Alternatives to TROJAI

c/side: The Client-Side Platform for Cybersecurity, Compliance, and Privacy Monitoring third-party scripts effectively eliminates uncertainty, ensuring that you are always aware of what is being delivered to your users' browsers, while also enhancing script performance by up to 30%. The unchecked presence of these scripts in users' browsers can lead to significant issues when things go awry, resulting in adverse publicity, potential legal actions, and claims for damages stemming from security breaches. Compliance with PCI DSS 4.0.1, particularly sections 6.4.3 and 11.6.1, requires that organizations handling cardholder data implement tamper-detection measures by March 31, 2025, to help prevent attacks by notifying stakeholders of unauthorized modifications to HTTP headers and payment information. c/side stands out as the sole fully autonomous detection solution dedicated to evaluating third-party scripts, moving beyond reliance on merely threat feed intelligence or easily bypassed detections. By leveraging historical data and artificial intelligence, c/side meticulously analyzes the payloads and behaviors of scripts, ensuring a proactive stance against emerging threats. Our continuous monitoring of numerous sites allows us to stay ahead of new attack vectors, as we process all scripts to refine and enhance our detection capabilities. This comprehensive approach not only safeguards your digital environment but also instills greater confidence in the security of third-party integrations.

SOCRadar Extended Threat Intelligence is a holistic platform designed from the ground up to proactively detect and assess cyber threats, providing actionable insights with contextual relevance. Organizations increasingly require enhanced visibility into their publicly accessible assets and the vulnerabilities associated with them. Relying solely on External Attack Surface Management (EASM) solutions is inadequate for mitigating cyber risks; instead, these technologies should form part of a comprehensive enterprise vulnerability management framework. Companies are actively pursuing protection for their digital assets in every potential exposure area. The conventional focus on social media and the dark web no longer suffices, as threat actors continuously expand their methods of attack. Therefore, effective monitoring across diverse environments, including cloud storage and the dark web, is essential for empowering security teams. Additionally, for a thorough approach to Digital Risk Protection, it is crucial to incorporate services such as site takedown and automated remediation. This multifaceted strategy ensures that organizations remain resilient against the evolving landscape of cyber threats.

Aegis provides robust protection for your AI models, effectively preventing issues like model poisoning and safeguarding data integrity, allowing you to confidently implement your AI/ML initiatives in either the cloud or on-premises while maintaining a strong security posture against a constantly changing threat environment. The lack of security in AI/ML tools can widen attack surfaces and significantly increase the risk of security breaches if security teams do not remain vigilant. An inadequate security strategy for AI/ML can lead to severe consequences, including data breaches, operational downtime, loss of profits, damage to reputation, and theft of credentials. Additionally, weak AI/ML frameworks can endanger data science projects, leaving them susceptible to breaches, theft of intellectual property, supply chain vulnerabilities, and manipulation of data. To combat these risks, Aegis employs a comprehensive suite of specialized tools and AI models to scrutinize data within your AI/ML ecosystem as well as information from external sources, ensuring a proactive approach to security in an increasingly complex landscape. This multifaceted strategy not only enhances protection but also supports the overall integrity of your AI-driven operations.

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.

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.

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.

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.

Lakera Guard enables organizations to develop Generative AI applications while mitigating concerns related to prompt injections, data breaches, harmful content, and various risks associated with language models. Backed by cutting-edge AI threat intelligence, Lakera’s expansive database houses tens of millions of attack data points and is augmented by over 100,000 new entries daily. With Lakera Guard, the security of your applications is in a state of constant enhancement. The solution integrates top-tier security intelligence into the core of your language model applications, allowing for the scalable development and deployment of secure AI systems. By monitoring tens of millions of attacks, Lakera Guard effectively identifies and shields you from undesirable actions and potential data losses stemming from prompt injections. Additionally, it provides continuous assessment, tracking, and reporting capabilities, ensuring that your AI systems are managed responsibly and remain secure throughout your organization’s operations. This comprehensive approach not only enhances security but also instills confidence in deploying advanced AI technologies.

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.

