Hallucination Attacks in Adonisjs with Api Keys

Hallucination attacks in AdonisJS when API keys are involved occur when an application exposes key-sensitive behavior or allows indirect inference about valid keys through observable responses. In AdonisJS, API keys are commonly used to authenticate requests to external services or to gate internal endpoints. If key validation logic leaks information—such as returning different HTTP statuses or timing differences based on whether a key is malformed versus valid—an attacker can iteratively guess keys or deduce their structure.

A concrete scenario: an AdonisJS route that authenticates a request by comparing a provided API key against stored values may be vulnerable if it does not use constant-time comparison. An attacker can send many crafted requests and measure response times to perform a timing side-channel, inferring when a prefix of the key is correct. This is a form of hallucination where the system indirectly reveals information through behavior rather than explicit errors, enabling key enumeration without direct access to the key storage.

Another vector involves introspection or debug endpoints that, when authenticated with a valid key, return details about the key’s metadata or associated scopes. If such endpoints do not enforce strict authorization and rate limiting, an authenticated attacker can probe the API surface to map key capabilities, effectively hallucinating a broader access model than intended. This is particularly risky when keys embed tenant or user identifiers that should remain opaque; reflection of those identifiers in responses can aid privilege escalation or tenant hopping.

Input validation gaps compound the issue. AdonisJS applications that accept API keys via headers or query parameters and pass them unchecked to downstream services may open SSRF or injection paths. For example, a key that contains newline characters or encoded payloads might be forwarded to an internal HTTP client, enabling request smuggling or header injection. The hallucination here is that the key is treated as opaque data when, in practice, its structure is interpreted by downstream parsers, creating an implicit trust boundary violation.

LLM/AI security considerations also apply if an AdonisJS service generates or consumes token usage reports or completion data tied to a key. Without output validation, an attacker might craft prompts that cause key-related information to be reflected in LLM responses, leading to inadvertent leakage through generated text. This aligns with the broader class of hallucination attacks where indirect outputs reveal sensitive configuration details rather than explicit errors.

Remediation centers on consistent, side-channel-resistant validation, strict input handling, and scoping controls. Use constant-time comparison for key checks, avoid exposing metadata in responses, and enforce strict allowlists for key formats.

// config/env.ts
export const apiKeyHeader = 'X-API-Key';

// start/hooks.ts
import { HttpContextContract } from '@ioc:Adonis/Core/HttpContext'
import { schema, rules } from '@ioc:Adonis/Core/Validator'
import { ApiKey } from 'App/Models/ApiKey'
import { logger } from 'App/Helpers/logger'

// Validate API key presence and format before route handling
export const validateApiKey = async (ctx: HttpContextContract) => {
  const apiSchema = schema.create({
    api_key: schema.string({ trim: true }, [
      rules.regex(/^[A-Z0-9]{32,64}$/), // strict alphanumeric, length-limited
      rules.exists({ table: ApiKey.table, column: 'keyHash' }), // hashed lookup
    ]),
  })

  try {
    const payload = await ctx.validate({ schema: apiSchema, normalize: true, messages: { 'regex:invalid': 'Invalid key format', 'exists:missing': 'Unauthorized' } })
    ctx.params.apiKey = payload.api_key
  } catch (error) {
    logger.warn('API key validation failed', { path: ctx.request.url(), error: error.message })
    ctx.response.unauthorized({ error: 'Unauthorized' })
  }
}

Use a constant-time comparison when checking hashed keys to prevent timing leaks. AdonisJS’s built-in hashing utilities align with this approach; avoid manual string equality on raw keys.

// app/Helpers/auth.ts
import { Hmac } from '@ioc:Adonis/Addons/Hmac'
import { ApiKey } from 'App/Models/ApiKey'

export class ApiKeyAuth {
  public static async verify(rawKey: string, storedHash: string): Promise<boolean> {
    // Use HMAC-based comparison on the hashed representation
    const digest = Hmac.make(rawKey, process.env.API_KEY_SALT!, 'sha256')
    // Constant-time check via timing-safe compare
    return await Hmac.verify(digest, storedHash, process.env.API_KEY_SALT!)
  }
}

Scope keys to specific permissions and tenants, and never reflect key material or derived metadata in responses. Enforce rate limits per key to mitigate brute-force attempts.

// start/routes.tsnimport Route from '@ioc:Adonis/Core/Route'
import { validateApiKey } from 'App/Hooks/validateApiKey'

Route.group(() => {
  Route.get('/internal/reports', async ({ params, response }) => {
    // Key already validated via hook; ensure scoping
    const reports = await Report.query().where('tenantId', params.tenantId).preload('schema')
    return response.ok({ data: reports })
  }).middleware(['validateApiKey', 'rateLimit'])
}).prefix('api/v1')

For middleware-based enforcement, define a rate limiter keyed by the API key identifier to prevent abuse without exposing key validity through timing or status differences.

// start/kernel.ts
import { ExceptionHandler } from '@ioc:Adonis/Core/ExceptionHandler'
import { RateLimiter } from '@ioc:Adonis/Addons/RateLimiter'

const limiter = new RateLimiter({
  duration: 60, // seconds
  max: 100,     // requests per key per window
  identifier: (ctx) => ctx.params.apiKey || ctx.request.headers().apikey,
})

export default class Kernel extends HttpServerKernel {
  public async handle(request: HttpContextContract['request'], response: HttpContextContract['response']) {
    await limiter.check(request)
    return super.handle(request, response)
  }
}

Audit and rotate keys regularly, and prefer short-lived tokens where feasible. Combine these practices with the framework’s native validation and hashing features to reduce the attack surface associated with API keys in AdonisJS.