Email Injection in Gin with Dynamodb

Email Injection becomes relevant in a Gin application when user-controlled input is used to construct email headers or message content that is later processed by an email service. In a typical workflow, a Gin handler might accept a user email address or message text, validate it at the application layer, and then forward it to an AWS DynamoDB table for logging or record-keeping. If input is not strictly sanitized, an attacker can supply newline characters (e.g., %0d%0a or \r\n) within the email field, causing header injection. Later, when an administrative script or a backend process retrieves the stored data from DynamoDB and uses it to compose raw SMTP commands or passes it to a templating engine for email generation, the injected lines can alter message routing, inject additional headers, or spoof the sender address.

DynamoDB itself does not interpret email semantics, but it stores the raw payload. The risk emerges during consumption: an unauthenticated scan by middleBrick can detect whether your public-facing Gin endpoints accept newline characters in email parameters and whether retrieved DynamoDB records are used in downstream email workflows. middleBrick’s Input Validation and Unsafe Consumption checks will flag patterns such as missing newline stripping, absence of strict allowlists for email characters, and missing encoding when data moves from DynamoDB into mail libraries. Because the scan is unauthenticated and runs in 5–15 seconds, it can quickly surface whether your API surface permits email injection via stored DynamoDB entries without requiring credentials or source code access.

Real-world attack patterns mirror CVE-like behaviors seen in header injection flaws, where a payload such as [email protected]%0d%0aCC: [email protected] is stored in DynamoDB and later rendered in an email composed by a backend worker. If the worker does not sanitize retrieved items, the injected headers can redirect mail, expose internal relays, or facilitate phishing. middleBrick’s LLM/AI Security checks do not apply here, but its cross-referencing of OpenAPI specs with runtime findings ensures that parameters documented as strings are also validated against observed injection attempts during the scan.

Remediation focuses on strict validation at the Gin handler boundary and safe handling when reading from DynamoDB. Use an allowlist approach for email addresses: accept only characters permitted by RFC 5322 (local-part and domain) and reject any presence of carriage return or line feed characters. When storing to DynamoDB, ensure the item attributes are normalized and encoded. When reading from DynamoDB and using the data in email contexts, reapply validation and use a dedicated email library that handles headers safely.

Example: Gin handler with validation and DynamoDB storage using the AWS SDK for Go (v2). This code demonstrates a minimal, secure pattern:

import (
    "net/http"
    "regexp"
    "strings"

    "github.com/aws/aws-sdk-go-v2/aws"
    "github.com/aws/aws-sdk-go-v2/config"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb/types"
    "github.com/gin-gonic/gin"
)

var emailRegex = regexp.MustCompile(`^[a-zA-Z0-9.!#$%&'*+/=?^_` + "`" + `{|}~-]+@[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?(?:\.[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?)*$`)

func isValidEmail(email string) bool {
    if strings.ContainsAny(email, "\r\n") {
        return false
    }
    return emailRegex.MatchString(email)
}

func SubmitEmail(c *gin.Context) {
    var payload struct {
        Email string `json:"email"`
    }
    if err := c.BindJSON(&payload); err != nil {
        c.JSON(http.StatusBadRequest, gin.H{"error": "invalid request"})
        return
    }

    if !isValidEmail(payload.Email) {
        c.JSON(http.StatusBadRequest, gin.H{"error": "invalid email"})
        return
    }

    cfg, err := config.LoadDefaultConfig(c.Request.Context())
    if err != nil {
        c.JSON(http.StatusInternalServerError, gin.H{"error": "config error"})
        return
    }
    client := dynamodb.NewFromConfig(cfg)

    item := map[string]types.AttributeValue{
        "email": &types.AttributeValueMemberS{Value: payload.Email},
    }
    _, err = client.PutItem(c.Request.Context(), &dynamodb.PutItemInput{
        TableName: aws.String("AuditLog"),
        Item:      item,
    })
    if err != nil {
        c.JSON(http.StatusInternalServerError, gin.H{"error": "storage error"})
        return
    }

    c.JSON(http.StatusOK, gin.H{"status": "ok"})
}

When retrieving items for email generation, re-validate and use net/mail to construct headers:

import (
    "net/mail"
    "net/textproto"
)

func buildHeader(email string) (textproto.MIMEHeader, error) {
    if !isValidEmail(email) {
        return nil, fmt.Errorf("invalid email")
    }
    h := make(textproto.MIMEHeader)
    addr, _ := mail.ParseAddress(email) // safe after validation
    h.Set("From", addr.String())
    return h, nil
}

By combining input validation, DynamoDB storage of normalized data, and safe header construction, you mitigate email injection while maintaining compatibility with standard workflows. middleBrick’s CLI can be used to verify that your endpoints reject newline-injected email values and that no unsafe patterns are present in observable API behavior.