ZeroLeaks serves as an AI-driven security platform designed to assist organizations in detecting and addressing vulnerabilities related to exposed system prompts, internal tools, and logical flaws that may lead to prompt injection, extraction, or other forms of data leakage threatening sensitive instructions or intellectual property. The platform features an interactive dashboard that allows users to perform manual scans of system prompts or automate the scanning process through CI/CD integrations, enabling the identification of leaks and injection vectors prior to code deployment. Additionally, it employs an AI-enhanced red-team analysis engine to evaluate prompt areas for logical errors, extraction threats, and potential misuse, providing users with evidence, scoring, and actionable remediation strategies. Aimed at enterprise-level security for products utilizing large language models, ZeroLeaks delivers vulnerability assessments that detail the extent of prompt exposure, highlight prioritized risks, provide proof of issues discovered, and outline access paths along with proposed solutions, such as prompt reconfiguration and tool access restrictions. Ultimately, ZeroLeaks empowers organizations to bolster their security measures and safeguard their intellectual assets effectively.

Prompt Security allows businesses to leverage Generative AI while safeguarding against various risks that could affect their applications, workforce, and clientele. It meticulously evaluates every interaction involving Generative AI—ranging from AI applications utilized by staff to GenAI features integrated into customer-facing services—ensuring the protection of sensitive information, the prevention of harmful outputs, and defense against GenAI-related threats. Furthermore, Prompt Security equips enterprise leaders with comprehensive insights and governance capabilities regarding the AI tools in use throughout their organization, enhancing overall operational transparency and security. This proactive approach not only fosters innovation but also builds trust with customers by prioritizing their safety.

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.

XBOW is an advanced offensive security platform driven by AI that autonomously identifies, confirms, and exploits vulnerabilities in web applications, all without the need for human oversight. It adeptly executes high-level commands based on established benchmarks and analyzes the resulting outputs to tackle a diverse range of security challenges, including CBC padding oracle attacks, IDOR vulnerabilities, remote code execution, blind SQL injections, SSTI bypasses, and cryptographic weaknesses, achieving impressive success rates of up to 75 percent on recognized web security benchmarks. Operating solely on general directives, XBOW seamlessly coordinates tasks such as reconnaissance, exploit development, debugging, and server-side assessments, leveraging publicly available exploits and source code to create tailored proofs-of-concept, validate attack pathways, and produce comprehensive exploit traces along with complete audit trails. Its remarkable capability to adjust to both new and modified benchmarks underscores its exceptional scalability and ongoing learning, which significantly enhances the efficiency of penetration-testing processes. This innovative approach not only streamlines workflows but also empowers security professionals to stay ahead of emerging threats.

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.

With SydeLabs, you can proactively address vulnerabilities and receive immediate defense against threats and misuse while ensuring compliance. The absence of a structured method to recognize and resolve vulnerabilities in AI systems hinders the secure implementation of models. Furthermore, without real-time protective measures, AI applications remain vulnerable to the constantly changing landscape of new threats. The evolving regulations surrounding AI usage create opportunities for non-compliance, which can jeopardize business stability. Thwart every attack, mitigate abuse, and maintain compliance seamlessly. At SydeLabs, we offer an all-encompassing suite of solutions tailored to your AI security and risk management needs. Gain an in-depth insight into the vulnerabilities present in your AI systems through continuous automated red teaming and tailored assessments. Leverage real-time threat scores to take proactive steps against attacks and abuses across various categories, thereby establishing a solid defense for your AI systems while adapting to the latest security challenges. Our commitment to innovation ensures that you are always a step ahead in the ever-evolving world of AI security.

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.

The rise of large, reliable quantum computers threatens the security of existing public-key cryptography, exposing crucial data and systems to potential breaches. In response to this challenge, SandboxAQ has been chosen by NIST's National Cybersecurity Center of Excellence to participate in its Migration to Post-Quantum Cryptography initiative, collaborating with industry partners to guide the government in establishing effective strategies for transitioning from current public-key systems to new post-quantum cryptography algorithms. This initiative simplifies compliance with emerging cryptographic standards and allows for seamless switching between different algorithms without the need for extensive development or upkeep. Furthermore, the Application Analyzer plays a pivotal role by monitoring and documenting all interactions with cryptographic libraries during application runtime, thereby pinpointing vulnerabilities and instances of non-compliance. Such tools are essential in fortifying the security framework as we advance toward a quantum computing era.

Aurascape is a cutting-edge security platform tailored for the AI era, empowering businesses to innovate securely amidst the rapid advancements of artificial intelligence. It offers an all-encompassing view of interactions between AI applications, effectively protecting against potential data breaches and threats driven by AI technologies. Among its standout features are the ability to oversee AI activity across a wide range of applications, safeguarding sensitive information to meet compliance standards, defending against zero-day vulnerabilities, enabling the secure implementation of AI copilots, establishing guardrails for coding assistants, and streamlining AI security workflows through automation. The core mission of Aurascape is to foster a confident adoption of AI tools within organizations while ensuring strong security protocols are in place. As AI applications evolve, their interactions become increasingly dynamic, real-time, and autonomous, necessitating robust protective measures. By preempting emerging threats, safeguarding data with exceptional accuracy, and enhancing team productivity, Aurascape also monitors unauthorized app usage, identifies risky authentication practices, and curtails unsafe data sharing. This comprehensive security approach not only mitigates risks but also empowers organizations to fully leverage the potential of AI technologies.

