Lakera
Lakera is an AI-powered security platform built to protect generative AI systems from emerging threats like prompt attacks, data leakage, and model manipulation.
FAQ
How does Lakera protect against prompt injections and model misuse?
Lakera employs runtime monitoring of all prompts and interactions to detect malicious inputs (e.g. prompt injections, system prompt leaks). It uses its threat intelligence database (from Gandalf plus internal & open-source data) to classify and block or mitigate harmful behavior before it affects model output.
Is Lakera model-agnostic? Can it work with any LLM or AI model?
Yes. Lakera is designed to work with any large language model and supports various modalities. Its API-based architecture makes it possible to enforce security policies across different model backends without deeply coupling to any single model provider.
What is Gandalf and how does it relate to Lakera’s security offerings?
Gandalf is Lakera’s educational red-team game / platform where users attempt to discover and exploit weaknesses in AI agents. The adversarial data collected there helps Lakera build its threat intelligence database, which in turn improves detection and forecast of new attack patterns.
What kind of latency or overhead does Lakera introduce when protecting AI applications?
The platform is optimized for low latency, aiming for sub-50 ms runtime impact so that security protections do not degrade user experience in real-time AI systems.
Which organisations or types of businesses benefit most from Lakera?
Enterprises building or deploying generative AI, AI agents, chatbots, document / retrieval-augmented agents, multilingual AI systems, or any AI systems exposed to user inputs benefit significantly. Regulated industries, financial services, customer-facing platforms, and other high risk environments are especially likely to need its protections.
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