LLM Security Platforms Explained begins with a simple reality: large language models are now being deployed into production systems that handle sensitive data, make decisions, and interact with users at scale. As organisations adopt generative AI across customer support, software development, research, and internal operations, they are discovering that traditional security tooling does not address the unique risks introduced by LLMs.
These risks include prompt injection, data leakage, unsafe outputs, model misuse, hallucinations, and weak oversight of how AI systems behave once deployed. In response, a new category of security tooling has emerged—LLM security platforms—designed specifically to monitor, test, control, and govern large language models throughout their lifecycle.
Unlike conventional application or cloud security tools, LLM security platforms focus on runtime behavior, model integrity, and policy enforcement for AI systems. They play a critical role in GenAI governance, helping organisations establish guardrails, demonstrate accountability, and reduce operational risk as AI becomes embedded into core business processes.
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Key LLM Security Platforms
Lakera
Lakera focuses on protecting large language models from prompt injection, misuse, and malicious inputs. Its platform provides runtime safeguards designed to prevent unsafe or unintended model behavior in production environments.
WhyLabs
WhyLabs delivers observability and monitoring for machine learning and LLM systems. It helps teams detect data drift, model degradation, and anomalous behavior that can indicate emerging security or reliability risks.
Lasso Security
Lasso Security specialises in securing enterprise use of generative AI tools. The platform focuses on preventing sensitive data exposure and enforcing usage policies across LLM-powered applications.
Calypso AI
Calypso AI provides AI risk management and security solutions designed for both commercial and government use cases. Its platform emphasises model evaluation, governance, and protection against adversarial manipulation.
Qodex.ai
Qodex.ai focuses on securing AI workflows and protecting LLM interactions from abuse. The platform is designed to help organisations control how models are accessed and used across applications.
LLMFuzzer
LLMFuzzer applies fuzz testing techniques to large language models to uncover vulnerabilities and failure modes. It is primarily used to stress-test LLM behavior before and during production deployment.
Vigil
Vigil provides real-time monitoring and alerting for AI systems. Its platform helps security and engineering teams identify abnormal LLM behavior that could signal misuse or exploitation.
G-3PO
G-3PO focuses on automating security controls and policy enforcement for generative AI systems. The platform aims to bring consistency and repeatability to AI security operations.
EscalateGPT
EscalateGPT is designed to support incident detection and escalation within LLM-powered workflows. It helps teams respond quickly when AI systems produce unsafe or unexpected outcomes.
Aim Security
Aim Security addresses AI risk posture management by applying security controls across AI applications and data flows. The platform supports governance, visibility, and risk reduction for enterprise GenAI deployments.
Prompt Security
Prompt Security focuses specifically on protecting prompts, responses, and user interactions with LLMs. Its tooling helps organisations defend against prompt-based attacks and misuse.
Robust Intelligence
Robust Intelligence specialises in testing and hardening AI models before deployment. Its platform identifies vulnerabilities, bias, and failure conditions that could lead to security or compliance issues.
Darktrace
Darktrace applies AI-driven threat detection across networks, cloud environments, and increasingly AI-enabled systems. Its approach extends behavioral analysis principles to emerging AI and LLM-related risks.
Why LLM Security Platforms Matter
As generative AI becomes business-critical infrastructure, organisations need visibility and control over how models behave in real-world conditions. LLM security platforms provide the tooling required to move from experimental AI usage to governed, secure, and auditable deployments.
For security leaders, these platforms are becoming foundational to AI risk management strategies—supporting compliance, reducing exposure, and enabling responsible innovation without slowing adoption.
Further Reading
To build a strong foundation, begin with understanding what is AI security which explains why AI introduces a new attack surface.
We also have a post that lists some of the industry's best AI security companies and why buyer education is driving demand in AI security webinars.
Explore governance and protection strategies in our roundup of LLM security platforms.