Alternatives to Cloaked AI

Adaptive Security is OpenAI’s investment for AI cyber threats. The company was founded in 2024 by serial entrepreneurs Brian Long and Andrew Jones. Adaptive has raised $50M+ from investors like OpenAI, a16z and executives at Google Cloud, Fidelity, Plaid, Shopify, and other leading companies. Adaptive protects customers from AI-powered cyber threats like deepfakes, vishing, smishing, and email spear phishing with its next-generation security awareness training and AI phishing simulation platform. With Adaptive, security teams can prepare employees for advanced threats with incredible, highly customized training content that is personalized for employee role and access levels, features open-source intelligence about their company, and includes amazing deepfakes of their own executives. Customers can measure the success of their training program over time with AI-powered phishing simulations. Hyper-realistic deepfake, voice, SMS, and email phishing tests assess risk levels across all threat vectors. Adaptive simulations are powered by an AI open-source intelligence engine that gives clients visibility into how their company's digital footprint can be leveraged by cybercriminals. Today, Adaptive’s customers include leading global organizations like Figma, The Dallas Mavericks, BMC Software, and Stone Point Capital. The company has a world class NPS score of 94, among the highest in cybersecurity.

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.

Searching and analyzing structured data is easy; however, over 80% of generated data is unstructured, requiring a different approach. Machine learning converts unstructured data into high-dimensional vectors of numerical values, which makes it possible to find patterns or relationships within that data type. Unfortunately, traditional databases were never meant to store vectors or embeddings and can not meet unstructured data's scalability and performance requirements. Zilliz Cloud is a cloud-native vector database that stores, indexes, and searches for billions of embedding vectors to power enterprise-grade similarity search, recommender systems, anomaly detection, and more. Zilliz Cloud, built on the popular open-source vector database Milvus, allows for easy integration with vectorizers from OpenAI, Cohere, HuggingFace, and other popular models. Purpose-built to solve the challenge of managing billions of embeddings, Zilliz Cloud makes it easy to build applications for scale.

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

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

Qdrant serves as a sophisticated vector similarity engine and database, functioning as an API service that enables the search for the closest high-dimensional vectors. By utilizing Qdrant, users can transform embeddings or neural network encoders into comprehensive applications designed for matching, searching, recommending, and far more. It also offers an OpenAPI v3 specification, which facilitates the generation of client libraries in virtually any programming language, along with pre-built clients for Python and other languages that come with enhanced features. One of its standout features is a distinct custom adaptation of the HNSW algorithm used for Approximate Nearest Neighbor Search, which allows for lightning-fast searches while enabling the application of search filters without diminishing the quality of the results. Furthermore, Qdrant supports additional payload data tied to vectors, enabling not only the storage of this payload but also the ability to filter search outcomes based on the values contained within that payload. This capability enhances the overall versatility of search operations, making it an invaluable tool for developers and data scientists alike.

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.

DeepArmor uses patented algorithms and model-building tools that can predict and prevent attacks across all attack vectors, including file-based, fileless and in-memory. DeepArmor intercepts and stops attacks before they can be executed, eliminating the need to perform post-infection behavioral analysis and ineffective system rollbacks.

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.

SAGE is an advanced cyber defense platform powered by AI, specifically designed to assist Chief Information Security Officers (CISOs) in creating and maintaining a robust cyber defense strategy. By continuously updating the defense plan with reports and assessments from various sources, it ensures the strategy remains agile and pertinent. Its AI capabilities facilitate the connection and analysis of various elements within the defense framework. SAGE takes into account the organization's specific needs, such as business impact analysis, risk tolerance, and overall cyber posture, while also evaluating potential attack vectors through HolistiCyber’s innovative perspective, which mimics an attacker’s view of the attack surface. The platform features a comprehensive context map that outlines critical factors like risks, vulnerabilities, assets, and cyber threats, along with their implications for the business. Additionally, SAGE simplifies communication for management by converting cyber risks into understandable business risks and incorporates “what-if” scenarios to effectively allocate cybersecurity budgets, making it an essential tool for organizations aiming to enhance their cyber defense capabilities. Moreover, its user-friendly interface allows for seamless integration into existing workflows, further bolstering the operational efficiency of cyber defense initiatives.