Large Language Models (LLMs) are trained on extensive datasets that could inadvertently contain your private information, leading to potential risks of exposure and misuse by unethical providers or malicious individuals. To counteract these threats, ZeroTrusted.ai has developed its LLM Firewall, which effectively safeguards against such vulnerabilities. Our advanced sanitization model is capable of identifying sensitive data types, including GDPR, PHI, PII, and PCI information. Additionally, it is continuously updated with compliance data from NIST to ensure that you meet regulatory requirements while automating the compliance process. Beyond this, our platform offers numerous other features such as prompt optimization, minimizing hallucinations, and preventing data injection through our unique LLM ensemble technique, enhancing the overall user experience. However, it's important to note that these advanced features are accessible exclusively through our business plan, ensuring that your organization receives the highest level of protection and functionality.

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.

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.

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.

CrowdStrike's Charlotte AI serves as a state-of-the-art cybersecurity solution powered by artificial intelligence, aimed at improving the detection and response to threats through the utilization of machine learning and behavioral analytics. It perpetually observes network activities, endpoints, and cloud infrastructures to uncover patterns and irregularities that may signify harmful actions or impending cyber threats. By employing sophisticated algorithms, Charlotte AI predicts and identifies complex attacks in real-time, thereby minimizing response durations and enhancing overall threat mitigation. Its capability to sift through extensive data and deliver practical insights empowers security teams to effectively tackle vulnerabilities and thwart incidents before they materialize. Additionally, Charlotte AI is an integral component of CrowdStrike's extensive array of cybersecurity offerings, equipping organizations with advanced automated defense mechanisms to stay ahead of evolving threats while ensuring robust protection against potential risks. This proactive approach not only strengthens organizational security but also fosters a culture of vigilance and preparedness in the face of cyber challenges.

Consistently monitor and remediate vulnerabilities within AI data, models, and application usage using IBM Guardium AI Security, which provides automated and ongoing surveillance for AI implementations. The system identifies security flaws and misconfigurations while managing the security dynamics between users, models, data, and applications. This functionality is integrated within the IBM Guardium Data Security Center, designed to enhance collaboration between security and AI teams through streamlined workflows, a unified overview of data assets, and centralized compliance regulations. Guardium AI Security identifies the specific AI model linked to each deployment, revealing the data, model, and application interactions involved. Additionally, it displays all applications that access the model, allowing users to assess vulnerabilities in the model, its foundational data, and the interacting applications. Each identified vulnerability is given a criticality score, enabling effective prioritization of remediation efforts. Furthermore, users can easily export the vulnerability list for comprehensive reporting, ensuring that all necessary stakeholders are informed and aligned on security efforts. This proactive approach not only strengthens security but also fosters a culture of awareness and responsiveness within the organization.

Alice is an enterprise-grade AI security and trust platform designed to protect applications, agents, and foundation models from adversarial threats. Formerly known as ActiveFence, the company leverages its proprietary Rabbit Hole intelligence engine, built on billions of real-world toxic and abusive data samples, to deliver unmatched safety coverage. Alice protects more than 50% of global online experiences, monitoring over 1 billion daily AI-human interactions across 120+ languages. Its WonderSuite platform provides comprehensive safeguards, including pre-launch stress testing with WonderBuild, dynamic runtime guardrails through WonderFence, and continuous automated red-teaming via WonderCheck. These solutions help organizations defend against prompt injection, jailbreaks, model exploitation, and policy misalignment risks. By aligning defenses with regulatory and compliance requirements, Alice supports responsible AI governance and enterprise risk management. Trusted by leading tech companies and model labs, Alice empowers businesses to deploy GenAI systems securely and scale innovation without fear.

