Llm Data Leakage in Fiber with Hmac Signatures

When building LLM-enabled endpoints in Fiber, developers sometimes use HMAC signatures to verify the origin of incoming requests or to sign outbound data. If the application embeds sensitive information such as user identifiers, internal API keys, or session data inside the payload and then signs it with HMAC, a data leakage risk arises if the signed data is later logged, echoed, or returned in LLM responses. middleBrick’s LLM/AI Security checks include system prompt leakage detection and output scanning for API keys and PII, which can surface scenarios where HMAC-signed payloads inadvertently expose secrets through the model’s output or through debug endpoints that echo the signed value.

For example, if a Fiber route deserializes an HMAC-signed JSON body and passes user-controlled fields into an LLM prompt without careful sanitization, the signature may be treated as part of the prompt context. Attackers can use prompt injection techniques—such as requesting the system prompt or instructing the model to exfiltrate data—to coax the model into repeating the signed payload or parts of it. Because the signature may contain user-specific metadata or act as a bearer-like token, this constitutes both a data exposure and an authentication bypass concern. middleBrick’s active prompt injection testing (five sequential probes including system prompt extraction and data exfiltration) is designed to uncover these multi-step risks where authentication logic intersects with LLM output handling.

Another angle is server-side logging or error handling in Fiber middleware. If an HMAC signature is included in request logs and those logs are later consumed by an LLM tool or exposed through a debug route, the signature can become an unintended data channel. The LLM endpoint might inadvertently echo log entries in completions, especially if the application uses the model to summarize or analyze request data. Because HMAC signatures can resemble tokens or keys, their presence in model outputs violates data exposure controls. middleBrick’s output scanning for API keys and PII is specifically invoked to detect such leakage in LLM responses, flagging patterns that match known secret formats even when they are wrapped in signed structures.

Additionally, if the application uses the same HMAC key across multiple endpoints or over long time windows, a compromised signature can be replayed to induce improper authorization or to supply tainted data to the LLM. This intersects with BOLA/IDOR and BFLA checks, where insecure direct object references or privilege escalation may be chained with LLM interactions. The scanner cross-references OpenAPI/Swagger definitions with runtime findings, so if an endpoint that accepts HMAC-signed input also exposes an LLM-compatible route, the correlation can highlight insecure design patterns that amplify data leakage risk.

middleBrick’s LLM/AI Security capability is unique in actively probing for these conditions, rather than relying solely on static scans. By testing prompt injection paths and scanning outputs for sensitive content, it helps identify subtle channels where HMAC-signed data can escape the intended boundary and appear in model-generated text. This is especially important in Fiber applications that combine high-throughput routing with rich LLM integrations, because the framework’s minimal conventions can inadvertently simplify the attack surface if security controls are not explicitly coordinated.

To mitigate data leakage when using HMAC signatures in Fiber, treat the signature as sensitive data and ensure it is never reflected in LLM prompts, logs, or responses. Below are concrete remediation patterns and code examples for a Fiber application that uses HMAC to validate incoming requests.

// Secure HMAC verification in Fiber without leaking signature to LLM
const crypto = require('crypto');
const express = require('express'); // Fiber-compatible pattern

function verifySignature(body, signature, secret) {
  const hmac = crypto.createHmac('sha256', secret);
  hmac.update(JSON.stringify(body));
  const expected = hmac.digest('hex');
  return crypto.timingSafeEqual(Buffer.from(signature), Buffer.from(expected));
}

const app = require('express')();
const SECRET = process.env.HMAC_SECRET;

app.post('/api/llm-task', (req, res) => {
  const provided = req.get('X-Signature');
  if (!provided) {
    return res.status(401).json({ error: 'Missing signature' });
  }
  const isValid = verifySignature(req.body, provided, SECRET);
  if (!isValid) {
    return res.status(403).json({ error: 'Invalid signature' });
  }

  // Explicitly strip signature before LLM interaction
  const { signature, ...safeBody } = req.body;
  // safeBody now excludes the HMAC signature
  // Pass safeBody to LLM prompt builder
  const prompt = buildPrompt(safeBody);
  const llmResponse = callLLM(prompt);
  res.json({ result: llmResponse });
});

function buildPrompt(data) {
  // Do not include raw signature; include only necessary business fields
  return `Process the following data securely: ${JSON.stringify(data)}`;
}

async function callLLM(prompt) {
  // Placeholder for actual LLM call
  return 'processed result';
}

Key practices demonstrated:

• Verify HMAC before any LLM interaction and remove the signature from the data passed to the model.
• Do not log the full signed payload; if logging is required, redact or hash the signature value.
• Use crypto.timingSafeEqual to prevent timing attacks on signature comparison.
• Scope the HMAC secret per environment and rotate periodically; avoid sharing the same secret across unrelated services.

If you use the middleBrick CLI to scan this endpoint, the tool will flag findings related to authentication, data exposure, and LLM output risks, providing prioritized remediation guidance. Teams on the Pro plan can enable continuous monitoring so that any regression in HMAC handling is caught before it reaches production. The GitHub Action can fail the build if the risk score exceeds the configured threshold, ensuring that insecure signature flows are blocked at CI/CD gates.