Api Scraping in Adonisjs

Api scraping occurs when unauthorized clients repeatedly consume Adonisjs endpoints for data harvesting or resource exhaustion. In Adonisjs, this often appears through unprotected GET /api/v1/users routes that return paginated user lists without rate limiting or authentication. Attackers may use headless browsers like Puppeteer or curl scripts to bypass client-side validation, exploiting Adonisjs's default lack of request throttling. Common patterns include scraping of /api/v1/posts for content aggregation or /api/v1/comments for social engineering reconnaissance. Adonisjs's built-in Request object does not enforce rate limits by default, making it vulnerable to high-volume scraping without explicit guards. Scanning with middleBrick identifies scraping risks through anomaly detection in response size and request frequency.

Specific Adonisjs code paths where scraping manifests include controller methods that query databases directly without pagination constraints. For example, a controller action like public async index({ request }) that uses User.query().fetch() without limiting results can return thousands of records in a single call. Attackers may target endpoints like /api/v1/orders to harvest order histories, triggering high CPU usage on the server. Another pattern involves scraping of GraphQL endpoints if implemented via adonisjs-lucid-graphql, where introspection queries expose all schema fields. Scanning tools like middleBrick detect these patterns by analyzing OpenAPI specs and runtime behavior to flag endpoints returning excessive data without authentication, mapping findings to OWASP API Top 10 category B1:2023 - Broken Object Level Authorization.

Detecting API scraping in Adonisjs requires monitoring for anomalous request patterns and insecure data exposure. middleBrick scans Adonisjs APIs by submitting URLs and analyzing response behavior without authentication. It checks for unrate-limited endpoints that return large payloads, such as Response.send(User.all()) in controllers. Scanning also identifies missing @csrf protection on state-changing endpoints and evaluates whether GraphQL schemas expose sensitive fields. During a scan, middleBrick detects if an endpoint like /api/v1/products returns more than 500 items in under 3 seconds, triggering a scraping risk alert. The tool cross-references OpenAPI responses definitions with actual response sizes to flag potential scraping vectors. For example, if a spec defines schema: { type: array, items: { $ref: '#/components/schemas/Product' } } but runtime responses exceed 10KB, middleBrick flags this as suspicious. Findings are mapped to OWASP API Top 10 B2:2023 - Broken Access Control when authorization checks are absent. The CLI tool can be used to scan staging environments before deployment, ensuring scraping risks are caught early.

middleBrick's scanning process evaluates 12 security checks in parallel, including Input Validation and Rate Limiting. It does not require credentials but analyzes unauthenticated behavior to detect scraping risks. For Adonisjs applications using JWT, middleBrick checks if protected routes like /api/v1/session are accessible without tokens. The scan also identifies missing Access-Control-Allow-Origin headers that could enable cross-origin scraping. Findings include severity ratings, remediation guidance, and category mappings to frameworks like OWASP API Top 10. This approach ensures that even complex Adonisjs setups with middleware chains are evaluated for scraping vulnerabilities without internal configuration.

Remediating API scraping in Adonisjs involves implementing rate limiting, pagination, and authentication using native framework features. To prevent excessive data exposure, always use limit() and paginate() methods when querying databases. For example, replace User.query().fetch() with User.query().paginate(request.page()) to enforce result limits. Add @rateLimiter middleware to high-risk routes like Route.get('api/v1/users', 'UserController.index') to restrict requests to 10 per minute per IP. Configure the limiter in config/ratelimiter.ts with a tiered approach: const limiter = new SimpleRateLimiter({ maxRequests: 10, duration: 60 }). Ensure sensitive endpoints require authentication by adding auth' middleware to routes in config/auth.js. For GraphQL, use @auth directives to restrict field access. Scanning with middleBrick after these changes confirms reduced scraping risk by verifying smaller response sizes and proper rate limiting. Always validate OpenAPI specs to ensure responses include schema with maximum item counts, preventing unintended data leakage.

Code examples for secure Adonisjs controllers include:

public async index({ request }) {   const users = await User.query().paginate(request.page() || 1, 20)   return users

To implement rate limiting:

Route.get('api/v1/users', 'UserController.index').middleware('rateLimiter')

Configure rateLimiter as:

const limiter = new SimpleRateLimiter({ maxRequests: 15, duration: 60 })   Route.middleware('rateLimiter')

These practices align with OWASP API Top 10 recommendations for B4:2023 - Unrestricted Rate Limiting and prevent scraping by enforcing controlled access patterns. middleBrick can verify these fixes by rescanning the endpoint and confirming reduced risk scores.