Ldap Injection in Gin with Dynamodb

LDAP injection is an injection technique where untrusted input is concatenated into LDAP query strings, allowing an attacker to alter query logic. Gin is a popular HTTP web framework for Go, and while it does not directly interact with LDAP, developers often build authentication or group-resolution endpoints in Gin that forward credentials or filters to an LDAP service. When those endpoints construct LDAP filters using string concatenation or interpolation, injection becomes possible.

In a typical Gin handler, you might accept a username or search filter from a client and embed it in an LDAP query such as (&(uid=USER)(objectClass=person)). If USER is taken directly from user input and not sanitized, an attacker can supply values like admin)(uid=*))(|(uid=evil to break the filter structure, potentially bypassing authentication or reading unauthorized entries.

DynamoDB is often used as a user store or cache in backend services written in Go. The vulnerability arises when the application uses data derived from LDAP queries (or attempts to mirror LDAP-style filters) to build DynamoDB operations, such as constructing KeyConditionExpressions or filtering expressions. For example, if a Gin handler builds a DynamoDB Scan or Query filter using string concatenation with values that originated from LDAP input, malicious payloads can manipulate which items are retrieved or cause unexpected behavior in the query.

Consider a scenario where a Gin endpoint accepts a search term, queries LDAP for user details, and then uses that term to filter items in a DynamoDB table. If the LDAP query is vulnerable to injection and the resulting data is passed into a DynamoDB expression without validation, the attacker may influence which DynamoDB items are returned. This can lead to information disclosure, privilege escalation (if roles or permissions are stored in DynamoDB), or bypassing intended access controls. Because DynamoDB does not support native LDAP query syntax, the injection surface is typically in how the application translates LDAP-derived inputs into DynamoDB operations rather than in LDAP or DynamoDB themselves.

middleBrick detects this class of issue by analyzing the unauthenticated attack surface of your Gin endpoints and correlating findings with risky usage patterns, such as unchecked input usage in DynamoDB expressions. It does not test internal LDAP servers or your DynamoDB data model directly; rather, it flags locations where attacker-controlled data could affect authentication flows or data access logic that involves DynamoDB.

To prevent LDAP injection when the data influences DynamoDB operations in a Gin service, follow strict input validation, use parameterized approaches, and avoid string-based query building. Below are concrete, actionable fixes and examples for a Gin handler that interacts with DynamoDB.

1. Validate and sanitize LDAP-derived input before using it in DynamoDB

Treat any data originating from LDAP queries as untrusted. Normalize and validate it before using it in a DynamoDB expression.

import (
    "github.com/gin-gonic/gin"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb/types"
    "regexp"
    "strings"
)

// validateUsername ensures the input contains only safe characters for uid.
func validateUsername(input string) bool {
    // Allow alphanumeric, underscore, hyphen, and dot; length limits reduce risk.
    pattern := `^[a-zA-Z0-9_.-]{1,64}$`
    matched, _ := regexp.MatchString(pattern, input)
    return matched
}

2. Use DynamoDB ConditionExpression and ExpressionAttributeValues (parameterized patterns)

Never concatenate user input into filter or key expressions. Use ExpressionAttributeNames and ExpressionAttributeValues to keep data separate from the instruction language.

func queryUser(c *gin.Context, svc *dynamodb.Client) {
    username := c.Query("username")
    if !validateUsername(username) {
        c.JSON(400, gin.H{"error": "invalid username"})
        return
    }

    input := &dynamodb.QueryInput{
        TableName:              aws.String("Users"),
        KeyConditionExpression: aws.String("pk = :uid"),
        ExpressionAttributeNames: map[string]string{
            "pk": "PK",
        },
        ExpressionAttributeValues: map[string]types.AttributeValue{
            ":uid": &types.AttributeValueMemberS{Value: "USER#" + username},
        },
    }

    out, err := svc.Query(c, input)
    if err != nil {
        c.JSON(500, gin.H{"error": "query failed"})
        return
    }
    c.JSON(200, out.Items)
}

3. Avoid building expressions with string replacement or concatenation

Do not use functions that insert values directly into the expression string. This is unsafe even if you attempt to escape characters.

// UNSAFE: building expression with string concatenation
// Avoid patterns like:
// expr := "username = '" + username + "'"
// Instead, always use expression attributes as shown above.

4. Apply least-privilege IAM policies for the DynamoDB operations called by Gin

Ensure the role associated with your service can only perform the specific actions needed (e.g., dynamodb:Query on a particular table). This limits the impact of any injection that may bypass validation.

5. Use middleware to normalize authentication flows and avoid mixing LDAP syntax with DynamoDB

Keep LDAP-specific operations isolated and do not propagate raw LDAP filters into downstream data store logic. If you must mirror LDAP search patterns, transform them into safe parameterized queries before any DynamoDB interaction.

middleBrick’s scans can help identify endpoints where LDAP-derived input reaches DynamoDB-related logic without sufficient validation. By running the scanner against your Gin service, you can surface risky patterns and prioritize fixes using the prioritized findings and remediation guidance provided in the report.