Out Of Bounds Read in Chi with Dynamodb

An Out Of Bounds Read in the context of Chi using Amazon DynamoDB occurs when a query or scan retrieves data beyond the intended record set due to incorrect pagination or key-condition construction. In Chi, this typically arises when developers implement pagination manually using ExclusiveStartKey or Limit parameters without fully validating the sort key boundaries. Because DynamoDB returns items in the order defined by the key schema, an off-by-one error or incorrect continuation token can cause the client to request a page that overlaps or skips items, leading the application to read data that belongs to another partition or belongs to a different user entirely.

Consider a multi-tenant API where each tenant’s data is segregated by a partition key such as tenant_id. If a developer constructs a query using a start key derived from the last seen sort key of the previous page but does not reapply the tenant_id filter, the next page can include items from a different tenant. This is an Out Of Bounds Read because the application accesses data outside its authorized scope. In Chi, this risk is amplified when APIs are built to iterate over large datasets with nested keys, and the runtime behavior of the client library does not enforce strict boundary checks.

The vulnerability is further exposed when using DynamoDB Streams or time-based sort keys (e.g., created_at) without validating that the read index remains within the logical partition. An attacker could manipulate pagination parameters to iterate through adjacent partitions, leveraging the natural ordering of keys to read sensitive records. Because DynamoDB does not enforce row-level permissions at the storage layer, the application must correctly scope every query. If Chi-generated SDK code does not embed tenant context into key expressions, the resulting requests can traverse beyond intended boundaries, exposing data inadvertently.

In practice, this maps to OWASP API Top 10 categories such as Broken Object Level Authorization (BOLA), where insecure direct object references allow traversal across resources. The risk is not in DynamoDB itself, which is a managed service with strong isolation, but in how Chi templates generate the key expressions and pagination logic. A misconfigured index or an unchecked continuation token can silently expose adjacent records, making the data exposure appear as a benign pagination artifact during normal operation.

Remediation focuses on ensuring every query explicitly includes the partition key and validates sort key ranges before issuing the request. In Chi, you should parameterize key expressions so that tenant context is part of the condition, and never derive continuation tokens from external input without re-verifying scope.

Example: Safe paginated query with tenant isolation

const { DynamoDBClient, QueryCommand } = require("@aws-sdk/client-dynamodb");

const client = new DynamoDBClient({ region: "us-east-1" });

async function queryTenantData(tenantId, lastEvaluatedKey = null) {
  const params = {
    TableName: "AppRecords",
    KeyConditionExpression: "tenant_id = :tid AND sort_key BETWEEN :start AND :end",
    ExpressionAttributeValues: {
      ":tid": { S: tenantId },
      ":start": { S: "2024-01-01T00:00:00Z" },
      ":end": { S: "2024-12-31T23:59:59Z" }
    },
    Limit: 50,
    ExclusiveStartKey: lastEvaluatedKey || undefined
  };

  const command = new QueryCommand(params);
  const response = await client.send(command);
  return {
    items: response.Items,
    lastEvaluatedKey: response.LastEvaluatedKey || null
  };
}

module.exports = { queryTenantData };

This pattern ensures that each query is bound to a specific tenant and a bounded time window. The KeyConditionExpression includes the partition key as an exact match, preventing cross-tenant traversal. The Limit parameter controls page size, and ExclusiveStartKey is only passed if it was returned by the previous query, preserving continuity within the same logical partition.

Validating sort key boundaries before querying

function isValidSortKeyRange(start, end) {
  if (!start || !end) return false;
  const startTs = Date.parse(start);
  const endTs = Date.parse(end);
  return !isNaN(startTs) && !isNaN(endTs) && startTs <= endTs && (endTs - startTs) <= 30 * 24 * 60 * 60 * 1000; // 30 days
}

// Usage in Chi route handler
if (!isValidSortKeyRange(req.query.start, req.query.end)) {
  res.status(400).json({ error: "Invalid time range" });
  return;
}

By validating ranges on the client side before issuing DynamoDB requests, you prevent accidental reads outside expected windows. This complements server-side checks and reduces the chance of an Out Of Bounds Read due to malformed or manipulated input.

For continuous monitoring, integrate the middleBrick CLI to scan your Chi endpoints and detect insecure pagination patterns. Use the command middlebrick scan <url> to assess your public attack surface. Teams on the Pro plan can enable continuous monitoring to catch regressions early, while the GitHub Action can fail builds if a new endpoint introduces unbounded queries. These integrations help maintain secure key scoping without relying on manual review alone.