AI Agent Memory Encryption

AES-256 encrypted storage for AI agent memory. Protect sensitive conversation data, meet compliance requirements, and keep agent memories private.

AES-256-GCM Encryption at Rest MIT License Open Source

Why Encryption Matters for AI Agent Memory

AI agents remember everything — including sensitive information from your conversations. When agent memory is stored unencrypted, it creates security risks:

Data at rest — Unencrypted memory files expose conversation history to anyone with filesystem access
Compliance requirements — GDPR Article 32, EU AI Act, SOC 2, HIPAA all require encryption of sensitive data
Supply chain attacks — Memory files on shared systems or CI/CD pipelines can be read by unauthorized parties
Secret leakage — API keys, credentials, and internal decisions stored in plain memory

"Implement encryption at rest: Store sensitive data encrypted in databases and file systems using AES-256 encryption, ensuring that even if storage is compromised, data remains protected." — The Agentic Brief, November 28, 2025

AES-256: The Standard for Encrypted Storage

🔒 AES-256-GCM

Authenticated encryption with Galois Counter Mode. Both confidentiality and integrity protection.

🔑 Keychain Integration

macOS Keychain stores encryption keys securely. Keys never stored alongside encrypted data.

🔌 Zero-Cloud Keys

Encryption keys stay on your machine. No key management service required.

🚀 Transparent

Encryption applied automatically before storage, decrypted on retrieval. No application changes needed.

AI Agent Memory Solutions: Encryption Comparison

Solution	AES-256	Encryption at Rest	Key Management	License
★ agent-memory	AES-256	Yes	Custom (raw key)	MIT
omega-memory	AES-256-GCM	Yes (optional)	macOS Keychain	MIT
Mem0	—	—	Cloud-managed	Open core
Zep	—	Partial	Cloud + self-host	Apache 2.0
Letta	—	—	Self-hosted	Apache 2.0
Supermemory	—	—	Cloud-only	MIT

omega-memory: AES-256-GCM + macOS Keychain

omega-memory is a new competitor with strong encryption:

"Encryption at Rest (optional) — AES-256-GCM encrypted storage with macOS Keychain integration." — omega-memory GitHub

Key features:

Claude Code hooks for automatic memory capture
MCP server for cross-platform agents
Local embedding model (no cloud)
Benchmarks at omegamax.co/benchmarks

agent-memory: AES-256 + TTL + MCP v3.2

agent-memory combines encryption with unique features no competitor offers:

# agent-memory — AES-256 encryption + TTL + MCP v3.2
pip install agent-memory

# Run with encryption enabled
python -m agent_memory.mcp_server \\
  --storage json \\
  --path ./secure_memory.json

# Store encrypted memories with auto-expiration
memory_add key="customer_context" value="..." ttl_seconds=86400

# AES-256 encryption applied before storage
# TTL auto-expires old entries — no stale sensitive data left behind
# MCP v3.2 — connect to any agent: Claude Code, Cursor, OpenClaw, OpenHands

What makes agent-memory different:

AES-256 + TTL combined — Encrypted memories auto-expire. No other solution has both.
MCP v3.2 native — Works with any MCP-compatible agent, not just Claude Code
JSON / SQLite / Redis backends — Choose your storage, keep encryption
100% local — Keys and data never leave your infrastructure
MIT license — No vendor lock-in, audit the code

Secure Storage for AI Agents — 2026 Guide

"If your agent stores customer records or internal strategy documents in a vector store, that data needs to be protected just as strictly as a standard production database." — Fast.io AI Agent Secure Storage Guide (2026)

agent-memory on GitHub Try Live Demo