encryption

Add custom at-rest encryption to your LangGraph application.

.. warning:: This API is in beta and may change in future versions.

The Encryption class provides a system for implementing custom encryption of data at rest in LangGraph applications. It supports encryption of both opaque blobs (like checkpoints) and structured JSON data (like metadata, context, kwargs, values, etc.).

To use, create a separate Python file and add the path to the file to your LangGraph API configuration file (langgraph.json). Within that file, create an instance of the Encryption class and register encryption and decryption handlers as needed.

Example langgraph.json file:

{
  "dependencies": ["."],
  "graphs": {
    "agent": "./my_agent/agent.py:graph"
  },
  "env": ".env",
  "encryption": {
    "path": "./encryption.py:my_encryption"
  }
}

Then the LangGraph server will load your encryption file and use it to encrypt/decrypt data at rest.

JSON Encryptors Must Preserve Keys

JSON encryptors must not add or remove keys from the input dict. Only values may be transformed. This constraint is enforced at runtime by the server and exists because SQL JSONB merge operations (used for partial updates) work at the key level.

Correct (per-key encryption):

# Input:  {"secret": "value", "plain": "x"}
# Output: {"secret": "<encrypted>", "plain": "x"}  ✓ Keys preserved

Incorrect (key consolidation):

# Input:  {"secret": "value", "plain": "x"}
# Output: {"__encrypted__": "<blob>", "plain": "x"}  ✗ Key changed

If your encryptor needs to store auxiliary data (DEK, IV, etc.), embed it within the encrypted value itself, not as separate keys.

Basic Usage

from langgraph_sdk import Encryption, EncryptionContext

my_encryption = Encryption()

SKIP_FIELDS = {"tenant_id", "owner", "thread_id", "assistant_id"}
ENCRYPTED_PREFIX = "encrypted:"

@my_encryption.encrypt.blob
async def encrypt_blob(ctx: EncryptionContext, blob: bytes) -> bytes:
    return your_encrypt_bytes(blob)

@my_encryption.decrypt.blob
async def decrypt_blob(ctx: EncryptionContext, blob: bytes) -> bytes:
    return your_decrypt_bytes(blob)

@my_encryption.encrypt.json
async def encrypt_json(ctx: EncryptionContext, data: dict) -> dict:
    result = {}
    for k, v in data.items():
        if k in SKIP_FIELDS or v is None:
            result[k] = v
        else:
            result[k] = ENCRYPTED_PREFIX + your_encrypt_string(v)
    return result

@my_encryption.decrypt.json
async def decrypt_json(ctx: EncryptionContext, data: dict) -> dict:
    result = {}
    for k, v in data.items():
        if isinstance(v, str) and v.startswith(ENCRYPTED_PREFIX):
            result[k] = your_decrypt_string(v[len(ENCRYPTED_PREFIX):])
        else:
            result[k] = v
    return result

Field-Specific Logic

The ctx.model and ctx.field attributes tell you which model type and specific field is being encrypted, allowing different logic:

@my_encryption.encrypt.json
async def encrypt_json(ctx: EncryptionContext, data: dict) -> dict:
    if ctx.field == "metadata":
        # Metadata - standard encryption
        return encrypt_standard(data)
    elif ctx.field == "values":
        # Thread values - more sensitive, use stronger encryption
        return encrypt_sensitive(data)
    else:
        return encrypt_standard(data)

Model/Field May Differ Between Encrypt and Decrypt

Data encrypted with one (model, field) pair is not guaranteed to be decrypted with the same pair. The server performs SQL JSONB merges that can move encrypted values between models (e.g., cron metadata → run metadata). Your decryption logic must handle data regardless of the ctx.model or ctx.field values at decrypt time.

Safe: Use ctx.model/ctx.field for logging or metrics only.

Safe: Encrypt different keys based on ctx.field, but use a single decrypt handler that decrypts any value with the encrypted prefix (and passes through plaintext unchanged):

ENCRYPTED_PREFIX = "enc:"

@my_encryption.encrypt.json
async def encrypt_json(ctx: EncryptionContext, data: dict) -> dict:
    # Encrypt different keys depending on the field
    if ctx.field == "context":
        keys_to_encrypt = {"api_key", "secret_token"}
    else:
        keys_to_encrypt = {"email", "ssn"}
    return {
        k: ENCRYPTED_PREFIX + encrypt(v) if k in keys_to_encrypt else v
        for k, v in data.items()
    }

@my_encryption.decrypt.json
async def decrypt_json(ctx: EncryptionContext, data: dict) -> dict:
    # Decrypt ANY value with the prefix, regardless of model/field
    return {
        k: decrypt(v[len(ENCRYPTED_PREFIX):])
           if isinstance(v, str) and v.startswith(ENCRYPTED_PREFIX)
           else v
        for k, v in data.items()
    }

Unsafe: Using different encryption keys or algorithms based on ctx.model/ctx.field will cause decryption failures.

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