Vercara UltraWAF is a cloud-native web application security service designed to defend against threats aimed at the application layer. This solution safeguards your applications from various risks such as data breaches, defacements, and malicious bot attacks, ensuring a robust defense against web application-layer vulnerabilities. UltraWAF enhances operational efficiency by providing consistently configured security rules that are independent of service providers or hardware constraints, thus protecting applications regardless of their hosting environment. With its flexible security capabilities, UltraWAF addresses major network and application-layer threats like SQL injection, cross-site scripting (XSS), and distributed denial-of-service (DDoS) attacks. Its constant security presence, coupled with the scalability inherent to cloud solutions, guarantees thorough protection against the OWASP top 10 vulnerabilities, along with advanced bot management and vulnerability scanning. This comprehensive approach allows businesses to effectively safeguard their essential applications and those that interact with customers from evolving cyber threats. Moreover, UltraWAF’s proactive measures help maintain customer trust by ensuring a secure online experience.

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.

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.

We assist you in facilitating AI transformation while safeguarding it against cyber threats, privacy concerns, and safety challenges. Our expertise allows you to grasp how cybercriminals might take advantage of your AI applications by examining the specifics of your AI models, data, and operational context. Additionally, we evaluate the resilience of your AI application through scenario-driven attack simulations conducted by a highly skilled and motivated threat actor. Our auditing services ensure the integrity of your AI application through a detailed assessment rooted in a stress testing methodology focused on robustness. Recently, we have developed a novel attack targeting AI-driven facial recognition systems, which can result in an AI system misidentifying you as someone entirely different, thereby demonstrating the evolving landscape of AI vulnerabilities. This highlights the critical need for vigilance and proactive measures in the deployment of AI technologies.

Wardstone functions as a security API for language models, acting as a safeguard between applications and various language model providers by evaluating inputs and outputs for potential threats in four distinct categories during a single request: prompt attacks, content violations, data leaks, and suspicious links. It is adept at identifying jailbreaks, prompt injections, harmful content including hate speech, violence, and self-harm, as well as personally identifiable information like Social Security numbers, credit card details, email addresses, and phone numbers, in addition to detecting dubious URLs. Each response generated provides a detailed risk assessment for each category, achieving this within a swift response time of under 30 milliseconds. Compatible with any LLM provider, it is accessible via a REST API and offers SDKs for multiple programming languages, including TypeScript, Python, Go, Ruby, PHP, Java, and C#. A complimentary tier allows up to 10,000 calls per month without the need for a credit card, and it also features a web-based playground for users to experiment and test functionalities. Users can easily integrate this tool into their existing systems, enhancing the security of their language model interactions.

Acuvity stands out as the most all-encompassing AI security and governance platform tailored for both your workforce and applications. By employing DevSecOps, AI security can be integrated without necessitating code alterations, allowing developers to concentrate on advancing AI innovations. The incorporation of pluggable AI security ensures a thorough coverage, eliminating the reliance on outdated libraries or insufficient protection. Moreover, it helps in optimizing expenses by effectively utilizing GPUs exclusively for LLM models. With Acuvity, you gain complete visibility into all GenAI models, applications, plugins, and services that your teams are actively using and investigating. It provides detailed observability into all GenAI interactions through extensive logging and maintains an audit trail of inputs and outputs. As enterprises increasingly adopt AI, it becomes crucial to implement a tailored security framework capable of addressing novel AI risk vectors while adhering to forthcoming AI regulations. This approach empowers employees to harness AI capabilities with confidence, minimizing the risk of exposing sensitive information. Additionally, the legal department seeks assurance that there are no copyright or regulatory complications associated with AI-generated content usage, further enhancing the framework's integrity. Ultimately, Acuvity fosters a secure environment for innovation while ensuring compliance and safeguarding valuable assets.

ARTEMIS, developed by Repello AI, proactively seeks out vulnerabilities in your AI applications by mimicking the tactics employed by cybercriminals. By conducting thorough tests, ARTEMIS identifies and assists in addressing security threats before they can be leveraged in live environments, drawing on the largest collection of AI-focused threat intelligence available. Key Features: 1. Replicates genuine attack scenarios against your AI systems. 2. Identifies vulnerabilities throughout your AI architecture. 3. Offers practical recommendations for mitigation. 4. Evolves in response to new threats as your AI applications expand. Created by security experts, ARTEMIS is designed to safeguard AI from potential breaches. It is crucial to implement robust security measures early in the development phase and maintain them through the deployment process, ensuring ongoing protection against emerging threats.

Fasoo AI-R DLP (AI-Radar Data Loss Prevention) provides a proactive approach to safeguarding sensitive data from potential leaks when using generative AI services. The solution scans and monitors data input into tools like ChatGPT, identifying and blocking the transfer of confidential information. Through customizable policies, administrators can control what data is accessible, enforce restrictions on uploads, and track activities to ensure compliance. Fasoo AI-R DLP enables businesses to use generative AI safely, accelerating their AI adoption while mitigating the risks of data exposure.

