensitive information. This proactive approach positions Guardrail as an essential component in the evolving landscape of AI security.

MCP Defender is a cutting-edge open-source desktop application that acts as an AI firewall, meticulously designed to monitor and protect communications related to the Model Context Protocol (MCP). Operating as a secure intermediary between AI applications and MCP servers, it rigorously examines all communications in real-time to identify potential threats. With its automatic scanning and securing of all MCP tool calls, the application harnesses sophisticated LLM capabilities to effectively pinpoint malicious activities. Users have the option to customize the signatures used during the scanning process, allowing for personalized security measures tailored to their unique requirements. MCP Defender stands out in its ability to detect and thwart various AI security threats, including prompt injection, credential theft, arbitrary code execution, and remote command injection. It effortlessly integrates with a wide array of AI applications, such as Cursor, Claude, Visual Studio Code, and Windsurf, with aspirations for broader compatibility in the near future. The application boasts intelligent threat detection and promptly notifies users upon detecting any harmful actions from AI applications, ensuring a formidable defense against ever-evolving threats. Additionally, MCP Defender not only enhances security but also instills confidence in users as they engage with AI technologies, fostering an environment of safety and reliability. Ultimately, this innovative tool empowers users to navigate their AI interactions with enhanced security and peace of mind.

LangProtect is an innovative security and governance solution crafted specifically for AI, providing strong defenses against challenges such as prompt injections, jailbreaks, data breaches, and the creation of unsafe or non-compliant outputs in LLM and Generative AI systems. Designed for advanced GenAI production environments, the platform applies real-time controls at the execution level, carefully analyzing prompts, model responses, and function calls as they happen, which allows teams to block high-risk actions before they can impact users or jeopardize sensitive data. In doing so, LangProtect promptly neutralizes potential threats, thereby safeguarding the integrity of both data and user interactions. Moreover, LangProtect's API-first architecture allows for effortless integration with existing LLM systems while ensuring low latency, and it supports a variety of deployment models, including cloud, hybrid, and on-premise configurations to satisfy the security and data residency needs of organizations. The platform is also adept at protecting modern architectures like RAG pipelines and agentic workflows, offering policy-driven enforcement, ongoing monitoring, and governance that are prepared for audits. This all-encompassing strategy empowers organizations to harness AI technologies confidently while significantly reducing the risks tied to their implementation. Ultimately, LangProtect stands out as a vital resource for businesses aiming to navigate the complexities of AI security effectively.

Constellation Gate AI acts as a supplementary defense layer for AI agents, strategically placed between the agent and the model to scrutinize all requests for possible risks and data breaches. This innovative solution operates as an inline gateway for coding agents and model APIs, safeguarding workflows without requiring extensive code alterations. Users can seamlessly direct their existing tools such as Claude Code, Cursor, OpenClaw, Codex, or OpenCode to engage with Gate, thereby securing defenses against prompt injection, secret exposure, PII redaction, token optimization, and maintaining a trustworthy audit trail. The platform effectively tackles three significant vulnerabilities: prompt injection attacks, unauthorized access to credentials and PII, and illicit tool activations. Instead of relying solely on the model's built-in defenses, Gate proactively intercepts potential attacks before they reach the model, eliminates sensitive data from responses before they are returned, and blocks outputs from compromised tools before agents can utilize them. Gate remains compatible with the standard calls made by agents, forwarding them to the model while thoroughly analyzing each request and response in both directions, thereby providing robust protection against evolving threats. This forward-thinking strategy not only bolsters security but also cultivates user confidence in the reliability and safety of their AI operations, ultimately fostering a more secure environment for innovation.

Plurilock AI's PromptGuard is an innovative security solution designed to safeguard businesses from potential data breaches when employees interact with generative AI tools like ChatGPT. Unlike other offerings that simply block AI access or specific prompts, PromptGuard employs an advanced Data Loss Prevention (DLP) system to identify sensitive information and anonymize it before it reaches the AI platform, ensuring confidentiality. Upon receiving a response from the AI, PromptGuard reinstates the original data, maintaining the integrity of the workflow and enabling users to leverage AI efficiently while protecting critical information. Additionally, PromptGuard generates a comprehensive audit log that tracks all user queries and AI responses, empowering organizations to maintain a clear and accessible record of interactions with the AI. This feature not only enhances accountability but also fosters trust in the use of generative AI technologies within the workplace.

