Formula Injection in Adonisjs with Mutual Tls

Formula Injection occurs when an attacker can control part of a formula or expression that is later evaluated by the application or an integrated spreadsheet engine. In Adonisjs, this typically manifests when user input is used to construct values that are written to exported spreadsheets (e.g., via packages that generate XLSX or CSV) or interpreted by downstream services that evaluate expressions. When Mutual Transport Layer Security (Mutual TLS) is in use, the channel between the client and server is strongly authenticated and encrypted, which may create a false sense of security. Mutual TLS ensures that both client and server present valid certificates, but it does not validate the content of requests. As a result, an authenticated client—such as a partner service or an internal tool—can submit payloads containing malicious formula syntax that the Adonisjs application processes without sanitization.

Consider an endpoint in Adonisjs that accepts financial data and generates a spreadsheet for reconciliation. If the request body includes fields like adjustmentFactor or referenceCell, and these values are directly interpolated into a formula (e.g., =SUM(A1, {userValue})) without validation, an attacker can inject references to sensitive cells, external links, or even execute side-effect functions when the file is opened in a spreadsheet application. Common attack patterns include referencing malicious remote resources via HYPERLINK or using semicolons to chain expressions that trigger unintended behavior in the consuming application. Because Mutual TLS often automates certificate management, teams may overlook input validation, assuming that authenticated traffic is inherently safe. This assumption is dangerous: the authentication provided by Mutual TLS operates at the transport layer and does not constrain what authenticated clients are allowed to submit.

The risk is compounded when Adonisjs integrations involve LLM-assisted data processing or when generated files are consumed by automated pipelines. For example, an attacker could inject a formula that references external URLs, causing the spreadsheet application to make unauthorized network calls when opened, leading to information exposure or SSRF-like effects within the context of the document. Another scenario involves numeric or date-based injections that skew analytics or reporting, leading to incorrect business decisions. Because the vulnerability arises from the combination of user-controlled data and formula evaluation—not from the TLS setup—the presence of Mutual TLS does not mitigate the need for strict input validation, output encoding, and schema enforcement. Adonisjs developers should treat any data used in computed fields as untrusted, regardless of the strength of the transport security.

Remediation focuses on ensuring that Mutual TLS is correctly configured while also addressing input validation and output handling specific to formula generation. First, verify that your Adonisjs server is requesting and validating client certificates. In a typical Node.js HTTPS setup used by Adonisjs, you configure the server to require client certificates and validate them against a trusted CA. Below is a realistic example of creating an HTTPS server with Mutual TLS in an Adonisjs application using the built-in https module and integrating it with the framework’s server bootstrap.

const fs = require('fs');
const https = require('https');
const { Ignitor } = require('@adonisjs/ignitor');

const server = https.createServer({
  key: fs.readFileSync('path/to/server-key.pem'),
  cert: fs.readFileSync('path/to/server-cert.pem'),
  ca: fs.readFileSync('path/to/ca-cert.pem'),
  requestCert: true,
  rejectUnauthorized: true,
}, async (req, res) => {
  // Allow Adonisjs to handle the request
  await Ignitor.invokeForHttp(req, res);
});

server.listen(3333, () => {
  console.log('Server running on port 3333 with Mutual TLS');
});

On the client side, ensure that each request presents a valid certificate signed by the same CA. For example, when using axios or native https clients, configure the agent with the client certificate and key. This prevents unauthorized clients from establishing TLS connections, but again, this does not protect against formula injection from authorized clients.

To mitigate formula injection, apply strict validation to any user-supplied data that may influence spreadsheet content. Use a validation library or custom rules to ensure that numeric fields contain only numbers, string fields conform to expected patterns, and cell references are limited to safe ranges. For example, when generating CSV output, avoid constructing formulas dynamically from raw input; instead, write raw values and use spreadsheet features like defined names or lookup tables separately. If you must support formula generation, sanitize inputs by whitelisting allowed characters and rejecting references to external links or special syntax such as HYPERLINK, EVALUATE, or semicolon-separated expressions.

Finally, integrate middleBrick into your workflow to detect misconfigurations and injection risks automatically. Using the CLI, you can run middlebrick scan <url> to test authenticated endpoints and identify weaknesses in how your Adonisjs API handles data used in formulas. The GitHub Action can enforce security thresholds in CI/CD, while the Web Dashboard helps track improvements over time. These tools complement secure coding practices by providing continuous visibility into the API surface exposed by Mutual TLS configurations and formula-related endpoints.