Integrity Failures in Mongodb

Integrity Failures in MongoDB APIs occur when attackers can modify, delete, or read data they shouldn't have access to. These vulnerabilities stem from improper access controls and validation in the data layer, allowing unauthorized users to manipulate database documents or collections.

The most common MongoDB integrity failure pattern involves IDOR (Insecure Direct Object Reference) vulnerabilities where API endpoints accept MongoDB ObjectIDs as parameters without proper authorization checks. For example, a user might access /api/users/60d5f9b2e4b0f3a1c8e4d2a3 and retrieve or modify another user's profile by simply changing the ObjectID in the URL.

// Vulnerable pattern - no authorization check
app.get('/api/users/:userId', async (req, res) => {
  const { userId } = req.params;
  const user = await User.findById(userId); // Anyone can access any user
  res.json(user);
});

// BOLA vulnerability - Business Logic Manipulation
app.post('/api/users/:userId/update', async (req, res) => {
  const { userId } = req.params;
  const updates = req.body;
  await User.findByIdAndUpdate(userId, updates); // No ownership verification
  res.json({ success: true });
});

Property Authorization failures occur when APIs expose sensitive fields that should be filtered out. MongoDB's flexible schema allows storing complex nested objects, but APIs often return entire documents without considering which properties a user should access.

// Exposing sensitive fields
app.get('/api/users/:userId', async (req, res) => {
  const user = await User.findById(req.params.userId).select('-password');
  res.json(user); // Still exposes email, phone, address to unauthorized users
});

Another Mongodb-specific integrity issue involves improper use of aggregation pipelines. Attackers can craft queries that join unauthorized collections or project sensitive fields through pipeline stages.

// Vulnerable aggregation - no access control
app.get('/api/users/:userId/orders', async (req, res) => {
  const pipeline = [
    { $match: { userId: req.params.userId } },
    { $lookup: { from: 'orders', localField: '_id', foreignField: 'userId', as: 'orders' } }
  ];
  const result = await User.aggregate(pipeline);
  res.json(result); // Any user can query any other user's orders
});

Detecting integrity failures in MongoDB APIs requires examining both the API layer and the database interactions. middleBrick's black-box scanning approach tests these vulnerabilities without requiring access to source code or database credentials.

The scanner identifies IDOR vulnerabilities by systematically testing ObjectID permutations and analyzing response patterns. For MongoDB, this means testing valid ObjectIDs that differ by one character, invalid ObjectIDs, and ObjectIDs from different collections to see if the API exposes data it shouldn't.

# Using middleBrick CLI to scan for integrity failures
middlebrick scan https://api.example.com --path /api/users/{id} --method GET

# Scan with specific MongoDB patterns
middlebrick scan https://api.example.com --path /api/users/{id}/orders --method GET --test idor --test bolav2

Property authorization detection involves analyzing API responses for sensitive fields that shouldn't be exposed. middleBrick checks for patterns like email, phone, ssn, creditCard, and other PII fields that appear in responses without proper authorization.

For aggregation pipeline vulnerabilities, the scanner tests whether API endpoints accept arbitrary pipeline stages or allow joining collections that should be isolated. This includes testing for MongoDB-specific operators like $graphLookup, $facet, and $lookup that can be abused to access unauthorized data.

middleBrick's LLM/AI security features are particularly relevant for MongoDB APIs that use AI/ML services. The scanner tests for system prompt leakage and prompt injection vulnerabilities that could expose database credentials or allow attackers to manipulate AI responses to reveal sensitive data stored in MongoDB.

Real-world detection examples include:

• Testing if /api/users/000000000000000000000000 (min ObjectID) returns a valid response
• Checking if /api/users/ffffffffffffffffffffffff (max ObjectID) exposes data
• Verifying that aggregation endpoints reject unauthorized collection joins
• Ensuring property filtering removes sensitive fields before response serialization

Remediating integrity failures in MongoDB APIs requires implementing proper authorization checks at the database query level. The most effective approach uses MongoDB's native features combined with application-level access control.

For IDOR prevention, always verify that the authenticated user owns the resource being accessed. Use MongoDB's population features to join user data with ownership information.

// Secure pattern with ownership verification
app.get('/api/users/:userId', async (req, res) => {
  const { userId } = req.params;
  const currentUser = req.user; // Authenticated user from JWT/decode
  
  // Verify ownership before accessing data
  if (currentUser.id !== userId) {
    return res.status(403).json({ error: 'Access denied' });
  }
  
  const user = await User.findById(userId).select('-password -ssn -creditCard');
  res.json(user);
});

// Using MongoDB's $match for authorization
app.get('/api/users/:userId/orders', async (req, res) => {
  const { userId } = req.params;
  const currentUser = req.user;
  
  // Verify user owns these orders
  const orders = await Order.find({
    userId: userId,
    owner: currentUser.id
  }).select('-paymentDetails -customerNotes');
  
  res.json(orders);
});

Property authorization should use MongoDB's projection capabilities to explicitly exclude sensitive fields. Create reusable projection objects for different user roles.

const projections = {
  user: '-password -ssn -creditCard -address',
  admin: '-password', // Admins see more
  self: '' // User sees own data
};

app.get('/api/users/:userId', async (req, res) => {
  const { userId } = req.params;
  const currentUser = req.user;
  
  // Determine projection based on role and ownership
  let projection = projections.user;
  if (currentUser.role === 'admin') projection = projections.admin;
  if (currentUser.id === userId) projection = projections.self;
  
  const user = await User.findById(userId).select(projection);
  res.json(user);
});

For aggregation pipeline security, validate pipeline stages against a whitelist and ensure all joins respect data ownership boundaries.

// Secure aggregation with validation
app.get('/api/users/:userId/reports', async (req, res) => {
  const { userId } = req.params;
  const currentUser = req.user;
  
  // Only allow specific pipeline stages
  const allowedPipeline = [
    { $match: { userId: userId, owner: currentUser.id } },
    { $lookup: { from: 'reports', localField: '_id', foreignField: 'userId', as: 'reports' } },
    { $project: { reports: 1, _id: 0 } }
  ];
  
  const result = await User.aggregate(allowedPipeline);
  res.json(result);
});

Implement comprehensive input validation for all ObjectIDs and query parameters to prevent injection attacks that could bypass authorization.

const isValidObjectId = mongoose.Types.ObjectId.isValid;

app.use((req, res, next) => {
  const { userId } = req.params;
  if (userId && !isValidObjectId(userId)) {
    return res.status(400).json({ error: 'Invalid ID format' });
  }
  next();
});