Unicode Normalization in Gin with Dynamodb

Unicode normalization inconsistencies arise when an API accepts user-controlled string input, normalizes it differently than the persistence layer, and uses that value as a DynamoDB key. In Gin, if you read a path parameter or JSON body and store it directly in DynamoDB without a canonical normalization form, equivalent strings can map to different primary key values. This can bypass uniqueness checks, enable BOLA/IDOR-like access across logically related resources, or cause application logic to treat the same entity as two separate records.

For example, a user identifier might be submitted in NFC form (composed) by one client and NFD form (decomposed) by another. If the Gin service does not normalize before writing to DynamoDB, two records with logically identical keys will exist. An attacker can exploit this by switching normalization forms to retrieve or modify data belonging to another user, effectively an IDOR vector facilitated by key divergence rather than missing authorization checks. Input validation checks that compare raw strings will fail to detect the duplication, while property authorization checks that rely on the key may return the wrong item.

Because middleBrick scans the unauthenticated attack surface, it can surface inconsistencies between documented normalization expectations and runtime behavior. One of the 12 parallel checks tests Input Validation and can surface risks where string equivalence is not enforced consistently. Findings include severity-ranked guidance to normalize inputs to a single canonical form before any DynamoDB key construction, and to apply the same normalization on reads to ensure deterministic key resolution.

In OpenAPI/Swagger analysis, middleBrick resolves all $ref definitions and cross-references the spec against runtime findings. If your spec describes a path parameter like userID but does not explicitly require a normalization rule, the scanner highlights a gap that can contribute to key inconsistency when DynamoDB is used as the backend. The scanner does not fix the normalization, but it provides prioritized findings with remediation guidance mapped to frameworks such as OWASP API Top 10 and GDPR.

To prevent Unicode normalization issues when using Gin with DynamoDB, normalize all user-supplied strings to a single canonical form before using them as partition keys or sort keys. The Go standard library provides golang.org/x/text/unicode/norm and golang.org/x/text/transform to perform NFC, NFD, NFKC, or NFKD normalization.

Below is a concrete, working example for a Gin handler that normalizes an identifier before constructing a DynamoDB key. It uses the norm package to convert the input to NFC, ensuring a consistent key representation across clients.

import (
    "github.com/gin-gonic/gin"
    "golang.org/x/text/unicode/norm"
)

// normalizeNFC returns the NFC form of s, or an error if transform fails.
func normalizeNFC(s string) (string, error) {
    t := norm.NFC.String(s)
    return t, nil
}

func CreateUserHandler(c *gin.Context) {
    var req struct {
        UserID string `json:"user_id" binding:"required"`
        Name   string `json:"name" binding:"required"`
    }
    if err := c.ShouldBindJSON(&req); err != nil {
        c.JSON(400, gin.H{"error": err.Error()})
        return
    }

    canonicalID, err := normalizeNFC(req.UserID)
    if err != nil {
        c.JSON(500, gin.H{"error": "normalization failed"})
        return
    }

    // Example DynamoDB PutItem using the AWS SDK for Go v2.
    // Ensure the key uses the normalized value.
    _, err = dynamoClient.PutItem(c, &dynamodb.PutItemInput{
        TableName: aws.String("Users"),
        Item: map[string]types.AttributeValue{
            "user_id": &types.ScalarAttributeValue{Value: canonicalID},
            "name":    &types.ScalarAttributeValue{Value: req.Name},
        },
    })
    if err != nil {
        c.JSON(500, gin.H{"error": "failed to store user"})
        return
    }

    c.JSON(201, gin.H{"user_id": canonicalID})
}

On retrieval, apply the same normalization to any incoming key before querying DynamoDB. This prevents mismatches where a client supplies NFD while the stored key is in NFC.

func GetUserHandler(c *gin.Context) {
    userID := c.Param("user_id")
    canonicalID, err := normalizeNFC(userID)
    if err != nil {
        c.JSON(500, gin.H{"error": "normalization failed"})
        return
    }

    var out map[string]types.AttributeValue
    err = dynamoClient.GetItem(c, &dynamodb.GetItemInput{
        TableName:  aws.String("Users"),
        Key:        map[string]types.AttributeValue{"user_id": &types.ScalarAttributeValue{Value: canonicalID}},
        ConsistentRead: aws.Bool(true),
    }, &out)
    if err != nil || out["user_id"] == nil {
        c.JSON(404, gin.H{"error": "not found"})
        return
    }
    c.JSON(200, gin.H{"user_id": out["user_id"].(*types.ScalarAttributeValue).Value})
}

For automated enforcement, the Pro plan’s continuous monitoring can be configured to flag endpoints where input validation does not enforce a canonical normalization form before DynamoDB operations are performed. The CLI allows you to scan from terminal with middlebrick scan <url> to detect such gaps, and the GitHub Action can fail builds if risk scores drop below your chosen threshold. The MCP Server enables scanning APIs directly from your AI coding assistant within the IDE, helping maintain normalization discipline during development.