Broken Authentication in Hanami with Dynamodb

When Hanami applications interact with Amazon DynamoDB, broken authentication often stems from insufficient verification of identity and session integrity before issuing or accepting DynamoDB requests. Unlike traditional SQL stores, DynamoDB is a schema-less NoSQL service; this flexibility can lead to modeling decisions that inadvertently weaken authentication controls. For example, storing user records without enforcing a strict partition key design or missing secondary indexes for credential lookup can force the application to perform inefficient scans or accept ambiguous results, which may allow an attacker to escalate privileges or bypass ownership checks.

A concrete risk pattern is when a Hanami service retrieves a user item by a user identifier that is not properly bound to the request context. If the identifier is derived from an unchecked client-supplied value (e.g., a path parameter or JSON body) and directly used as the DynamoDB key, an attacker can substitute another user’s identifier to access or modify their data. This is a classic Broken Object Level Authorization (BOLA) issue, but it is amplified by DynamoDB’s behavior: a missing conditional check or an incomplete key specification can result in reading or updating an item that should be inaccessible.

Another specific concern involves authentication tokens or session metadata stored in DynamoDB. If items representing sessions or API keys lack proper Time to Live (TTL) configuration or are not removed after logout, stale credentials can be reused. Hanami middleware that validates tokens by querying DynamoDB must ensure the query uses exact key expressions rather than scans and that responses are carefully inspected for absence of data, rather than assuming a missing item implies an invalid request. Without these safeguards, an attacker can reuse old tokens or exploit weak token revocation logic.

Additionally, misconfigured IAM policies associated with the DynamoDB endpoint can unintentionally broaden the permissions available to the Hanami application. Overly permissive read/write grants on user-specific items can allow a compromised component to act on behalf of other users. Since Hanami does not enforce permissions at the framework level, developers must implement explicit checks and use conditional writes to ensure that operations are constrained to the authenticated subject’s own data. In practice, this means combining Hanami’s authorization patterns with tightly scoped DynamoDB access policies and application-level ownership verification on every request.

Remediation focuses on precise key design, strict ownership checks, and safe query patterns when using DynamoDB with Hanami. Always use exact key expressions to fetch items, avoid scans, and enforce that the authenticated subject matches the item’s ownership attribute. Below are concrete, syntactically correct examples for a Hanami service that manages user profiles stored in DynamoDB.

require 'aws-sdk-dynamodb'
require 'securerandom'

# Configuration (keep credentials out of code; use IAM roles or environment variables)
dynamodb = Aws::DynamoDB::Client.new(region: 'us-east-1')

# Create a user item with a composite key for ownership and a condition to avoid overwrites
def create_user(dynamodb, user_id, email)
  dynamodb.put_item(
    table_name: 'users',
    item: {
      pk: { s: "USER##{user_id}" },
      sk: { s: "PROFILE" },
      email: { s: email },
      created_at: { n: Time.now.to_i.to_s }
    },
    condition_expression: 'attribute_not_exists(pk)'
  )
rescue Aws::DynamoDB::Errors::ConditionalCheckFailedException
  raise 'User already exists'
end

# Retrieve a user item using exact keys, ensuring the authenticated user_id matches the pk
# The Hanami request context should supply the user_id after authentication
# DO NOT allow the client to specify the pk directly; map it server-side.
def get_user_profile(dynamodb, authenticated_user_id)
  pk = "USER##{authenticated_user_id}"
  resp = dynamodb.get_item(
    table_name: 'users',
    key: {
      pk: { s: pk },
      sk: { s: 'PROFILE' }
    }
  )
  item = resp.item
  raise 'Not found' if item.empty?
  item
end

# Update user email with an ownership check: ensure the pk matches the authenticated subject
# and use a conditional update to prevent race conditions.
def update_user_email(dynamodb, authenticated_user_id, new_email)
  pk = "USER##{authenticated_user_id}"
  dynamodb.update_item(
    table_name: 'users',
    key: {
      pk: { s: pk },
      sk: { s: 'PROFILE' }
    },
    update_expression: 'SET email = :val',
    expression_attribute_values: { ':val' => { s: new_email } },
    condition_expression: 'attribute_exists(pk)'
  )
rescue Aws::DynamoDB::Errors::ConditionalCheckFailedException
  raise 'Item changed concurrently or not found'
end

# Implement session cleanup and TTL to mitigate reused credentials
# Store sessions with a TTL attribute and query by exact session key.
def create_session(dynamodb, session_token, user_id, expires_at)
  dynamodb.put_item(
    table_name: 'sessions',
    item: {
      pk: { s: "SESSION##{session_token}" },
      user_id: { s: user_id },
      expires_at: { n: expires_at.to_i.to_s }
    },
    time_to_live: { attribute_name: 'expires_at', enabled: true }
  )
end

def get_session_user(dynamodb, session_token)
  resp = dynamodb.get_item(
    table_name: 'sessions',
    key: {
      pk: { s: "SESSION##{session_token}" },
      sk: { s: 'METADATA' }
    }
  )
  item = resp.item
  return nil if item.empty?
  item['user_id']['s']
end

In addition to code fixes, apply these DynamoDB-specific practices: enable point-in-time recovery for critical tables where modification detection is required, use IAM policies that restrict actions to items whose pk/sk match the authenticated subject (using conditionals with aws:PrincipalArn or context keys), and prefer Query with an index key over Scan. For Hanami, integrate these checks into your service objects or policy classes so that every DynamoDB request is preceded by explicit ownership validation. This approach aligns with findings mapped to frameworks such as OWASP API Top 10 and helps you use middleBrick to detect misconfigurations before they are exposed in production scans.