Introduction
As generative AI and Large Language Models (LLMs) rapidly transform enterprise operations, they introduce novel security challenges that traditional cybersecurity tools aren't designed to address. Organizations deploying AI systems face risks including prompt injection attacks, data poisoning, sensitive information leakage, and AI hallucinations that can lead to compliance violations or reputational damage.
This emerging threat landscape has given rise to a new category of security solutions specifically designed to protect AI systems. In this article, we explore ten cutting-edge commercial tools that are leading the charge in securing generative AI deployments, from runtime protection to governance frameworks that enable organizations to harness AI's power while maintaining security posture and compliance.
1. Securiti
Visit WebsiteKey Highlights
- Enterprise AI copilot with built-in rule awareness
- Context-aware LLM firewalls that protect AI interactions
- Data vectorization and ingestion pipelines for AI applications
- Data curation and sanitization services for model training
- Unstructured data governance capabilities
- Extensive integration across hybrid cloud and SaaS environments
1. Securiti
Securiti's Data Command Center provides a comprehensive platform for managing both data and AI security across hybrid multicloud environments. Using an advanced knowledge graph architecture, it delivers contextual awareness of data and AI objects throughout your organization.
Key Highlights
- Enterprise AI copilot with built-in rule awareness
- Context-aware LLM firewalls that protect AI interactions
- Data vectorization and ingestion pipelines for AI applications
- Data curation and sanitization services for model training
- Unstructured data governance capabilities
- Extensive integration across hybrid cloud and SaaS environments
2. Simbian
Visit WebsiteKey Highlights
- Configure AI agents and set appropriate permission boundaries
- Assign tasks using simple natural language commands
- Allow automated execution of routine security tasks
- Built on LLMs trained specifically on security datasets
- Available in both SaaS and on-premises deployments
- SOC2 compliant with browser and terminal integrations
2. Simbian
Simbian AI takes a different approach to AI security by deploying specialized AI agents that assist security teams in their daily operations. The platform features purpose-built agents for SOC operations, GRC functions, and threat hunting that seamlessly integrate with existing security tools and workflows.
Key Highlights
- Configure AI agents and set appropriate permission boundaries
- Assign tasks using simple natural language commands
- Allow automated execution of routine security tasks
- Built on LLMs trained specifically on security datasets
- Available in both SaaS and on-premises deployments
- SOC2 compliant with browser and terminal integrations
3. Avathon
Visit WebsiteKey Highlights
- Monitoring and management for legacy infrastructure systems
- AI-based inventory management and supply chain visibility
- Technology solutions for autonomous production systems security
- Smart city infrastructure management and protection
- Extension of secure operational life for valuable assets
- Protection against emerging AI-related infrastructure threats
3. Avathon
Avathon offers an AI-driven approach to infrastructure management and security. The platform focuses on extending asset lifecycle, improving operational safety, and optimizing infrastructure performance through artificial intelligence integration.
Key Highlights
- Monitoring and management for legacy infrastructure systems
- AI-based inventory management and supply chain visibility
- Technology solutions for autonomous production systems security
- Smart city infrastructure management and protection
- Extension of secure operational life for valuable assets
- Protection against emerging AI-related infrastructure threats
4. Operant AI
Visit WebsiteKey Highlights
- AI Application Protection against prompt injection attacks
- API Security with adaptive internal firewalls
- Cloud Application Security for Kubernetes environments
- Automated redaction of sensitive data
- Real-time threat detection across container environments
- Zero performance overhead security monitoring
4. Operant AI
Operant delivers runtime protection specifically designed for AI applications and cloud-native environments. The platform stands out for its zero-instrumentation approach, requiring no code changes while providing robust security.
Key Highlights
- AI Application Protection against prompt injection attacks
- API Security with adaptive internal firewalls
- Cloud Application Security for Kubernetes environments
- Automated redaction of sensitive data
- Real-time threat detection across container environments
- Zero performance overhead security monitoring
5. TestSavantAI
Visit WebsiteKey Highlights
- Protection for text, vision, multi-modal, and RAG workflows
- Automated scanning and threat detection systems
- Granular policy management and compliance monitoring
- AI governance and oversight capabilities
- Comprehensive security telemetry and analytics
- Algorithmic red teaming and threat intelligence
5. TestSavantAI
TestSavant focuses on protecting enterprise generative AI applications and Large Language Models from a range of threats including data poisoning, prompt injection attacks, and toxic outputs. The platform is designed for easy integration via a single line of code or REST API calls.
Key Highlights
- Protection for text, vision, multi-modal, and RAG workflows
- Automated scanning and threat detection systems
- Granular policy management and compliance monitoring
- AI governance and oversight capabilities
- Comprehensive security telemetry and analytics
- Algorithmic red teaming and threat intelligence
6. SPLX
Visit WebsiteKey Highlights
- Automated vulnerability scanning for AI-specific attack vectors
- Framework compliance verification against emerging standards
- Multi-language testing capabilities spanning over 20 languages
- CI/CD pipeline integration for continuous security validation
- Domain-specific penetration testing for AI applications
- Assessment of AI-specific risks like hallucinations and data leakage
6. SPLX
SplxAI Probe takes a proactive approach to AI security through automated red teaming designed specifically for conversational AI applications. The platform continuously assesses security by simulating realistic attack scenarios, including prompt injections, social engineering attempts, and sophisticated jailbreak techniques.