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.

Compile embeddings from past attacks in a vector database to identify and avert similar threats down the line. Employ a specialized model to scrutinize incoming prompts for potential attack patterns. Incorporate canary tokens within prompts to monitor for any data leaks, enabling the system to catalog embeddings for incoming prompts in the vector database and thwart future attacks. Additionally, preemptively screen for harmful inputs before they reach the model, ensuring a more secure analysis process. This multi-layered approach enhances the overall defense mechanism against potential security breaches.

Amazon S3 Vectors is the pioneering cloud object storage solution that inherently accommodates the storage and querying of vector embeddings at a large scale, providing a specialized and cost-efficient storage option for applications such as semantic search, AI-driven agents, retrieval-augmented generation, and similarity searches. It features a novel “vector bucket” category in S3, enabling users to classify vectors into “vector indexes,” store high-dimensional embeddings that represent various forms of unstructured data such as text, images, and audio, and perform similarity queries through exclusive APIs, all without the need for infrastructure provisioning. In addition, each vector can include metadata, such as tags, timestamps, and categories, facilitating attribute-based filtered queries. Notably, S3 Vectors boasts impressive scalability; it is now widely accessible and can accommodate up to 2 billion vectors per index and as many as 10,000 vector indexes within a single bucket, while ensuring elastic and durable storage with the option of server-side encryption, either through SSE-S3 or optionally using KMS. This innovative approach not only simplifies managing large datasets but also enhances the efficiency and effectiveness of data retrieval processes for developers and businesses alike.

Examine more than 350 facial vectors from a suspect's image and implement a responsible, policy-driven method for facial recognition that yields quick leads by matching to a meticulously curated booking image gallery. Accelerate the identification of persons of interest through advanced facial cataloging and alert systems. Leverage license plate information to uncover valuable leads that can effectively resolve cases. Enhance crime-solving capabilities by extracting actionable insights from your data. The process of gathering public assistance for identifying wanted suspects can be quite lengthy. Vigilant FaceSearch evaluates over 350 distinct facial vectors to swiftly generate leads from a booking image database that is not only sourced from your department but also includes contributions from partner agencies and our proprietary collection, ensuring a responsible approach to facial recognition identification. In the realm of facial recognition, accuracy is crucial for successful outcomes. Furthermore, this innovative system allows law enforcement to work more efficiently, ultimately leading to safer communities.

Oracle AI Vector Search is an innovative feature integrated into Oracle Database, specifically tailored for AI applications, which enables the querying of data based on its semantic meaning rather than relying solely on conventional keyword searches. This functionality empowers organizations to conduct similarity searches across both structured and unstructured datasets, allowing for retrieval of results that prioritize contextual relevance over precise matches. Employing vector embeddings to represent various forms of data—including text, images, and documents—it utilizes advanced vector indexing and distance metrics to quickly locate similar items. Moreover, it introduces a unique VECTOR data type along with SQL operators and syntax that enable developers to merge semantic searches with relational queries within a single database framework. As a result, this integration streamlines the data management process by negating the necessity for separate vector databases, ultimately minimizing data fragmentation and fostering a cohesive environment for both AI and operational data. The enhanced capability not only simplifies the architecture but also enhances the overall efficiency of data retrieval and analysis in complex AI workloads.

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.

Vectorize is a specialized platform that converts unstructured data into efficiently optimized vector search indexes, enhancing retrieval-augmented generation workflows. Users can import documents or establish connections with external knowledge management systems, enabling the platform to extract natural language that is compatible with large language models. By evaluating various chunking and embedding strategies simultaneously, Vectorize provides tailored recommendations while also allowing users the flexibility to select their preferred methods. After a vector configuration is chosen, the platform implements it into a real-time pipeline that adapts to any changes in data, ensuring that search results remain precise and relevant. Vectorize features integrations with a wide range of knowledge repositories, collaboration tools, and customer relationship management systems, facilitating the smooth incorporation of data into generative AI frameworks. Moreover, it also aids in the creation and maintenance of vector indexes within chosen vector databases, further enhancing its utility for users. This comprehensive approach positions Vectorize as a valuable tool for organizations looking to leverage their data effectively for advanced AI applications.

