Advanced AI Threat Detection & Security

Custom Transformer Architecture

Javelin’s security models are built on a proprietary, custom transformer architecture designed to detect how threats emerge in real-world AI environments. This architecture level approach enables us to deliver specialized security models for Enterprises to protect their unique threat surfaces, adapting protection across applications, risk profiles, and infrastructure with precision and control.

Adaptive Architecture for Defense-in-depth

Provides controls to manage AI Agent actions
Enforces privileges to restrict unauthorized activities
Prevents harmful actions or operations beyond intended scope

Hybrid modeling with transformer encoders and tree-based classifiers for precision and interpretability
Specialized loss functions and token-level weighting to surface subtle, low-signal threats
Continuously updated with red-teaming data to adapt to new adversarial techniques

Contextual Threat Detection

Automatic scaling to adapt as your needs grow
Ultra-low latency processing for optimal performance
Handles traffic bursts and high enterprise loads efficiently

Detects and blocks AI threats and unsafe MCP usage in real time
Protects LLMs at the input layer before threats reach the model
Enforces safety policies across any LLM or deployment environment

Security-Aligned Performance

High-performance stack for maximum efficiency
State-of-the-art throughput to handle demanding workloads
Scales to manage even the highest AI workloads

Tuned for threat sensitivity and low false positives
Compatible with real-time inference pipelines
Operates seamlessly alongside application-layer defenses

Scalable, Production-Ready Deployment

Real-time analytics and detailed reports on system performance and user activity
Supports Open Telemetry for alerts, logs, and metrics
Seamless integration with enterprise tools

Lightweight models optimized for sub-50ms inference
Supports high-throughput workloads with minimal compute overhead
Deployable across cloud, on-prem, or edge infrastructure

Visibility & Auditing

Real-time anomaly detection in AI usage
Instant reporting to Security Operations
Enhances security by identifying unusual activity

Log and trace blocked prompts and model decisions
Integrates with Security Information and Event Management (SIEM) and security analytics platforms
Enables auditing for compliance and trust reporting

Detection Engines for Emerging AI Attack Vectors

Integrating LLMs into business-critical systems introduces new classes of risk. The Javelin family of models deliver state of the art performance at the Agentic context layer, built on compact, high-performance transformer architectures designed to secure every stage of LLM interaction. From prompt-level filtering, tool-filtering to multi-turn manipulation detection, our custom models block unsafe, adversarial, and non-compliant actions before they reach your system.

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Prompt Injection Detection Model

Provides controls to manage AI Agent actions
Enforces privileges to restrict unauthorized activities
Prevents harmful actions or operations beyond intended scope

Detects embedded threats, indirect injections, and override attempts across complex prompt flows
Uses attention-based pooling and token-level weighting to catch subtle manipulations

Jailbreak Detection Model

Automatic scaling to adapt as your needs grow
Ultra-low latency processing for optimal performance
Handles traffic bursts and high enterprise loads efficiently

Flags attempts to override safety protocols, including evasive prompts and obfuscated phrasing
Trained on diverse jailbreak techniques, including multi-turn and policy bypass attacks

Content Safety Model

High-performance stack for maximum efficiency
State-of-the-art throughput to handle demanding workloads
Scales to manage even the highest AI workloads

Filters toxic, harmful, or policy-violating inputs before reaching your LLM
Provides robust protection in regulated, user-facing, or high-sensitivity environments

Red Teaming Model

Real-time analytics and detailed reports on system performance and user activity
Supports Open Telemetry for alerts, logs, and metrics
Seamless integration with enterprise tools

Uses hybrid architectures for resilience against edge cases and low-signal threats
Benchmarked on ToxicChat, DAN, JavelinBench, datasets derived from tools like Garak, and custom evaluation sets

MCP Security Model

Real-time anomaly detection in AI usage
Instant reporting to Security Operations
Enhances security by identifying unusual activity

Trained to detect indirect prompt injection & tool poisoning attacks vectors based on tool metadata
Detect and filter out malicious instructions embedded in external content, such as documents, web pages or emails extracted through MCP tool endpoints

AI Security Fabric

Javelin Red

Javelin Models

AI Developer Toolkit

Javelin Models

Javelin Red

AI Security Edge

AI Toolkit

Research-Backed, High-Performance Security Models