HOL Guard serves as a protective layer for AI agents, functioning primarily on a local basis to oversee the behavior of AI assistants and proactively avert potentially dangerous actions. Acting as a buffer between the AI agent and the computer, it evaluates tool usage and access to local resources, looking out for threats such as the leakage of secrets and credentials, harmful commands, actions influenced by prompt injections, and the utilization of tampered or suspicious packages, as well as unsafe configurations and unvalidated plugins, skills, hooks, and settings. Identified threats can be swiftly blocked, while uncertain activities are paused to obtain user approval, thus ensuring that users retain control over the process. The entire operation is confined to the developer's local environment, negating the need for an internet connection and ensuring that no files, prompts, or sensitive data are uploaded to external servers. Typically, local assessments are completed in under 50 milliseconds, and implementing Guard does not require any alterations to existing code or workflows. It is versatile and works seamlessly with several coding agents, including Claude Code, Cursor, Codex, Gemini CLI, OpenCode, Hermes, and OpenClaw, offering tailored integrations that scrutinize actions before they are carried out. Furthermore, this bolsters the overall safety and dependability of AI interactions, leading to enhanced confidence in automated systems. Overall, HOL Guard significantly contributes to a secure operational environment for AI assistants, making it an essential tool for developers focused on safeguarding their work.

Alice is a leading AI safety and adversarial intelligence platform built to secure the rapidly evolving landscape of generative AI, agents, and emerging technologies. Rebranded from ActiveFence, Alice combines a decade of real-world adversarial research with the industry’s most comprehensive toxic and abuse dataset to protect platforms, applications, and foundation models at scale. Its proprietary Rabbit Hole intelligence engine continuously ingests and analyzes billions of manipulative, harmful, and abusive data samples, enabling proactive threat detection before incidents become public crises. Today, Alice safeguards more than 3 billion users worldwide and monitors over 1 billion daily AI-human interactions across 120+ languages. The company’s WonderSuite platform delivers end-to-end AI security, including WonderBuild for pre-deployment stress testing, WonderFence for dynamic runtime guardrails, and WonderCheck for ongoing automated red-teaming. These capabilities address emerging risks such as prompt injection, jailbreaks, application-level exploits, compliance failures, and unintended GenAI behavior. Alice allows organizations to customize policy alignment based on regulatory obligations and risk tolerance, ensuring trusted interactions across text, image, and multimodal systems. By strengthening governance frameworks and reducing reputational exposure, Alice helps enterprises and frontier model labs deploy AI responsibly and confidently. Trusted by leading global technology companies, Alice serves as a foundational layer of safety for more than half of the world’s online experiences.

Silmaril represents a groundbreaking defense strategy against prompt injection, designed to autonomously repair itself in order to protect AI systems from complex, layered threats that traditional defenses often fail to address. Unlike standard techniques that simply filter out harmful inputs, it envelops inference requests, rigorously analyzing whether the series of actions could lead to adverse outcomes. Utilizing a multihead classifier, Silmaril assesses user motivations, application contexts, and execution states in parallel, enabling it to detect indirect injections, prolonged attack patterns, context alterations, and tool misuse before they can inflict damage. To bolster its protective features, Silmaril employs autonomous threat-hunting agents that navigate through systems, uncover vulnerabilities, and generate synthetic training data from real attack scenarios. This intelligence not only aids in automatic model retraining, allowing for the implementation of upgraded defenses in under an hour, but also ensures the distribution of anonymized protective strategies across all operational instances. Furthermore, this forward-thinking methodology guarantees that the system can maintain its resilience against new threats, continuously adapting to the shifting challenges in the cybersecurity landscape. By consistently evolving, Silmaril ultimately fortifies the security framework surrounding AI technology.

EarlyCore is a specialized security platform crafted specifically for AI agents, enhancing the efficiency of pre-production attack testing, ongoing surveillance, and compliance documentation throughout the agents' operational lifespan. The platform rigorously assesses agents against a wide range of potential threats, including prompt injection, jailbreaking, data exfiltration, tool misuse, and vulnerabilities within the supply chain. After agents are deployed, EarlyCore provides continuous oversight of their actions, establishes baseline behavioral norms, and detects anomalies in real time, promptly notifying users through Slack, email, or webhooks. Furthermore, it automates the creation of compliance documentation that adheres to various standards such as ISO 42001, NIST AI RMF, EU AI Act, SOC 2, and GDPR, ensuring that organizations are always prepared for audits. With an impressive deployment time of merely 15 minutes and without requiring any code modifications, it integrates effortlessly with services like AWS Bedrock, Gemini Enterprise Agent Platform, and LangChain, among others. Additionally, it supports multi-tenant environments, making it particularly suitable for agencies and Managed Security Service Providers (MSSPs). Tailored for security teams, agencies, and MSSPs, EarlyCore equips organizations with the tools necessary to effectively secure AI agents at scale while upholding rigorous compliance and security standards, ultimately fostering a safer AI ecosystem.