Key Highlights
- Automated vulnerability scanning for AI-specific attack vectors
- Framework compliance verification against emerging standards
- Multi-language testing capabilities spanning over 20 languages
- CI/CD pipeline integration for continuous security validation
- Domain-specific penetration testing for AI applications
- Assessment of AI-specific risks like hallucinations and data leakage
7. Swift Security
Visit WebsiteKey Highlights
- Monitoring and control of shadow AI usage across the organization
- Protection against data exposure in both public and private LLMs
- Security controls for code assistants and AI development tools
- Management of access policies for private LLM deployments
- Detection and blocking of risky browser extensions
- Implementation of guardrails for custom LLM applications
7. Swift Security
Swift Security addresses the widespread enterprise adoption of generative AI by providing a comprehensive platform for monitoring and controlling AI usage across organizations. This solution helps security teams gain visibility into shadow AI practices while implementing appropriate controls.
Key Highlights
- Monitoring and control of shadow AI usage across the organization
- Protection against data exposure in both public and private LLMs
- Security controls for code assistants and AI development tools
- Management of access policies for private LLM deployments
- Detection and blocking of risky browser extensions
- Implementation of guardrails for custom LLM applications
8. TensorOpera AI
Visit WebsiteKey Highlights
- Enterprise AI Platform with built-in security controls
- Secure AI Agent APIs and Services
- Training as a Service with data protection mechanisms
- Secure Model Deployment and Serving infrastructure
- Curated Marketplace for pre-vetted AI models
- Serverless and decentralized GPU job management
- Experimental tracking for distributed training
8. TensorOpera AI
TensorOpera AI provides a comprehensive platform for building and deploying secure generative AI applications at scale. The platform combines development capabilities with robust security features to support enterprise AI initiatives.
Key Highlights
- Enterprise AI Platform with built-in security controls
- Secure AI Agent APIs and Services
- Training as a Service with data protection mechanisms
- Secure Model Deployment and Serving infrastructure
- Curated Marketplace for pre-vetted AI models
- Serverless and decentralized GPU job management
- Experimental tracking for distributed training
9. Tumeryk
Visit WebsiteKey Highlights
- LLM vulnerability scanning to assess risks and generate security profiles
- AI Firewall technology to detect and prevent jailbreak attempts
- Content moderation and policy violation alerting
- Fact-checking alignment scores to identify and mitigate hallucinations
- Off-topic dialog controls to maintain conversation relevance
- Multi-tenant LLM management with conversational controls
9. Tumeryk
Tumeryk introduces the concept of Large Language Model Security Posture Management (LLM SPM), providing comprehensive security for generative AI systems throughout their lifecycle. The platform addresses the OWASP Top LLM vulnerabilities in production environments.
Key Highlights
- LLM vulnerability scanning to assess risks and generate security profiles
- AI Firewall technology to detect and prevent jailbreak attempts
- Content moderation and policy violation alerting
- Fact-checking alignment scores to identify and mitigate hallucinations
- Off-topic dialog controls to maintain conversation relevance
- Multi-tenant LLM management with conversational controls
10. Unbound Security
Visit WebsiteKey Highlights
- Discovery of AI applications used by employees across the organization
- Implementation of granular access policies for controlling AI usage
- Steering employees toward sanctioned AI alternatives
- Prevention of sensitive information upload to risky AI applications
- Comprehensive visibility into generative AI app usage
- Management of AI-related security concerns including compliance and data leakage
10. Unbound Security
Unbound Security focuses on governing the use of generative AI applications within enterprises, helping organizations maintain control over AI adoption while preventing security and compliance issues. The platform provides comprehensive discovery, policy enforcement, and protection capabilities.
Key Highlights
- Discovery of AI applications used by employees across the organization
- Implementation of granular access policies for controlling AI usage
- Steering employees toward sanctioned AI alternatives
- Prevention of sensitive information upload to risky AI applications
- Comprehensive visibility into generative AI app usage
- Management of AI-related security concerns including compliance and data leakage
Conclusion
As generative AI and LLMs become central to enterprise operations, securing these systems requires specialized tools designed to address their unique security challenges. The ten solutions covered in this article represent the cutting edge of AI security, offering various approaches from runtime protection to governance frameworks.
While each tool takes a different approach to AI security, they share a common goal: enabling organizations to capture the transformative benefits of generative AI while managing the associated risks. Whether you're concerned about prompt injection attacks, data leakage, or maintaining compliance, these solutions provide the capabilities needed to build and deploy AI systems securely.
As this emerging field continues to evolve, organizations should evaluate these tools based on their specific AI deployment scenarios, security requirements, and regulatory obligations. By implementing appropriate security measures early in your AI journey, you can build a foundation that supports secure innovation and responsible AI adoption.