Ldap Injection in Fiber with Dynamodb

Ldap Injection occurs when user-controlled input is concatenated into an LDAP query without validation or escaping, allowing an attacker to alter query semantics. In a Fiber application that interacts with AWS DynamoDB to store or retrieve user records which are later used in LDAP operations (for example, group membership checks or authentication against an LDAP directory), injection can arise at the intersection of the web framework, the database layer, and the LDAP backend.

Consider a scenario where DynamoDB holds user entries with attributes such as username and email. A vulnerable endpoint in Fiber retrieves a username from a DynamoDB item and builds an LDAP filter by string concatenation:

// Vulnerable: building LDAP filter via string concatenation
username := userFromDynamodb.Username
filter := "(&(objectClass=user)(uid=" + username + "))"
ldapSearch(filter)

An attacker can supply a username like admin)(uid=*)(cn=, turning the filter into:

(&(objectClass=user)(uid=admin)(uid=*)(cn=))

This may bypass authentication or extract unintended entries. Even when DynamoDB itself does not execute LDAP, storing and serving attacker-influenced data that is later used in LDAP queries creates an injection surface. The risk is elevated when authorization checks rely on LDAP group membership derived from DynamoDB-stored identifiers, enabling privilege escalation or information disclosure.

Because middleBrick tests unauthenticated attack surfaces across 12 checks including Authentication, Input Validation, and LLM/AI Security, it can flag LDAP injection patterns that involve dynamic query assembly and unsanitized data flows between DynamoDB and LDAP components.

Remediation centers on strict input validation, parameterized queries where applicable, and avoiding direct concatenation of user-controlled data into LDAP filters. When retrieving data from DynamoDB, treat all attributes as untrusted and sanitize before LDAP usage.

1. Use allowlists and strict validation for identifiers like username. Reject characters that have special meaning in LDAP filters: *, (, ), \, NUL, and control characters.

2. Prefer constructing filters via a structured approach rather than string concatenation. For example, use a library that properly escapes special characters or build filter components programmatically.

3. Apply the principle of least privilege: the IAM role attached to your Fiber service should have minimal permissions on DynamoDB (e.g., dynamodb:GetItem for the specific table) to limit impact if other vulnerabilities exist.

Below is a secure Fiber handler in Go that retrieves a user from DynamoDB and prepares a safe LDAP filter:

import (
    "github.com/gofiber/fiber/v2"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb"
    "github.com/aws/aws-sdk-go-v2/aws"
    "regexp"
    "strings"
)

var ldapSafe = regexp.MustCompile(`^[a-zA-Z0-9._-]+$`)

func getUserAndLdapFilter(c *fiber.Ctx) error {
    username := c.Params("username")
    if !ldapSafe.MatchString(username) {
        return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "invalid username"})
    }

    // Fetch user attributes from DynamoDB
    out, err := dynamoClient.GetItem(c.Context(), &dynamodb.GetItemInput{
        TableName: aws.String("Users"),
        Key: map[string]types.AttributeValue{
            "Username": &types.AttributeValueMemberS{Value: username},
        },
    })
    if err != nil {
        return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"error": "unable to fetch user"})
    }

    // Re-validate after retrieval
    dbUsername := strings.TrimSpace(*out.Item["Username"].(*types.AttributeValueMemberS).Value)
    if !ldapSafe.MatchString(dbUsername) {
        return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "invalid data"})
    }

    // Build LDAP filter safely
    filter := "(&(objectClass=user)(uid=" + dbUsername + "))"
    ldapSearch(filter)
    return c.SendStatus(fiber.StatusOK)
}

For automated security checks, the Pro plan of middleBrick supports continuous monitoring and can be integrated into your CI/CD pipeline via the GitHub Action to fail builds if risky patterns are detected across scans. The MCP Server also enables scanning APIs directly from your IDE, helping catch issues early during development.