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.

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.

Even the most advanced AI systems carry concealed risks that can jeopardize operations. It is crucial to proactively recognize and mitigate these challenges to facilitate seamless AI integration and adherence to regulations. AI technologies can be susceptible to increasingly sophisticated forms of attack. By staying proactive, you can safeguard your models and applications against threats like data poisoning, prompt injection, and other novel vulnerabilities. Utilize state-of-the-art public AI solutions with assurance. Our services are designed to promote responsible practices and prevent data breaches, allowing you to concentrate on driving innovation without concern. The TROJAI security platform empowers organizations to meet standards such as the OWASP AI framework and comply with privacy laws by rigorously testing models before they go live and securing applications against risks such as sensitive information loss during operation. By prioritizing these measures, you can ensure a more resilient AI deployment strategy.

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.

A vector database designed for scalable similarity searches. Open-source, highly scalable and lightning fast. Massive embedding vectors created by deep neural networks or other machine learning (ML), can be stored, indexed, and managed. Milvus vector database makes it easy to create large-scale similarity search services in under a minute. For a variety languages, there are simple and intuitive SDKs. Milvus is highly efficient on hardware and offers advanced indexing algorithms that provide a 10x speed boost in retrieval speed. Milvus vector database is used in a variety a use cases by more than a thousand enterprises. Milvus is extremely resilient and reliable due to its isolation of individual components. Milvus' distributed and high-throughput nature makes it an ideal choice for large-scale vector data. Milvus vector database uses a systemic approach for cloud-nativity that separates compute and storage.

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.

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.

Weaviate serves as an open-source vector database that empowers users to effectively store data objects and vector embeddings derived from preferred ML models, effortlessly scaling to accommodate billions of such objects. Users can either import their own vectors or utilize the available vectorization modules, enabling them to index vast amounts of data for efficient searching. By integrating various search methods, including both keyword-based and vector-based approaches, Weaviate offers cutting-edge search experiences. Enhancing search outcomes can be achieved by integrating LLM models like GPT-3, which contribute to the development of next-generation search functionalities. Beyond its search capabilities, Weaviate's advanced vector database supports a diverse array of innovative applications. Users can conduct rapid pure vector similarity searches over both raw vectors and data objects, even when applying filters. The flexibility to merge keyword-based search with vector techniques ensures top-tier results while leveraging any generative model in conjunction with their data allows users to perform complex tasks, such as conducting Q&A sessions over the dataset, further expanding the potential of the platform. In essence, Weaviate not only enhances search capabilities but also inspires creativity in app development.

Safeguard your organization from emerging dangers using our AI-driven security solution that consistently outpaces malicious entities. Ensure your team's vigilance with our on-demand red teaming service that replicates social engineering threats on mobile devices. You can select from a range of dynamic scenarios that reflect actual risks. Evaluate vulnerabilities within both individuals and teams through in-depth engagement analytics. Keep abreast of worldwide attack patterns. Implement our mobile protection to secure communications across SMS, WhatsApp, and voice calls. Our system leverages sophisticated AI to understand the motives of attackers, effectively thwarting their efforts even as their methods evolve. This proactive approach not only fortifies your defenses but also enhances your team's preparedness for unpredictable threats.

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.

NeuVector provides complete security for the entire CI/CD process. We provide vulnerability management and attack blocking in all production with our patented container firewall. NeuVector provides PCI-ready container security. You can meet your requirements in less time and with less effort. NeuVector protects IP and data in public and private cloud environments. Continuously scan the container throughout its lifecycle. Security roadblocks should be removed. Incorporate security policies from the beginning. Comprehensive vulnerability management to determine your risk profile. The only patentable container firewall provides immediate protection against known and unknown threats for zero days. NeuVector is essential for PCI and other mandates. It creates a virtual firewall to protect personal and private information on your network. NeuVector is a kubernetes-native container security platform which provides complete container security.

