Nosql Injection in Echo Go with Bearer Tokens

Nosql Injection occurs when user-controlled input is directly used to construct NoSQL queries without proper validation or parameterization. In an Echo Go service that relies on Bearer Tokens for authentication, the combination of per-request authorization parsing and unchecked query construction can expose endpoints to injection. Consider a handler that extracts a bearer token, decodes its claims, and uses a claim such as userID to build a MongoDB selector or a DynamoDB filter. If the userID from the token (or an attacker-influenced query parameter) is concatenated into the query string, an attacker can inject operators like $ne, $gt, or $where to alter logic or escalate access.

For example, a developer might write a function that selects a user document by ID taken from the token’s sub claim, then appends additional filters from request query parameters. If the query is built by string interpolation rather than using a typed struct or a parameter-safe builder, an input like {"$ne": "{"} can change the intended equality check into an inequality that returns other users’ data. This becomes especially risky when the token is issued by an external identity provider and the application trusts the contents without additional validation beyond signature verification.

Echo Go middleware often wraps authentication by extracting the Bearer token from the Authorization header, verifying it, and placing claims into the request context. If downstream handlers read claims directly to form NoSQL keys or filters, and also reflect untrusted query parameters into the same query, the attack surface expands. An attacker who can influence either the token payload (via a stolen or forged token) or the URL parameters can manipulate the resulting NoSQL selector. Common patterns vulnerable to this include passing token-derived identifiers into raw map-based filters or using reflection-based serialization that maps incoming JSON keys directly to database query conditions.

Real-world NoSQL injection behavior depends on the database driver and query API. In MongoDB, injecting operators such as $in or $regex can return unintended documents; in DynamoDB, key condition expression injection can scan beyond the intended partition key. Because Echo Go services frequently rely on third-party authentication libraries that populate context with claims, the risk emerges when those claims are naively composed into query structures. The vulnerability is not in Bearer Tokens themselves, but in how token-derived data is combined with unchecked NoSQL query construction, making the API susceptible to data exfiltration or privilege bypass.

Remediation centers on strict separation between authentication-derived claims and query construction, and the use of typed, parameterized structures instead of string-based query assembly. Below are concrete, idiomatic examples for Echo Go that demonstrate secure handling of Bearer Tokens and NoSQL queries.

Secure Token Validation and Claim Handling

Always validate the token signature and explicitly specify which claims you accept. Do not trust arbitrary fields for database queries.

import (
    "github.com/labstack/echo/v4"
    "github.com/golang-jwt/jwt/v5"
)

type CustomClaims struct {
    UserID string `json:"user_id"`
    Scopes []string `json:"scopes"`
    jwt.RegisteredClaims
}

func verifyToken(next echo.HandlerFunc) echo.HandlerFunc {
    return func(c echo.Context) error {
        auth := c.Request().Header.Get("Authorization")
        if auth == "" {
            return echo.ErrUnauthorized
        }
        tokenString := auth[len("Bearer "):]
        token, err := jwt.ParseWithClaims(tokenString, &CustomClaims{}, func(token *jwt.Token) (interface{}, error) {
            // TODO: use your actual key function, e.g., RSA public key
            return []byte("your-secret"), nil
        })
        if err != nil || !token.Valid {
            return echo.ErrUnauthorized
        }
        claims := token.Claims.(*CustomClaims)
        // Only use explicitly defined claims; do not forward raw claims to DB queries
        c.Set("userID", claims.UserID)
        return next(c)
    }
}

Parameterized NoSQL Queries (MongoDB Example)

Use typed structs and avoid concatenating user or claim values into selector strings.

import (
    "go.mongodb.org/mongo-driver/bson"
    "go.mongodb.org/mongo-driver/mongo"
)

type UserProfile struct {
    UserID string `bson:"user_id"`
    Email  string `bson:"email"`
}

func getUserProfile(c echo.Context, collection *mongo.Collection) error {
    userID := c.Get("userID").(string)
    var filter bson.M = bson.M{"user_id": userID} // safe: explicit field, no concatenation
    var result UserProfile
    if err := collection.FindOne(c.Request().Context(), filter).Decode(&result); err != nil {
        return echo.NewHTTPError(http.StatusInternalServerError, "unable to fetch profile")
    }
    return c.JSON(http.StatusOK, result)
}

Parameterized NoSQL Queries (DynamoDB Example)

Use the builder pattern with explicit key condition expressions and avoid injecting attribute names from input.

import (
    "github.com/aws/aws-sdk-go-v2/service/dynamodb"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb/types"
    "github.com/aws/aws-sdk-go-v2/feature/dynamodb/attributevalue"
)

type UserIndex struct {
    UserID string `dynamodbav:"user_id"`
    Email  string `dynamodbav:"email"`
}

func FetchUser(ctx context.Context, client *dynamodb.Client, userID string) (*UserIndex, error) {
    out, err := client.Query(ctx, &dynamodb.QueryInput{
        TableName: aws.String("Users"),
        KeyConditionExpression: aws.String("user_id = :uid"),
        ExpressionAttributeValues: map[string]types.AttributeValue{
            ":uid": &types.AttributeValueMemberS{Value: userID},
        },
    })
    if err != nil {
        return nil, err
    }
    var item UserIndex
    if err := attributevalue.UnmarshalMap(out.Items[0], &item); err != nil {
        return nil, err
    }
    return &item, nil
}

Additional Hardening Practices

• Do not reflect incoming JSON keys into NoSQL filters; use explicit field mappings.
• Apply strict allowlists for known query parameters if reflection is required.
• Log suspicious patterns (e.g., operators in string values) without exposing sensitive data in responses.

By keeping token-derived data as simple, typed identifiers and using parameterized query APIs, you eliminate the injection path while preserving the convenience of Bearer Token authentication.