Api Rate Abuse in Strapi with Dynamodb

Strapi is a headless CMS that often uses DynamoDB as a storage backend in production deployments. When rate limiting is not enforced at the API gateway or application layer, an unauthenticated or weakly authenticated endpoint can be targeted with rapid, high-volume requests. This can exhaust DynamoDB provisioned read capacity units (RCUs), trigger throttling responses, or amplify costs due to on-demand billing. Strapi’s default GraphQL and REST endpoints may expose collection data without built-in strict request ceilings.

An attacker can perform a low-and-slow rate abuse that avoids simple IP-based thresholds. By using distributed sources or rotating user agents, they can issue thousands of queries per minute against endpoints such as /api/articles or GraphQL queries that resolve to DynamoDB scan operations with FilterExpression patterns that are inefficient. DynamoDB’s eventual consistency and pagination (e.g., using LastEvalKey) allow an attacker to paginate through large datasets, increasing load without triggering obvious spikes in per-request latency.

The risk is compounded when the DynamoDB table uses sparse indexes or secondary indexes that are less optimized, causing the queries to consume more capacity than expected. In a black-box scan, middleBrick’s Rate Limiting check flags missing or inconsistent rate controls across HTTP methods and authenticated vs unauthenticated paths. If Strapi services are exposed directly to the internet without an API gateway that provides token-bucket or leaky-bucket enforcement, DynamoDB can become a cost amplification vector and a vector for denial-of-service via consumed read capacity.

middleBrick’s scan would identify missing per-endpoint rate limits, lack of burst control, and potentially unsafe query patterns that map to the OWASP API Top 10:2023 –2023.A05:2023 Security Misconfiguration and A07:2023 Identification and Authentication Failures. Remediation focuses on introducing request-level throttling, validating filter inputs to avoid full table scans, and monitoring DynamoDB consumed capacity metrics in tandem with API response codes.

To mitigate rate abuse, implement a two-layer defense: infrastructure-level throttling (API gateway or load balancer) and application-level validation in Strapi. For DynamoDB, ensure queries use indexed attributes, enforce pagination limits, and avoid scan operations in production paths. Below are specific code examples for a Strapi custom controller that safely queries DynamoDB with pagination and query constraints.

Example 1: Parameterized query with index use and limit

Use a KeyConditionExpression on a Global Secondary Index (GSI) to avoid scans and enforce a page size ceiling. This reduces consumed RCUs and prevents unbounded queries.

const AWS = require('aws-sdk');
const dynamo = new AWS.DynamoDB.DocumentClient({
  region: process.env.AWS_REGION,
  maxRetries: 1,
  httpOptions: { timeout: 5000 }
});

module.exports = {
  async findPublished(ctx) {
    const { status = 'published', limit = 20, lastKey } = ctx.query;
    const safeLimit = Math.min(Number(limit), 50); // enforce ceiling
    const params = {
      TableName: process.env.DYNAMO_TABLE,
      IndexName: 'status-date-index',
      KeyConditionExpression: 'status = :status',
      ExpressionAttributeValues: { ':status': status },
      Limit: safeLimit,
      ScanIndexForward: false
    };
    if (lastKey) {
      params.ExclusiveStartKey = JSON.parse(Buffer.from(lastKey, 'base64').toString());
    }
    try {
      const data = await dynamo.query(params).promise();
      const nextKey = data.LastEvaluatedKey
        ? Buffer.from(JSON.stringify(data.LastEvaluatedKey)).toString('base64')
        : null;
      ctx.body = { data: data.Items, nextKey };
    } catch (err) {
      ctx.throw(500, `DynamoDB error: ${err.message}`);
    }
  }
};

Example 2: Guard against expensive filters and enforce tenant isolation

If multi-tenant data is stored in DynamoDB, include a partition key filter derived from the authenticated context (e.g., userId or orgId) to prevent horizontal data enumeration and reduce RCUs used by unintended queries.

const validateAndBuildParams = (userTenantId, incoming) => {
  const filter = incoming.filters || {};
  // Ensure tenantId is always part of the key condition
  if (!filter.tenantId) {
    throw new Error('Missing tenant filter');
  }
  if (filter.tenantId !== userTenantId) {
    throw new Error('Cross-tenant access denied');
  }
  return {
    TableName: process.env.DYNAMO_TABLE,
    KeyConditionExpression: 'tenantId = :tid AND timestamp >= :since',
    ExpressionAttributeValues: {
      ':tid': userTenantId,
      ':since': new Date(Date.now() - 7 * 24 * 60 * 60 * 1000).toISOString()
    },
    Limit: Math.min(Number(incoming.limit) || 10, 100)
  };
};

module.exports = {
  async listEvents(ctx) {
    const params = validateAndBuildParams(ctx.state.user.tenantId, ctx.query);
    const data = await dynamo.query(params).promise();
    ctx.body = data.Items;
  }
};

Example 3: Middleware-level rate tracking with in-memory token bucket

Use a lightweight in-memory store for development or a Redis-backed bucket in production to enforce per-IP or per-api-key limits before requests hit DynamoDB. This complements, but does not replace, infrastructure throttling.

const rateLimit = require('rate-limiter-flexible');
const { RateLimiterRedis } = rateLimit;
const redisClient = require('redis').createClient({ url: process.env.REDIS_URL });
const limiter = new RateLimiterRedis({
  storeClient: redisClient,
  keyPrefix: 'middlebrick_rl',
  points: 100, // 100 requests
  duration: 60 // per 60 seconds
});

module.exports = async function rateCheck(ctx, next) {
  const identifier = ctx.ip;
  try {
    await limiter.consume(identifier);
    await next();
  } catch (rejErr) {
    ctx.throw(429, 'Too many requests');
  }
};

Combine these practices: require indexed queries, cap page sizes, validate tenant context, and enforce rate limits at multiple layers. This reduces the likelihood that unauthenticated or low-privilege abuse can overload DynamoDB or expose excessive data through Strapi endpoints.