Create your RAG system using a more straightforward approach than options such as LangChain, enabling you to select from an extensive array of hosted and remote services for vector databases, datasets, Large Language Models (LLMs), and application integrations. Leverage SciPhi to implement version control for your system through Git and deploy it from any location. SciPhi's platform is utilized internally to efficiently manage and deploy a semantic search engine that encompasses over 1 billion embedded passages. The SciPhi team will support you in the embedding and indexing process of your initial dataset within a vector database. After this, the vector database will seamlessly integrate into your SciPhi workspace alongside your chosen LLM provider, ensuring a smooth operational flow. This comprehensive setup allows for enhanced performance and flexibility in handling complex data queries.

Elevate your threat hunting and IT security operations with advanced querying and remote response functionalities. Safeguard against ransomware with file protection, automatic recovery solutions, and behavioral analytics designed to thwart ransomware and boot record intrusions. Intercept X integrates deep learning technology, utilizing artificial intelligence to identify both known and unknown malware without depending on signatures. Block attackers by preventing the exploits and methods they use to spread malware, steal credentials, and evade detection. A highly skilled team of threat hunters and response specialists proactively takes decisive actions to neutralize even the most advanced threats on your behalf. Additionally, active adversary mitigation ensures the prevention of persistence on systems, offers protection against credential theft, and enhances the detection of malicious traffic, further strengthening your security posture. With these robust features, organizations can significantly increase their resilience against evolving cyber threats.

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.

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.

SaaS Shield is an application data protection platform that developers and Ops can use to better protect the data in cloud applications. Using application-layer encryption, SaaS Shield handles key orchestration, lifecycles, workflows, and supports multi-tenant systems that need to offer HYOK/BYOK. Together with IronCore's other products, meaningfully protected data can still be usable and it can be searched over with Cloaked Search and Cloaked AI.

Cosmian’s Data Protection Suite offers a robust and advanced cryptography solution designed to safeguard sensitive data and applications, whether they are actively used, stored, or transmitted through cloud and edge environments. This suite features Cosmian Covercrypt, a powerful hybrid encryption library that combines classical and post-quantum techniques, providing precise access control with traceability; Cosmian KMS, an open-source key management system that facilitates extensive client-side encryption dynamically; and Cosmian VM, a user-friendly, verifiable confidential virtual machine that ensures its own integrity through continuous cryptographic checks without interfering with existing operations. Additionally, the AI Runner known as “Cosmian AI” functions within the confidential VM, allowing for secure model training, querying, and fine-tuning without the need for programming skills. All components are designed for seamless integration via straightforward APIs and can be quickly deployed through marketplaces such as AWS, Azure, or Google Cloud, thus enabling organizations to establish zero-trust security frameworks efficiently. The suite’s innovative approach not only enhances data security but also streamlines operational processes for businesses across various sectors.

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.

LanceDB is an accessible, open-source database specifically designed for AI development. It offers features such as hyperscalable vector search and sophisticated retrieval capabilities for Retrieval-Augmented Generation (RAG), along with support for streaming training data and the interactive analysis of extensive AI datasets, making it an ideal foundation for AI applications. The installation process takes only seconds, and it integrates effortlessly into your current data and AI toolchain. As an embedded database—similar to SQLite or DuckDB—LanceDB supports native object storage integration, allowing it to be deployed in various environments and efficiently scale to zero when inactive. Whether for quick prototyping or large-scale production, LanceDB provides exceptional speed for search, analytics, and training involving multimodal AI data. Notably, prominent AI companies have indexed vast numbers of vectors and extensive volumes of text, images, and videos at a significantly lower cost compared to other vector databases. Beyond mere embedding, it allows for filtering, selection, and streaming of training data directly from object storage, thereby ensuring optimal GPU utilization for enhanced performance. This versatility makes LanceDB a powerful tool in the evolving landscape of artificial intelligence.

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.