Identify threats sooner, react swiftly, and maintain an edge against cyber attacks. This platform represents the pinnacle of AI security analysts, being the sole comprehensive solution that integrates a unified platform, console, and data repository. Enhance autonomous security measures throughout your organization using cutting-edge, patent-pending artificial intelligence technology. Simplify the investigative process by seamlessly merging widely-used tools and integrating threat intelligence with relevant insights into an intuitive conversational interface. Uncover latent vulnerabilities, delve deeper into investigations, and respond more quickly, all while utilizing natural language. Equip your analysts with the ability to convert natural language inquiries into powerful query translations. Propel your Security Operations with our quick start hunting initiatives, AI-driven analyses, automated summaries, and recommended queries. Facilitate collaborative investigations with easily shareable notebooks. Utilize a framework meticulously designed for the safeguarding of data and privacy. Importantly, Purple AI ensures that customer data remains untouched during training and is constructed with the utmost protective measures. This commitment to security and privacy builds trust and confidence in the system’s reliability.

Verax is a leading platform designed to help enterprises manage the complexities and risks of deploying large language models (LLMs) in production environments. Through its Control Center, Verax offers real-time behavioral monitoring and automatic fixes for issues like hallucinations, biased responses, and data leakage, helping organizations maintain safe and verified AI operations. The Verax Explore module unlocks detailed insights into user behavior and model trends, empowering teams to continuously refine and improve LLM performance. Verax Protect, an upcoming feature, aims to safeguard sensitive data by preventing leaks and enforcing strict compliance with privacy regulations. The platform is tailored to meet the needs of IT leaders, data scientists, and innovation teams seeking to tame unpredictable LLM behavior and reduce manual intervention. Verax also fosters AI transparency and trust with ongoing educational content, including blogs that cover key challenges like hallucinations. Headquartered in Tel Aviv and Texas, Verax is positioned as a pivotal player in enterprise AI safety. Their solution helps businesses confidently leverage LLM technology while minimizing risks in real-world applications.

Your company's AI algorithms serve as a distinctive competitive edge, but they also represent a significant investment. If a successful adversarial attack were to occur, it could undermine that advantage without your awareness. HiddenLayer emerges as the pioneering solution tailored for this new security dimension—your AI. It provides a seamless software solution that ensures ongoing, real-time monitoring of your model's integrity and vulnerabilities, all without requiring access to its inner workings or the data used for training. Unlike most adversarial AI security firms, which rely on costly panels of experts to dissect and reinforce algorithms from within, HiddenLayer offers a more efficient approach. Established by professionals in machine learning and security, the company understands the subtlety and complexity of adversarial ML threats, making it easier for organizations to safeguard their AI assets. With HiddenLayer, businesses can focus on innovation while maintaining confidence in their AI's security.

ThreatMon is an advanced cybersecurity platform driven by artificial intelligence, which merges extensive threat intelligence with innovative technology to proactively detect, assess, and reduce cyber threats. It delivers instantaneous insights tailored to various threat environments, encompassing attack surface intelligence, fraud detection, and surveillance of the dark web. By providing thorough visibility into external IT assets, the platform aids organizations in identifying vulnerabilities and protecting against rising threats, including ransomware and advanced persistent threats (APTs). Furthermore, with customized security approaches and ongoing updates, ThreatMon empowers businesses to remain proactive against the ever-changing landscape of cyber risks, thereby fortifying their overall cybersecurity stance and resilience in the face of new challenges. This comprehensive solution not only enhances security measures but also instills greater confidence in organizations striving to safeguard their digital assets.

Raven is an innovative runtime application security platform that safeguards cloud-native applications by functioning internally during execution instead of depending on external security measures. By providing real-time insights into the actual operation of code, it can comprehend execution flows, libraries, and behaviors at the function level, which aids in identifying and averting malicious activities before they manifest. In contrast to conventional tools like WAF or EDR that observe from an external viewpoint, Raven integrates within the application itself, thus equipping it to thwart exploits, supply chain attacks, and zero-day vulnerabilities even in the absence of known threats or CVEs. It perpetually scrutinizes runtime activities, detects irregular patterns, or misuse of legitimate operations, and promptly intervenes to halt harmful executions. Furthermore, Raven aids security teams in prioritizing their efforts by sifting through countless irrelevant vulnerabilities, allowing them to concentrate solely on those that pose a genuine risk. This proactive approach not only enhances security but also streamlines the overall security management process, ensuring that resources are allocated effectively.

