Best LLM Security Tools
Compare and discover the best LLM Security software and tools for your team. Find the right solution for your needs.
Aurva provides a runtime security layer specifically designed for agentic AI architectures and LLM-driven workflows. It monitors granular data access patterns of AI agents, detects behavioral anomalies that signify prompt injection or agent hijacking, and enforces real-time compliance controls. The platform complements existing WAFs and API security tools by providing visibility into the internal logic and data orchestration of autonomous agents.
Dynamo AI specializes in the governance and security of Large Language Models (LLMs) and Generative AI agents. The platform provides automated red-teaming to identify prompt injections and jailbreaks, alongside real-time guardrails to prevent data leakage and ensure model alignment. It serves CISOs and AI leaders who need to maintain auditable compliance and safety across enterprise AI deployments.
GGroovy Security helps enterprises adopt AI without losing control of their data, an AI Security Posture Management (AI-SPM) and GenAI data-protection platform built for complete visibility and inline control. We build two products. Whiteout AI is an AI interaction interception platform that inspects and enforces policy on every AI interaction in real time, across desktop, browser, IDE, MCP agents, and cloud. Its full-LLM detection engine reads context to make decisions on compliant user AI usage. Whiteout AI surfaces shadow AI, stopping sensitive data exfiltration, enforcing security guardrails, and mapping AI-specific compliance across heterogeneous AI environments. Deployed via Groovy Security or hosted by the client organization to maximize data security. Maestro: our AI-driven penetration testing platform, automates security testing across your APIs, cloud, and AI/ML pipelines. Purpose-built for a world where AI is both the innovator and the risk.
Realm Labs provides an AI Trust and Security platform designed to monitor and secure LLM applications in production environments. It focuses on identifying and mitigating 'surprises' such as model hallucinations, prompt injections, and data leakage by providing a transparency layer for enterprise AI workflows. The solution complements existing LLM development frameworks by adding a dedicated security and observability shim to ensure model outputs align with corporate policy.
Every company should be able to innovate with AI as confidently as they build in the cloud. Generative AI adoption can be safe, accountable, and scalable -- when organizations have the visibility and control they need to manage risk, meet compliance standards, and build trust.
TSecurity built for the agentic era, by the people who built security for the cloud era.
What is LLM Security software?
Compare and discover the best LLM Security software and tools for your team. Find the right solution for your needs. With 6 llm security tools listed on Picari, you can compare features, pricing models, and real user experiences side-by-side, without speaking to a single sales rep until you're ready.
Who needs llm security tools?
LLM Security software is typically adopted by teams that have outgrown manual processes and need repeatable, scalable workflows. You'll get the most value if:
- Your team spends more than 5 hours/week on tasks that could be automated
- You're scaling past 10 team members and need consistent processes
- You need better visibility into performance metrics and ROI
- Your current tools don't integrate well with the rest of your stack
Buying criteria checklist for llm security
Before committing to a llm security platform, run through this evaluation checklist:
Common mistakes when evaluating llm security tools
- 1.Buying based on demos alone. A polished demo doesn't reveal how the tool handles your actual data and workflows. Always run a proof-of-concept.
- 2.Ignoring total cost of ownership. The sticker price is rarely the full cost, factor in implementation, training, integrations, and potential add-on fees.
- 3.Not involving end users in the evaluation. The people who'll use the tool daily should have a say. Top-down purchases often lead to low adoption.
- 4.Comparing too many tools at once. Shortlist 2–3 finalists max. Evaluating 5+ tools in parallel leads to decision fatigue and delayed timelines.
How to evaluate llm security tools on Picari
Picari is built to help security teams evaluate cybersecurity tools on their terms, no cold calls, no spam, no pressure. Here's how to get started:
- Browse and compare, Review features, pricing, and team fit for each tool above.
- Start a Briefing, Describe your problem and get a personalised shortlist of vendors in minutes.
- Run a Stack Audit, See how a new tool fits alongside what you already use, and identify gaps or overlaps.
- Open an Evaluation Room, Collaborate with your team, organize requirements, and message vendors directly, all in one place.
Not sure which llm security tool fits?
Start a Briefing to tell us what you're trying to solve, get a shortlist and a stack audit in minutes.
Top LLM Security tools on Picari (2026)
Here are some of the most popular llm security tools currently listed on the platform:
- Aurva · Aurva provides a runtime security layer specifically designed for agentic AI arc…
- Dynamo Ai · Dynamo AI specializes in the governance and security of Large Language Models (L…
- Groovy Security · Groovy Security helps enterprises adopt AI without losing control of their da…
- Realm Labs · Realm Labs provides an AI Trust and Security platform designed to monitor and se…
- SolidCore.ai · Every company should be able to innovate with AI as confidently as they build in…
- Tego AI · Security built for the agentic era, by the people who built security for the clo…