Conventional endpoint detection and response (EDR) systems concentrate solely on the activities within endpoints to identify potential threats. This narrow focus results in a lack of comprehensive context, hindering accurate attack analysis and resulting in an incomplete understanding of security incidents, alongside a propensity for numerous false positives and negatives. Consequently, organizations find themselves needing to deploy various point solutions and maintain large teams for incident response. Qualys addresses these limitations by introducing a novel multi-vector approach, leveraging the robust capabilities of its scalable Cloud Platform to enhance EDR with essential context and extensive visibility across the entire attack lifecycle—from prevention through detection to response. The Qualys Multi-Vector EDR integrates various contextual elements such as asset discovery, a detailed software inventory, insights into end-of-life assets, vulnerabilities, exploitable conditions, misconfigurations, comprehensive endpoint telemetry, and network accessibility, all supported by a powerful backend that facilitates accurate correlation for effective assessment, detection, and response—all within a single cloud-based application. This approach not only streamlines the process but also empowers organizations to respond more effectively to threats.

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.

The number of security firms is at an all-time high, creating a multitude of solutions, yet the frequency of successful attacks has also reached unprecedented levels. This situation suggests that merely creating new defenses is not a viable solution. Reach offers an innovative approach to safeguarding your organization. It provides immediate insights into threats targeting your team, identifies areas of vulnerability, and reveals unutilized security capabilities. With a deep understanding of the attackers' profiles, the significance of their targets, and the methods they employ, Reach delivers a comprehensive analysis of the attack landscape. By evaluating vast amounts of data, it pinpoints how you are being compromised and formulates the most effective response tailored to your specific risks and available resources. You can adjust configurations, close security gaps, and optimize your defenses seamlessly, either automatically or with just a single click. Furthermore, Reach supplies configurations as code, ensures complete automation, and offers extensive deployment documentation that can be seamlessly integrated into your change control processes. This multifaceted approach allows businesses to stay ahead of evolving threats while maximizing their existing security investments.

Reclaim Security is an advanced cybersecurity platform powered by artificial intelligence, designed to autonomously detect and rectify security vulnerabilities within an organization’s current security framework and tools. Rather than merely identifying weaknesses or sending out alerts, it emphasizes automated remediation, enabling security teams to efficiently address misconfigurations, apply security policies, and mitigate risks with minimal manual effort. The platform conducts thorough scans of the organization’s security apparatus, encompassing cloud services, identity management systems, endpoint protection mechanisms, and other defensive measures to uncover deficiencies, poorly configured settings, or ineffective controls that could be targeted by cybercriminals. When vulnerabilities are identified, it evaluates them against real-world attack methodologies and prioritizes the most critical threats. Following this assessment, it suggests appropriate remediation strategies and can automatically implement those adjustments once approved, ensuring that security configurations are consistently optimized and resilient against potential attacks. By streamlining the remediation process, Reclaim Security enhances the overall security posture of an organization.

By collaborating, we can effectively combat cyber attacks at every endpoint, throughout the entire organization, and wherever the conflict unfolds. Cybereason offers unparalleled visibility and precise identification of both familiar and unfamiliar threats, empowering defenders to harness the strength of genuine prevention. The platform supplies comprehensive context and correlations from the entire network, enabling defenders to become skilled threat hunters who can identify covert operations. With just a simple click, Cybereason drastically cuts down the time needed for defenders to investigate and resolve incidents through both automated processes and guided remediation. Analyzing an astounding 80 million events per second, Cybereason operates at a scale that is 100 times greater than many other market solutions. This remarkable capability allows for a reduction in investigation time by as much as 93%, empowering defenders to respond to new threats in mere minutes instead of days. Ultimately, Cybereason redefines the standards of threat detection and response, creating a safer digital landscape for all.

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.

txtai is a comprehensive open-source embeddings database that facilitates semantic search, orchestrates large language models, and streamlines language model workflows. It integrates sparse and dense vector indexes, graph networks, and relational databases, creating a solid infrastructure for vector search while serving as a valuable knowledge base for applications involving LLMs. Users can leverage txtai to design autonomous agents, execute retrieval-augmented generation strategies, and create multi-modal workflows. Among its standout features are support for vector search via SQL, integration with object storage, capabilities for topic modeling, graph analysis, and the ability to index multiple modalities. It enables the generation of embeddings from a diverse range of data types including text, documents, audio, images, and video. Furthermore, txtai provides pipelines driven by language models to manage various tasks like LLM prompting, question-answering, labeling, transcription, translation, and summarization, thereby enhancing the efficiency of these processes. This innovative platform not only simplifies complex workflows but also empowers developers to harness the full potential of AI technologies.