Tumeryk Inc. specializes in state-of-the-art security solutions tailored for generative AI, offering features like the AI Trust Score that supports real-time monitoring, risk evaluation, and compliance with regulations. Our cutting-edge platform empowers businesses to protect their AI infrastructures, guaranteeing that implementations are not only dependable and credible but also in line with relevant policies. The AI Trust Score measures the potential hazards associated with generative AI technologies, which is crucial for organizations seeking to adhere to significant regulations such as the EU AI Act, ISO 42001, and NIST RMF 600.1. This score evaluates the reliability of AI-generated responses by examining various risks, including bias, vulnerability to jailbreak attacks, irrelevance, harmful content, risks of disclosing Personally Identifiable Information (PII), and occurrences of hallucination. Furthermore, it can be easily integrated into current business processes, allowing companies to make well-informed decisions about accepting, flagging, or rejecting AI-generated outputs, which ultimately minimizes the associated risks of these technologies. By adopting this score, organizations can create a more secure environment for AI applications, which in turn enhances public confidence in automated systems and promotes responsible usage of AI technology. This commitment to security and compliance positions Tumeryk Inc. as a leader in the intersection of artificial intelligence and safety.

Mindgard is an automated AI red teaming platform for security and engineering teams accountable for AI in development and production. It continuously tests AI models, agents, and applications the way real attackers do, finds the vulnerabilities most likely to cause a breach, validates whether guardrails hold, and delivers evidence and remediation steps to close each gap. Coverage includes prompt injection, jailbreaks, data extraction, poisoning, and agentic tool abuse, mapped to OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, and the EU AI Act. Assessments take hours rather than weeks. SOC 2 Type 2 compliant.

Wardstone serves as a protective security API designed for language models, functioning as a barrier between applications and different language model suppliers by assessing both inputs and outputs for possible threats across four specific categories within a single request: prompt attacks, content violations, data leaks, and suspicious links. It excels at detecting jailbreaks and prompt injections, as well as harmful content that includes hate speech, violence, and self-harm, while also identifying personally identifiable information such as Social Security numbers, credit card information, email addresses, and phone numbers, in addition to spotting questionable URLs. Each response it generates comes with a comprehensive risk evaluation for every category, all accomplished in a rapid response time of less than 30 milliseconds. Compatible with any language model provider, it is available through a REST API and supports SDKs in a variety of programming languages including TypeScript, Python, Go, Ruby, PHP, Java, and C#. There is a free tier that allows for up to 10,000 calls per month without requiring a credit card, and it also includes a web-based playground for users to try out and test its functionalities. This tool can be seamlessly integrated into existing systems, significantly improving the security measures of language model interactions, thereby ensuring a safer environment for users and applications alike.

Palo Alto Networks Cortex Agentic Endpoint Security (AES) is an AI-native endpoint security platform developed to protect organizations from threats introduced by autonomous AI agents, developer tools, and dynamically executed software. The solution extends traditional endpoint protection by providing visibility into non-binary software components and AI systems operating with access to enterprise devices and resources. Its discovery capabilities identify AI coding agents, local language models, browser extensions, IDE plugins, Model Context Protocol servers, and open-source software packages. The platform detects unauthorized or unmanaged AI applications and maintains an inventory of software components that may create security exposures. Its AI Context Graph analyzes relationships between agents, tools, permissions, software dependencies, and sensitive resources to provide contextual risk assessments. Continuous risk evaluation helps security teams identify vulnerable packages, excessive permissions, malicious extensions, and potential software supply chain threats. Governance capabilities include configurable security policies, automated guardrails, application controls, and removal of insecure software components. Runtime protection monitors agent actions and can intercept unauthorized tool execution, malicious downloads, and potentially destructive operations before they reach the host system. Integration with Prisma AIRS provides additional protection against prompt injection, unsafe AI interactions, malicious URLs, and potential data exfiltration. Cortex AES can operate as a standalone solution, integrate directly with Cortex XDR, or extend protection alongside compatible third-party endpoint detection and response platforms.