Protector Air prioritizes the safeguarding of individual sessions and their associated transactions, while Protector Web enhances the security of the web server through robust enterprise-level web application security and DDoS mitigation. This solution effectively addresses vulnerabilities in websites and applications, including cross-site scripting (XSS), SQL Injection, Remote File Inclusion (RFI), and the OWASP Top-10 list. By thwarting unauthorized access attempts to web systems, it helps protect sensitive information and prevents website defacement, thereby reducing an organization’s reliance on secure development practices and third-party patches. Serving as an advanced alternative to traditional web application firewalls (WAF), Protector Web tackles significant shortcomings typically found in WAFs through the implementation of active learning, dynamic content serving, and cloud replication techniques. Consequently, it notably lowers the occurrence of false positives and negatives, expedites deployment timelines to mere hours, and simplifies operational management for users. This comprehensive approach not only enhances security but also ensures a more efficient and effective defense against modern cyber threats.

Tailored content scanning solutions guarantee that any sensitive information or proprietary data embedded in a prompt remains secure within your organization. The output generated by language models is thoroughly examined for code across numerous programming languages, and any responses that include such code are blocked from entering your system. These scanners utilize diverse methods to detect and thwart prompts that may seek to bypass established guidelines and organizational protocols regarding language model usage. With in-house specialists overseeing the process, your teams can confidently utilize the insights offered by language models. Avoid allowing concerns about potential risks associated with large language models to impede your organization's pursuit of a competitive edge. Embracing these technologies can ultimately lead to enhanced productivity and innovation within your operations.

Cloaked AI safeguards confidential AI information through encryption while maintaining accessibility. It enables vector embeddings in databases to be securely encrypted, ensuring that only individuals possessing the appropriate key can perform searches on the vectors. This approach effectively thwarts inversion attacks and various other threats targeting retrieval-augmented generation (RAG) systems, facial recognition technologies, and beyond, thereby enhancing overall data protection. Such safeguards are crucial in an era where the integrity of AI applications is constantly under scrutiny.

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.

Heeler serves as an advanced application security platform designed to assist both development and security teams in automating the identification, ranking, and resolution of risks associated with open source and applications by consolidating contextual information from various sources, including code, runtime environments, deployments, dependencies, and business logic into a cohesive actionable framework. By integrating static and dynamic analysis, software composition analysis, threat modeling, and secrets scanning with a sophisticated context engine that illustrates the operational behavior of code in production, Heeler allows for the prioritization of threats in real-time based on their exploitability and potential business repercussions, rather than simply relying on the number of vulnerabilities. This platform not only automatically produces validated remediation recommendations but can also generate merge-ready pull requests to update libraries or resolve identified issues, which significantly reduces the need for manual research and expedites the process of implementing fixes. Furthermore, Heeler delivers comprehensive visibility throughout the software development lifecycle, systematically tracking vulnerabilities from the moment they are discovered until they are resolved, while also ensuring that fixes are effectively monitored across various deployments, thus enhancing the overall security posture of the organization.

Deep Instinct is unique in applying end-to-end deeplearning to cybersecurity. Deep Instinct's approach is preemptive, unlike response-based solutions that wait for an attack to occur before reacting. Deep Instinct's preventative approach ensures customers are protected in no time. Files and vectors are automatically analyzed before execution. This is crucial in a dangerous environment where it is impossible to act quickly. Deep Instinct is designed to eradicate cyber threats from an enterprise. It detects and blocks the most evasive known as well as unknown cyberattacks with unmatched accuracy. Third-party tests are performed regularly and have the highest detection rates. The lightweight solution provides protection for endpoints, networks and servers as well as mobile devices. It can be applied to all OSs and protects against file-based and fileless attacks.

Plurilock AI promptGuard is a patent-pending new security tool that protects companies from data leaks when their employees are using generative AI platforms such as ChatGPT. PromptGuard is different from other solutions that address the problem of generative AI data leakage. It doesn't block AI or individual AI prompts. PromptGuard uses a mature DLP to detect sensitive data and anonymize it prior to sending it to the AI platform. PromptGuard restores original references when the AI platform returns a response. This preserves the workflow of AI and the query flow, allowing users to use it productively, while keeping sensitive information out of the AI platform’s hands. PromptGuard provides a complete audit log of all queries and responses for each user. This allows companies to create an easy-to-understand record of what AI has sent and what AI has returned.