HIGH ldap injectiondynamodb

Ldap Injection in Dynamodb

How Ldap Injection Manifests in Dynamodb

LDAP injection in DynamoDB contexts typically occurs when user input is improperly incorporated into DynamoDB queries, particularly when building filter expressions or query parameters dynamically. While DynamoDB uses a different query language than LDAP, the injection patterns are analogous—malicious input can alter query logic, bypass authorization, or extract unauthorized data.

The most common DynamoDB LDAP injection pattern involves FilterExpression construction. Consider an application that builds queries like:

const email = req.query.email;
const params = {
TableName: 'Users',
FilterExpression: 'email = :email',
ExpressionAttributeValues: { ':email': email }
};
dynamodb.scan(params, callback);

If the email parameter contains special characters like parentheses or comparison operators, an attacker might manipulate the query structure. For example, submitting admin@example.com or 1=1 could potentially alter the query logic.

DynamoDB's expression syntax makes certain injection patterns more subtle. The use of begins_with, contains, and between functions in FilterExpression creates specific injection opportunities:

// Vulnerable: dynamic function construction
const searchType = req.query.type; // 'begins_with' or 'contains'
const searchTerm = req.query.term;
const params = {
TableName: 'Products',
FilterExpression: `${searchType}(#name, :term)`,
ExpressionAttributeNames: { '#name': 'name' },
ExpressionAttributeValues: { ':term': searchTerm }
};

An attacker could manipulate searchType to inject arbitrary function calls or alter the expression structure.

Another DynamoDB-specific pattern involves partition key manipulation in queries. When building KeyConditionExpression dynamically:

const userId = req.query.userId;
const orderId = req.query.orderId;
const params = {
TableName: 'Orders',
KeyConditionExpression: 'userId = :userId and orderId = :orderId',
ExpressionAttributeValues: { ':userId': userId, ':orderId': orderId }
};

If userId or orderId contains DynamoDB expression syntax, it could break out of the intended query context.

Batch operations present additional risks. DynamoDB's BatchGetItem and BatchWriteItem operations accept arrays of keys or items. When these arrays are constructed from user input without validation:

const items = req.body.items; // Array from user
const params = {
RequestItems: {
'Inventory': items.map(item => ({
PutRequest: { Item: item }
}))
}
};

An attacker could craft items that exploit DynamoDB's type system or expression evaluation.

Dynamodb-Specific Detection

Detecting LDAP injection patterns in DynamoDB requires examining both the query construction logic and the runtime behavior. Static analysis tools can identify dangerous patterns in code that builds DynamoDB expressions dynamically.

Code-level detection focuses on these indicators:

  • Dynamic construction of FilterExpression, KeyConditionExpression, or UpdateExpression strings
  • Concatenation of user input into expression strings
  • Direct use of request parameters in ExpressionAttributeValues without validation
  • Dynamic function names in expressions (e.g., contains, begins_with)

Runtime detection involves monitoring query execution and response patterns. Unexpected query results, performance anomalies, or authorization bypass attempts may indicate injection attempts.

middleBrick's DynamoDB security scanning specifically tests for these injection patterns by:

  • Submitting crafted payloads containing special characters, comparison operators, and boolean logic
  • Testing expression syntax manipulation attempts
  • Verifying that user input cannot alter query structure or logic
  • Checking for data exposure through malformed queries

The scanner tests 12 security checks including Input Validation and Data Exposure, which directly address LDAP injection patterns in DynamoDB contexts. For example, it submits payloads like:

middlebrick scan https://api.example.com/users 
# Tests for LDAP injection patterns in DynamoDB queries

middleBrick's LLM/AI Security features also scan for AI-specific injection patterns that might affect DynamoDB queries processed by AI services, detecting system prompt leakage and prompt injection attempts that could manipulate query logic.

Continuous monitoring through middleBrick's Pro plan can detect injection attempts over time, alerting when suspicious query patterns emerge or when security scores drop below configured thresholds.

Dynamodb-Specific Remediation

Remediating LDAP injection in DynamoDB requires strict input validation, parameterized queries, and proper expression construction. The primary defense is never concatenating user input directly into expression strings.

Safe DynamoDB query construction follows these principles:

1. Use Parameterized Expressions

// SAFE: parameterized query
const email = req.query.email;
if (!isValidEmail(email)) {
throw new Error('Invalid email format');
}
const params = {
TableName: 'Users',
FilterExpression: 'email = :email',
ExpressionAttributeValues: { ':email': email }
};

2. Validate Input Strictly

function isValidEmail(email) {
const emailRegex = /^[a-zA-Z0-9._-]+@[a-zA-Z0-9.-]+$/;
return emailRegex.test(email);
}

function validateUserId(userId) {
// Enforce numeric or UUID format
return /^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}$/.test(userId);
}

3. Use Expression Attribute Names for Reserved Words

const params = {
TableName: 'Orders',
FilterExpression: '#status = :status',
ExpressionAttributeNames: { '#status': 'status' },
ExpressionAttributeValues: { ':status': 'pending' }
};

4. Implement Input Sanitization

function sanitizeDynamoInput(input) {
// Remove or escape special characters
return input.replace(/[()';]/g, ''); // Basic sanitization
}

5. Use DynamoDB's Built-in Validation

const params = {
TableName: 'Products',
};

6. Implement Query Pattern Templates

const queryTemplates = {
findByEmail: 'email = :email',
findById: 'id = :id',
findByStatus: '#status = :status'
};

function buildSafeQuery(template, values) {
if (!queryTemplates[template]) {
throw new Error('Invalid query template');
}
return {
FilterExpression: queryTemplates[template],
ExpressionAttributeValues: values
};
}

7. Use IAM Least Privilege

// IAM policy limiting query capabilities
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [ "dynamodb:Query", "dynamodb:Scan", "dynamodb:GetItem" ],
"Resource": "arn:aws:dynamodb:region:account:table/AllowedTable" }
]
}

middleBrick's remediation guidance maps these fixes to specific findings, providing severity-based prioritization and compliance mappings to OWASP API Top 10 and other frameworks.

Frequently Asked Questions

How does middleBrick detect LDAP injection in DynamoDB queries?
middleBrick scans DynamoDB endpoints by submitting crafted payloads containing special characters, boolean operators, and expression syntax. It tests FilterExpression construction, KeyConditionExpression manipulation, and batch operation inputs. The scanner identifies when user input can alter query logic or bypass authorization, providing specific findings with severity levels and remediation guidance mapped to OWASP API Top 10.
Can LDAP injection in DynamoDB lead to data exfiltration?
Yes. When LDAP injection patterns allow query structure manipulation in DynamoDB, attackers can potentially bypass authorization checks, modify filter logic to return unintended data, or craft queries that extract sensitive information. This is particularly dangerous in applications that use DynamoDB for user data storage, where injection could expose PII, credentials, or business data. middleBrick's Data Exposure check specifically tests for these exfiltration scenarios.