It suits application teams that want to inspect LLM requests before they reach a provider, including for prompt injection, PII, or data leakage risks.
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Best LLM Security Tools 2026
Safeguarding an LLM application can involve controls for different kinds of risk. Compare model-abuse detection, output guardrails, and prompt injection defense, then consider whether PII redaction or secrets detection is relevant to your needs. Deployment model helps you assess operational fit, while free-plan availability and paid-from pricing provide cost points to weigh. The entries include Sanctum Runtime, Amazon Bedrock Guardrails, and Openlayer Guardrails, along with PromptGuard and GLACIS. Lasso AI Security Platform, WitnessAI, and HiddenLayer AI Guardrails are also listed. Match the specific protections and deployment options shown to the safeguards you are looking to put in place.
Prompt Inspector
It suits developers and teams adding prompt safety checks to applications through APIs, SDKs, or MCP.
WebWindowsMac+3NVIDIA NeMo Guardrails
NeMo Guardrails is for developers and teams building LLM applications that need configurable policy checks.
WindowsMacLinux+2CyberSecEval
CyberSecEval suits people evaluating cybersecurity risks or defensive behavior in large language models.
WebMacLinux+2Sanctum Runtime
It suits teams building AI agents, robotics, workflow automation, or other systems that can take real-world actions.
AndroidiPhone & iPadWeb+3It suits engineering, AI, security, compliance, and finance teams working with AI systems, including teams in healthcare and financial services.
Inferwall suits teams operating their own LLM infrastructure and wanting configurable input and output screening.
VotalAI is aimed at enterprise AI teams, including platform and security engineers, that need policies and visibility around agent prompts, outputs, and tool calls.
It may suit teams building chatbots, RAG pipelines, or agents that need checks for risks such as PII exposure or jailbreaks.
GLACIS may suit AI-agent builders or operators and teams selling AI to healthcare or other regulated buyers.
It is aimed at developers building LLM applications who want self-hosted prompt and output scanners or documented integrations.
WitnessAI is aimed at enterprises managing AI use across employees, applications, developers, and agents.
Lasso is designed for enterprises managing AI applications, agents, and connected resources.
It is aimed at organizations governing enterprise LLM applications and agent interactions.
This product suits organizations governing AI models, agents, sensitive information, and tool access.