Prompt Security

Monitors LLM application traffic in real-time to identify and flag prompt injection attempts before they reach the model. Analyzes input payloads against patterns indicative of injection attacks and blocks malicious requests.

Detects and blocks attempts to circumvent LLM safety guidelines through sophisticated jailbreak techniques. Identifies patterns that try to override model instructions or elicit harmful outputs.

Monitors LLM outputs to detect and prevent sensitive data from being extracted or leaked through model responses. Identifies patterns where confidential information is being exposed to unauthorized users.

Allows security teams to define and enforce tailored guardrails and policies specific to their organization's use cases and risk tolerance. Enables fine-grained control over LLM behavior without broad restrictions.

Provides continuous visibility into all requests and responses flowing through LLM applications without requiring architectural changes. Captures detailed logs of inference activity for audit and analysis purposes.

Identifies emerging attack patterns and known threat signatures targeting LLM applications. Continuously updates detection rules based on evolving threat landscape and known attack techniques.

Automatically identifies and classifies sensitive data in LLM inputs and outputs, then applies masking or redaction rules to prevent exposure. Supports PII, credentials, and custom data types.

Secures LLM API endpoints by enforcing authentication, rate limiting, and access control policies. Prevents unauthorized access and abuse of LLM services.

Generates comprehensive audit trails and compliance reports documenting all LLM application activity, security events, and policy enforcement. Supports regulatory requirements and internal audits.

Tailors security rules and detection patterns to specific LLM models and their known vulnerabilities. Adapts protection strategies based on the underlying model architecture and behavior.