Large Language Models (LLMs) are developed using vast collections of data, which may unintentionally include personal information, posing risks of unauthorized access and exploitation by unethical entities. To mitigate these challenges, ZeroTrusted.ai has introduced its LLM Firewall, designed to shield against these vulnerabilities effectively. This sophisticated sanitization model can recognize various sensitive data categories, such as GDPR, PHI, PII, and PCI information. Furthermore, it is regularly updated with compliance data from NIST to guarantee adherence to regulations while streamlining the compliance workflow. In addition to these features, our platform provides a range of tools for prompt optimization, reducing hallucinations, and preventing data injection via our innovative LLM ensemble technique, all aimed at improving user interaction. It is essential to highlight that these robust functionalities are only available through our business plan, ensuring your organization benefits from optimal protection and enhanced capabilities. Ultimately, ZeroTrusted.ai's commitment to security and compliance empowers users to navigate the complexities of data management with confidence.

Prompt Security enables organizations to harness the potential of Generative AI while minimizing various risks that could impact their applications, employees, and customers. It thoroughly analyzes each interaction involving Generative AI—from AI tools employed by staff to GenAI functionalities embedded in customer services—ensuring the safeguarding of confidential data, the avoidance of detrimental outputs, and protection against threats associated with GenAI. Moreover, Prompt Security provides business leaders with extensive insights and governance tools concerning the AI technologies deployed across their enterprise, thereby improving operational visibility and security measures. This forward-thinking strategy not only encourages innovative solutions but also strengthens customer trust by placing their safety at the forefront of AI implementation. In this way, organizations can confidently explore new frontiers in technology while maintaining a commitment to responsible and secure practices.

NativeMind is an entirely open-source AI assistant that runs directly in your browser via Ollama integration, ensuring complete privacy by not transmitting any information to external servers. All operations, such as model inference and prompt management, occur locally, thereby alleviating worries regarding syncing, logging, or potential data breaches. Users can easily navigate between a variety of robust open models, including DeepSeek, Qwen, Llama, Gemma, and Mistral, without needing additional setups, while leveraging native browser functionalities to optimize their tasks. Furthermore, NativeMind offers effective webpage summarization, supports continuous, context-aware dialogues across multiple tabs, facilitates local web searches that can respond to inquiries directly from the webpage, and provides translations that preserve the original format. Built with a focus on both performance and security, this extension is fully auditable and community-supported, ensuring that it meets enterprise standards for practical uses without the dangers of vendor lock-in or hidden telemetry. In addition, its intuitive interface and smooth integration make it a desirable option for anyone in search of a dependable AI assistant that emphasizes user privacy. This way, users can confidently engage with advanced AI capabilities while maintaining control over their personal information.

middleBrick is an advanced, frictionless security scanner tailored specifically for APIs and AI models, designed with the requirements of high-performance engineering teams in mind. In contrast to traditional scanners that often require complex agents or user credentials, middleBrick can conduct a comprehensive security assessment in under 60 seconds by simply analyzing an endpoint URL. This robust scanner covers 14 critical security categories, which include the entire OWASP API Top 10 (addressing issues such as BOLA/IDOR, BFLA, Mass Assignment, and SSRF); AI/LLM Security, which incorporates 18 adversarial tests aimed at uncovering prompt injection, jailbreaks, and data leaks; and Web3 & DeFi, offering targeted scans for JSON-RPC nodes across platforms like Ethereum, Solana, and Cosmos, while also verifying the reliability of price oracles. Developed to integrate effortlessly into modern workflows, middleBrick is compatible with a GitHub Action, a command-line interface (CLI), and an MCP server that works with tools like Claude and Cursor. This innovative solution not only presents prioritized security insights but also offers practical remediation recommendations, enabling developers to launch secure code swiftly and effectively. Envision middleBrick as the ever-watchful "smoke alarm" for your API environment, continuously observing and alerting you only when significant threats emerge. Its rapid and reliable performance ensures it is an essential tool for contemporary development teams striving for security excellence while maintaining efficiency.

