I built a cryptographic memory layer for humans in Python tags: python, opensource, security, blockchain

Source: Dev.to

Quick start

vault = MemoryVault(encryption_key="your-secret-key")

Capture Layer — Gets data in

Manual entries now, AI agents later.

Synthesis Layer — AI enrichment

Summarization, pattern detection, emotional analysis. (Coming in v0.2)

Verification Layer — The cryptographic core

This is where it gets interesting.

Permanence Layer — Anchoring verified hashes

Local storage, Arweave, Ethereum L2, or IPFS.

The crypto decisions I made (and why)

Key derivation: HKDF, not raw SHA‑256

My first implementation derived encryption and signing keys by doing SHA‑256(master_key + purpose). It worked, but it isn’t how serious cryptographic systems operate. I switched to HKDF (RFC 5869), the industry‑standard used by TLS 1.3 and the Signal Protocol.

from cryptography.hazmat.primitives.kdf.hkdf import HKDF
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.ciphers.aead import AESGCM
import os

def _derive_key(self, purpose: bytes) -> bytes:
    # Example derivation using HKDF
    hkdf = HKDF(
        algorithm=hashes.SHA256(),
        length=32,
        salt=None,
        info=purpose,
    )
    return hkdf.derive(self._master_key)

def encrypt(self, plaintext: str) -> tuple[bytes, bytes]:
    nonce = os.urandom(12)
    aesgcm = AESGCM(self._enc_key)
    ciphertext = aesgcm.encrypt(nonce, plaintext.encode("utf-8"), None)
    return ciphertext, nonce

Signing: HMAC‑SHA256

All signed data uses HMAC‑SHA256 to ensure integrity and authenticity.

import hmac
import hashlib

def sign(self, data: bytes) -> bytes:
    return hmac.new(self._sign_key, data, hashlib.sha256).digest()

AI capture agents (v0.2)

Future versions will include AI agents that automatically capture and annotate entries.

Try it

• GitHub:
• License: MIT
• Test suite: 28 tests passing
• No venture capital, no tokens—just a tool I think should exist.