Adept
Defense-in-Depth Platform
AI Cybersecurity PlatformPrompt Firewall · RAG Neutralizer · Red-Teaming
Platform Engine · Sub-15ms Proxy Firewall

Adept Kawas

Real-Time AI Cybersecurity Proxy & Prompt Firewall

Defensive Perimeter

Sub-15ms Real-Time Token Inspection & Firewall Architecture

Adept Kawas is the enterprise real-time security proxy, prompt injection firewall, and adversarial threat defense platform designed to shield foundation models, RAG vector stores, and autonomous agent swarms.

Operating inline between users, ingestion channels, and inference endpoints, Kawas inspects input tokens, retrieved knowledge chunks, and model responses in sub-15 milliseconds, detecting and neutralizing prompt injections, jailbreaks, data exfiltration, and unauthorized tool invocations.

Coupled with Adept’s continuous adversarial red-teaming intelligence, Kawas provides unbreakable defense-in-depth against emerging AI-specific attack vectors without impacting end-user latency or system fluidity.

Defensive Pillars

How Kawas Neutralizes Exploits

Real-Time Inline Prompt Firewall

Inspects raw token streams and semantic embeddings in sub-15ms to neutralize direct jailbreaks, cognitive role-play exploits, and multilingual cipher bypasses.

Indirect Prompt Injection Neutralizer

Scans ingested documents, scraped web data, and external API responses before RAG indexing, preventing poisoned documents from hijacking agent reasoning.

Cryptographic Tool Authorization Boundary

Enforces strict permission scopes, schema invariants, and idempotency guarantees before agent function calls can reach internal databases or financial APIs.

Continuous Adversarial Threat Feeds

Dynamic security rule updates generated from Adept’s red-team laboratory, protecting systems against zero-day jailbreaks before public disclosure.

System Modules

Defense-in-Depth for Compound AI Workloads

Sub-15ms Semantic Anomaly Proxy

High-performance Rust-based proxy architecture that evaluates token embeddings and semantic intent without adding perceptible round-trip latency.

Ultra-low latency vector similarity distance classifiers
Token entropy analysis detecting encoded and obfuscated payloads
Configurable blocking, sanitizing, or honeypot diversion policies

RAG Knowledge Base & Chunk Sanitizer

Active document hygiene engine that analyzes PDFs, spreadsheets, and HTML chunks at ingestion time for hidden adversarial instructions.

Hidden visual text and zero-font-size adversarial instruction detection
Chunk-level semantic taint tracking throughout retrieval lifecycles
Automated isolation of compromised vector database namespaces

Data Exfiltration & PII Masking Engine

Bidirectional inspection that intercepts model output tokens to prevent leaking system prompts, proprietary training data, or confidential customer records.

High-speed regex and NER-based PII redaction at the wire
System prompt reconstruction and memorization signature detection
Encrypted audit logging of all intercepted security events

Automated Fuzzing & Red-Teaming Integration

Seamless integration with Adept’s red-teaming suite, allowing continuous automated security audits that test Kawas defensive thresholds against 100k+ attack vectors.

Automated OWASP Top 10 for LLMs vulnerability scanning
Continuous adaptive multi-turn jailbreak fuzzing
Executive risk posture reporting and compliance certifications
Engine Architecture

Zero-Trust High-Performance Proxy Architecture

Kawas is built in systems-level Rust for deterministic memory safety and microsecond-level execution, capable of handling tens of thousands of concurrent inference streams with zero jitter.

Available as an Envoy/Nginx sidecar, Kubernetes ingress controller, or API gateway plugin
Hardware-accelerated embedding inference running on CPU (AVX-512) or edge TPUs
Full mutual TLS (mTLS) and confidential compute enclave compatibility
Real-time SIEM forwarding to Splunk, Datadog, AWS CloudWatch, and Elasticsearch
Kawas Specifications

Frequently Asked Questions

Kawas uses a multi-tier detection pipeline: lightweight token entropy filters and compiled regex triage execute in sub-millisecond time, followed by optimized semantic embedding classifiers running on AVX-512 optimized cores.