Proofpoint AI Security is a comprehensive solution designed to support organizations in overseeing, monitoring, and protecting the implementation of AI technologies, such as large language models and autonomous agents. This platform provides visibility into both sanctioned and unsanctioned AI activities, enabling security teams to detect unauthorized AI tools, monitor prompts and responses, and evaluate AI interactions with confidential data in real-time. By leveraging intent-based detection and behavioral analysis, it efficiently identifies anomalies, prompt injection attempts, and potentially harmful interactions, while also enforcing operational policies to prevent data breaches and misuse. Additionally, it reconstructs detailed AI transactions from the user's initial query to the subsequent actions and outcomes generated by the agents, ensuring that organizations retain full traceability and are ready for audits. Its functionalities encompass endpoints, web browsers, and AI agent links, promoting stringent access governance that ensures AI systems only utilize and share necessary information. This comprehensive control not only strengthens the enterprise's security posture but also fosters a proactive approach as organizations adapt to the evolving landscape of AI system integration, creating a safer digital environment overall.

Straiker is a cutting-edge security solution meticulously crafted to protect enterprise AI applications and autonomous agents, specifically targeting the new risks introduced by "agentic AI" systems that interact with a multitude of tools, APIs, and sensitive data. By providing extensive visibility and management across the complete AI stack, it scrutinizes behavioral signals from models, prompts, tools, identities, and infrastructure, enabling swift identification and mitigation of AI-specific risks such as prompt injection, privilege escalation, data exfiltration, and tool misuse. The platform seamlessly incorporates continuous discovery, adversarial testing, and runtime safeguarding through vital components like Discover AI, Ascend AI, and Defend AI, which collaborate to recognize all active agents, simulate possible attacks to uncover vulnerabilities, and enforce real-time protective measures during operation. Its complex, layered architecture captures deep contextual signals from user interactions, network behavior, and agent workflows, thereby ensuring a formidable defense against constantly evolving threats. As advancements in AI technologies progress at an unprecedented rate, the demand for such specialized security measures will only grow, making them essential for enterprises striving to thrive in this intricate environment. Ultimately, the proactive approach of platforms like Straiker is crucial in maintaining the integrity and safety of AI-driven operations.

Operant AI provides extensive protection across all tiers of modern applications, ranging from infrastructure to APIs. Its easy-to-implement solution can be set up in just minutes, guaranteeing full security visibility and runtime controls that effectively counter a wide spectrum of cyber threats, including data exfiltration, data poisoning, zero-day vulnerabilities, lateral movement, cryptomining, prompt injection, and more. This level of security is delivered without the need for instrumentation, ensuring there is no drift and that Development, Security, and Operations teams experience minimal disruption. Additionally, Operant enhances the defense mechanisms for cloud-native applications by offering in-line runtime protection for all data being utilized during every interaction, from infrastructure to APIs. This solution demands zero instrumentation, requires no changes to application code, and does not necessitate extra integrations, thereby significantly simplifying the overall security process while maintaining robust protection. Ultimately, the combination of these features positions Operant AI as a leader in the realm of application security.

The emergence of enterprise copilots and low-code/no-code platforms has transformed the landscape of creating powerful business AI applications and bots, accelerating the development process and making it more user-friendly. Generative AI has opened doors for individuals across varying technical expertise to drive innovation, optimize repetitive tasks, and craft efficient workflows effortlessly. However, similar to the public cloud, these AI and low-code frameworks provide a safety net for the underlying infrastructure but do not extend that protection to the data and resources built upon it. As an increasing number of applications, automations, and copilots are launched, the potential risks from prompt injection, RAG poisoning, and data breaches become more pronounced. Unlike conventional software development, the integration of copilots and low-code platforms frequently neglects essential stages such as thorough testing, security assessments, and performance checks. By equipping both seasoned and novice developers, organizations can create customized solutions that remain compliant with security protocols. We encourage you to explore how your team can leverage the capabilities of copilots and low-code development to propel your business toward greater success. This partnership has the potential to yield innovative outcomes that not only fulfill your requirements but also significantly boost overall operational efficacy, positioning your organization for future growth.

