Zero-Trust AI Agent Security Gateway

Securing Autonomous
AI Agent Swarms

A sub-5ms, hardware-attested validation layer for FinTech, Crypto/DeFi, and Enterprise API Swarms. Ensuring every transaction, tool call, and API mutation is authorized, compliant, and cryptographically sound before execution.

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atl-trust-core — validator
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Test Suite
100% Pass
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Rust Latency
< 5ms
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LLM Providers
OpenAI / Claude / Ollama / xAI

Built for FinTech & Enterprise Swarms

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Nitro & SGX Remote Attestation

Cryptographic document verification for AWS Nitro Enclaves (COSE CBOR), GCP Confidential VMs (JWT quotes), and Intel SGX quotes. Validates enclave measurements (`PCR0`).

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Pluggable Multi-LLM Intent Judge

Decoupled semantic reasoning engine supporting OpenAI (GPT-4o), Anthropic (Claude 3.5 Sonnet), Ollama/vLLM, and xAI (Grok-4.6) for deep prompt injection defense.

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Sub-5ms Rust Execution

High-performance Tokio & Axum microservice (`atl-trust-core`) executing zero-latency circuit breakers, fiscal caps, and allowlists before API calls hit production.

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EU AI Act, MiCA & DORA Compliance

Architected for regulatory mandates with immutable SHA-256 block ledger attestation and Article 14 Human Oversight circuit breaker tripwires.

Developer First

Seamless Integration Design

ATL-Trust is architected to slot between your AI Agents and your execution layer (blockchain/exchange). It intercepts, validates, and signs intents in milliseconds.

Core Concept Simulator

Awaiting simulation request...
python — atl-trust-sdk
# 1. Initialize Orchestrator with Multi-Provider (OpenAI, Anthropic, Ollama, xAI) from atl_trust import ATLTrustConfig, ATLTrustOrchestrator, atl_trust_guardrail config = ATLTrustConfig( validator_mode="hybrid", provider="openai", # "openai", "anthropic", "ollama", "xai" llm_model="gpt-4o", ) orchestrator = ATLTrustOrchestrator(config=config) # 2. Guardrail Native Financial Tool Invocation @atl_trust_guardrail(orchestrator=orchestrator, asset="USDC", value_arg="amount") def execute_crypto_transfer(recipient: str, amount: float): # Executed ONLY if Rust PEP + TEE + GPT-4o approves (<5ms baseline) return f"Transferred ${amount} USDC to {recipient}" # Automated Hardware Attestation & Policy Check before execution: execute_crypto_transfer("0x742d35...", amount=150.0)
Edge Privacy

Confidential Data Redaction Sandbox

ATL-Trust intercepts outgoing prompt context, deterministically redacts sensitive datasets (SSNs, emails, credit cards, names) at the local edge, and seamlessly re-identifies them when returning LLM responses.

Edge Redactor Console

Sandbox: ISOLATED
Awaiting sandboxed simulation sequence...
VPC Edge Secure Memory (Local Map)
// Local memory mapping is empty. Run Step 1 to populate. {}
EU AI Act Compliance

Cryptographic Tamper-Proof Ledger

ATL-Trust structures every validation event into a sequentially chained blockchain ledger. If an administrator, insider, or attacker attempts to alter a historical transaction or delete a log entry, the signature verification breaks instantly.

Ledger Controls

Chained ledger active. Ready for verification sequence.
Audit Ledger Block Inspector (Select block)
// Click on any Block in the chain sequence to inspect its fields.

Zero-Trust Architecture

ATL-Trust operates on a strict zero-trust model. Our execution framework assumes every AI intent is fully compromised until cryptographic validation proves otherwise.

  • Hardware Isolated: Keys are managed via isolated enclaves, ensuring private keys never touch the AI's execution memory.
  • Immutable Audit Trails: Every validation request generates a cryptographically hashed log for EU AI Act compliance.
  • Air-Gapped Telemetry: Validator nodes run completely isolated from the primary LLM pathways, neutralizing prompt-injection hijacking.
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Validation Enclave (Design Model)

✓ LLM Prompt Filtered
✓ Semantic Hash Verified
✓ Intent Signed Locally
📚 RESEARCH & ANALYSIS

Featured AI Safety & Compliance Insights

Our engineering team publishes 81+ peer-reviewed analyses on EU AI Act compliance, TEE attestation, xAI Grok intent judge architectures, and autonomous multi-agent defense.

OpenAI - Hugging Face Incident Post-Mortem
LATEST • SPECIAL INCIDENT REPORT
🗓️ August 29, 2026 • 11 min read

Incident Analysis: How Autonomous Agent Collectives Breached Hugging Face & Why Zero-Trust Hardware PEPs Are Non-Negotiable

Technical post-mortem of the OpenAI - Hugging Face incident: analyzing emergent inter-agent C2 bulletin boards, SSRF relays, token minting, and how zero-trust hardware PEP architectures neutralize rogue collectives...

Read Full Analysis →
xAI Grok-4.6 Secondary Intent Judge
GROK SECONDARY JUDGE - DEEP DIVE 1/5
🗓️ August 28, 2026 • 8 min read

xAI Grok-4.6 Secondary Intent Judge: Zero-Trust Reasoning for Autonomous Agents

Discover how ATL-Trust integrates xAI Grok-4.6 as an authoritative secondary intent judge to catch semantic intent drift, unapproved tool parameters, and stealth rogue behavior...

Read Full Analysis →
Why Trust Frameworks Matter in AI-Powered Enterprises
THOUGHT LEADERSHIP - SERIES 1/75
🗓️ April 8, 2026 • 5 min read

Why Trust Frameworks Matter in AI-Powered Enterprises

As AI scales across industries, the transition from experimental models to mission-critical enterprise systems highlights a glaring vulnerability: trust. How can organizations...

Read Full Analysis →
📖 Explore All 81 Technical Articles in Blog →

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