LLM SECURITY

Securely deploy LLMs in your apps

Security is a key blocker for launching LLM-based applications to production. Bad actors can gain access to Personally Identifiable Information (PII) or can rewire the model behavior with prompt injections. A21.ai LLM Security offering enables teams to protect LLM applications against malicious prompts and guardrails the responses

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Securing LLM Applications:

A Critical Enterprise Imperative

In today’s digital landscape, the security of Large Language Model (LLM) applications is paramount for enterprises.

These advanced models, while powerful, are susceptible to unique vulnerabilities such as prompt injections and data leakage, which can lead to the exposure of Personally Identifiable Information (PII).

Furthermore, the risk of generating misinformation or inappropriate content can have severe consequences, including customer loss, legal complications, and irreparable reputational damage.

By implementing robust security measures like A21.ai’s LLM Security framework, enterprises can effectively shield their LLM applications from these threats.

This proactive approach not only ensures a consistent and safe user experience but also upholds the integrity and reliability of the enterprise in a competitive and rapidly evolving technological environment.

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Protect llms from vulnerabilities

Prompt Injections

Malicious prompts designed to confuse the system into providing harmful outputs. Monitoring for such prompts and for changes in LLM behavior is crucial to ensure consistent user experience

Data Leakage

LLMs are vulnerable to targeted attacks designed to leak confidential data. Evaluating prompts for these attacks and blocking responses containing PII is key for production LLMs.

Hallucinations

LLMs can produce misinformation or inappropriate content due to “hallucinations.” Without monitoring this can lead to customer loss, legal issues, and reputational damage.

a21.ai approach to Protect you

Methodology to keep LLM safe and secured

Deploying OWASP Top 10 guidelines for LLM Apps

LLMs are susceptible to a range of vulnerabilities which are unlike the vulnerabilities in traditional software. The guidance around these vulnerabilities is rapidly evolving and A21.ai is providing an extensible platform that enables teams to adopt best practices that are available today and keep these best practices up to date. A21.ai can help you implement telemetry to capture the OWASP Top 10 for LLM Applications (v0.5) and will be implementing the new guidelines as they become available.

A21.ai uses telemetry to enable inline guardrails, continuous evaluations, and observability.

Protection for open source and proprietary models

Protect the LLM user experience against the key LLM vulnerability types. Deploy inline guardrail with customizable metrics, thresholds, and actions. The solution is applicable to internal and external LLM applications of any scale. Whether you are integrating with a public API or running a proprietary model, use the A21.ai proxy to ensure guardrails and logging of each prompt/response pair. A21.ai integrates with LangChain, HuggingFace, MosaicML, OpenAI, Falcon, Anthropic, and more.
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