Type Confusion in Fastapi with Dynamodb

Type confusion in a FastAPI application that uses DynamoDB typically arises when the API accepts user input to determine how data is deserialized or mapped into Python types before values are sent to DynamoDB. Because DynamoDB stores typed attributes (strings, numbers, booleans, binary, lists, maps), a FastAPI endpoint that dynamically constructs item shapes or merges user-controlled fields can misinterpret an attacker-supplied type indicator, leading to unexpected attribute interpretations.

Consider a FastAPI endpoint that accepts a JSON payload describing an item to store in a DynamoDB table. If the endpoint uses a field such as attribute_type to decide how to cast or decode a value, and that field is directly bound to user input without strict validation, an attacker can change the declared type to cause the application to treat data as a different Python type. For example, a field expected to be a number might be supplied as a string, a list, or even a map, and downstream code that assumes a specific type may process it incorrectly. This can lead to logic bypasses, injection through type-coercion paths, or unsafe operations when the runtime type differs from the expected schema.

When the malformed or unexpected data is written to DynamoDB, the stored representation may still appear valid to the service, but the consuming application can later misread the item. An attacker might exploit this by crafting requests that cause the server to store a value under a different attribute name, store a list where a scalar is expected, or store a map that triggers deeper traversal bugs in the application. In addition, if the FastAPI route merges user-supplied updates into an existing DynamoDB item using a generic update mechanism (such as a partial update with attribute path expressions), type confusion can allow an attacker to modify fields that should be immutable or to bypass authorization checks that rely on type-specific comparisons.

Because middleBrick scans test unauthenticated attack surfaces and include checks such as Input Validation and Property Authorization, it can surface indicators that user-controlled data influences how items are constructed or interpreted before being sent to DynamoDB. Findings may highlight endpoints where type indicators are not enforced strictly, where deserialization logic is too permissive, or where attribute-level authorization does not account for type-based coercion. These findings do not imply that DynamoDB itself is insecure, but rather that the application layer must enforce strict type contracts and validate all input that influences how data is structured for storage and retrieval.

Remediation focuses on strict input validation, explicit type schemas, and safe construction of DynamoDB items in FastAPI. Avoid dynamic type selection based on user input, and instead use Pydantic models to enforce field types before constructing DynamoDB attribute maps.

Example of a vulnerable pattern to avoid:

from fastapi import FastAPI
import boto3

app = FastAPI()
dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('Items')

@app.post('/store/')
async def store_item(data: dict):
    # Unsafe: type indicator from user input
    attr_type = data.get('type', 'string')
    value = data['value']
    # Risk: attacker can set type to 'list' or 'map' and bypass expected handling
    item = {'id': data['id'], attr_type: value}
    table.put_item(Item=item)
    return {'status': 'ok'}

Secure alternative using Pydantic for validation and explicit mapping:

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel, Field
import boto3
from typing import Union

app = FastAPI()
dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('Items')

class ItemInput(BaseModel):
    id: str = Field(..., min_length=1)
    # Explicitly allow expected scalar types; reject unexpected structures
    string_value: Union[str, None] = None
    number_value: Union[int, float, None] = None
    bool_value: Union[bool, None] = None

@app.post('/store/')
async def store_item(input: ItemInput):
    # Build item with known attribute names and explicit types
    item = {
        'id': input.id,
        'string_value': input.string_value,
        'number_value': input.number_value,
        'bool_value': input.bool_value,
    }
    # Remove None values to avoid storing nulls unintentionally
    item = {k: v for k, v in item.items() if v is not None}
    table.put_item(Item=item)
    return {'status': 'ok', 'id': input.id}

When updates are required, use explicit attribute paths and avoid passing raw user input into expression attribute names or values. For example, with UpdateItem, define allowed attributes server-side and map user input safely:
@app.patch('/update/{item_id}')
async def update_item(item_id: str, updates: dict):
    # Whitelist updatable fields and enforce types server-side
    allowed = {'string_value': str, 'number_value': (int, float), 'bool_value': bool}
    update_expr = 'SET '
    expr_attrs = {}
    for key, val in updates.items():
        if key not in allowed:
            continue
        if not isinstance(val, allowed[key]):
            raise HTTPException(status_code=400, detail=f'Invalid type for {key}')
        attr_name = f'#{key}'
        update_expr += f'{attr_name} = :{key}, '
        expr_attrs[f':{key}'] = val
        expr_attrs[f'#{key}'] = key
    # Remove trailing comma and space
    update_expr = update_expr.rstrip(', ')
    table.update_item(
        Key={'id': item_id},
        UpdateExpression=update_expr,
        ExpressionAttributeNames=expr_attrs,
        ExpressionAttributeValues=expr_attrs
    )
    return {'status': 'updated', 'id': item_id}

These practices reduce the risk of type confusion by ensuring that the shape and types of data sent to DynamoDB are strictly controlled by server-side logic, not by unvalidated user input. This aligns with findings that may be reported by middleBrick checks such as Input Validation and Property Authorization, helping to keep the API surface predictable and resilient against malformed or malicious payloads.