ZeroLeaks is an advanced security platform powered by AI, tailored to help organizations identify and rectify vulnerabilities associated with exposed system prompts, internal tools, and logical errors that could facilitate prompt injection, data extraction, or other data leakage risks that endanger sensitive instructions and intellectual property. This platform includes an engaging dashboard that enables users to manually scan system prompts or automate the scanning process via CI/CD integrations, which helps in detecting leaks and injection vectors before code is deployed. Furthermore, it integrates an AI-driven red-team analysis engine that scrutinizes prompt areas for logical inconsistencies, extraction risks, and possible misuse, offering users evidence, scoring metrics, and practical remediation plans. Designed specifically for enterprise-level security concerning products that utilize large language models, ZeroLeaks provides comprehensive vulnerability assessments that detail the severity of prompt exposure, underscore critical risks, furnish proof of identified issues, and delineate access routes along with recommended solutions, such as reconfiguring prompts and restricting tool access. By utilizing ZeroLeaks, organizations can significantly enhance their security protocols and effectively protect their valuable intellectual assets from potential threats. Importantly, the platform not only aids in risk management but also fosters a culture of security awareness within the organization.

Uncover the definitive answer for recognizing, monitoring, and safeguarding sensitive data on a grand scale. This all-encompassing data protection platform is meticulously crafted to quickly address risks, detect anomalies in activity, and maintain compliance, all while ensuring your operations run smoothly. By merging a powerful platform with a committed team and a strategic framework, it provides you with a significant advantage in the marketplace. The platform incorporates classification, access governance, and behavioral analytics to effectively protect your information, counteract threats, and streamline compliance requirements. Our proven approach is informed by numerous successful implementations that assist you in overseeing, securing, and managing your data with ease. A dedicated group of security experts constantly refines advanced threat models, updates policies, and aids in incident response, allowing you to focus on your primary goals while they navigate the intricacies of data security. This joint effort not only strengthens your overall security stance but also nurtures an environment of proactive risk management, ultimately leading to enhanced organizational resilience. Additionally, as the landscape of data threats evolves, our platform adapts to ensure continuous protection and peace of mind.

Lasso is a comprehensive AI security platform created to help enterprises manage, govern, and secure AI applications and autonomous agents throughout their operational lifecycle. As organizations increasingly deploy generative AI and agentic technologies, the platform provides centralized oversight and protection for rapidly growing AI ecosystems. Lasso begins with AI discovery and inventory capabilities that identify AI agents, applications, models, prompts, tools, and security controls across the enterprise. Its AI Bill of Materials (AI-BOM) functionality helps organizations maintain a detailed understanding of their AI assets and dependencies. Automated AI security posture management capabilities assess configurations, identify weaknesses, and support ongoing governance efforts. The platform’s red teaming engine continuously evaluates AI systems against thousands of attack techniques and adversarial scenarios to uncover vulnerabilities before they impact production environments. Runtime enforcement features monitor AI interactions in real time, helping organizations enforce policies and prevent unsafe or unauthorized behavior. Intent-based security analysis enables Lasso to evaluate the purpose and context of AI actions rather than relying exclusively on static detection methods. AI detection and response capabilities provide security teams with actionable insights, investigation tools, and threat monitoring across AI environments. Designed for enterprise deployment, the platform emphasizes scalability, accuracy, cost efficiency, and rapid response to evolving AI risks. By integrating discovery, governance, testing, monitoring, and protection into a unified platform, Lasso helps organizations accelerate AI adoption while maintaining security, compliance, and operational confidence.

Snapper functions as an all-encompassing security framework designed specifically for AI agents, focusing on the governance and safeguarding of organizations that deploy AI across a multitude of applications, networks, and systems. It enforces runtime regulations by meticulously examining each action performed by an agent, including interactions with tools, API requests, and data access demands, before they are executed, employing a sophisticated, multi-layered, policy-driven rule engine. Furthermore, Snapper offers a comprehensive overview of AI activities by scrutinizing network traffic, browser activity, DNS queries, and active processes to detect unauthorized tools and concealed AI applications. In addition, it takes proactive steps to intercept outgoing requests to large language models through SDK wrappers and a network proxy, enabling real-time assessment, redaction, and documentation of sensitive data. To bolster its protective capabilities, Snapper incorporates advanced threat detection systems capable of identifying prompt injection strategies, exploit chains, abnormal behaviors, and intricate attack patterns, using behavioral baselines, kill chain analysis, and an integrated trust scoring framework for enhanced security. This combination of features makes Snapper an invaluable resource for organizations striving to manage the inherent risks linked to AI implementation while ensuring the integrity of their operations. Ultimately, the platform not only mitigates potential threats but also empowers organizations to confidently leverage AI technology.