Log Injection in Echo Go with Dynamodb

Log injection occurs when untrusted input is written directly into log entries without sanitization, enabling attackers to forge log lines, hide malicious activity, or trigger log-based security controls to misbehave. In an Echo Go service that stores or references data in DynamoDB, the combination of structured logging expectations, DynamoDB’s attribute-value format, and Echo’s HTTP request handling can unintentionally create paths for injection.

Consider an Echo handler that logs incoming request parameters alongside a DynamoDB key value before a GetItem call:

c.Logger().Infof("fetching item: user_id=%s, sort_key=%s", userID, sortKey)

If userID or sortKey originate from query parameters or headers and contain newlines or structured delimiters (e.g., userID=attacker@example.com\nAWS_REQUEST_ID=stolen), the resulting log line can produce a second fabricated entry when logs are later parsed by line-oriented tools. In DynamoDB terms, storing raw, unsanitized request attributes as item keys or string attributes can also cause issues if log messages include those attribute values verbatim, because log parsers may misinterpret embedded control characters or JSON-like fragments as new log records or metadata.

Additionally, if your application logs the raw DynamoDB AttributeValue map before validation, special characters such as newlines, tabs, or Unicode line separators within string sets can corrupt log structure. This becomes particularly risky when logs are forwarded to systems that rely on newline delimiters. The vulnerability is not in DynamoDB itself but in how attribute values are sourced into logs without normalization or escaping, combined with Echo’s straightforward routing that may pass unchecked input into logging statements.

To mitigate log injection when integrating Echo Go with DynamoDB, ensure all data written to logs is sanitized and that DynamoDB attribute values are validated and normalized before inclusion in any log context. Below are concrete, safe patterns for Echo handlers that interact with DynamoDB.

1. Sanitize inputs before logging

Normalize strings by removing or replacing control characters and newlines. Use a small helper to clean attribute values that may be logged:

// sanitizeLogValue removes or replaces characters that can break log structure.
func sanitizeLogValue(v string) string {
    // Replace newlines and carriage returns; trim spaces.
    v = strings.ReplaceAll(v, "\r", "\\r")
    v = strings.ReplaceAll(v, "\n", "\\n")
    v = strings.TrimSpace(v)
    return v
}

// Usage in an Echo handler:
userID := sanitizeLogValue(c.Param("userID"))
sortKey := sanitizeLogValue(c.Param("sortKey"))
c.Logger().Infof("fetching item: user_id=%s, sort_key=%s", userID, sortKey)

2. Validate and encode DynamoDB attribute values

When constructing DynamoDB input structures, validate string lengths and content. Avoid directly inserting raw request values into key expressions or attribute values used for logging. Use the AWS SDK for Go’s model types explicitly:

import (
    "github.com/aws/aws-sdk-go/service/dynamodb"
    "github.com/labstack/echo/v4"
    "strings"
)

func getItemHandler(c echo.Context) error {
    userID := sanitizeLogValue(c.Param("userID"))
    sortKey := sanitizeLogValue(c.Param("sortKey"))

    // Validate expected format (e.g., UUID for userID)
    if !isValidUUID(userID) {
        return echo.NewHTTPError(400, "invalid user_id")
    }

    input := &dynamodb.GetItemInput{
        TableName: aws.String("Items"),
        Key: map[string]*dynamodb.AttributeValue{
            "PK": {
                S: aws.String("USER#" + userID),
            },
            "SK": {
                S: aws.String("METADATA#" + sortKey),
            },
        },
    }

    // Perform GetItem (pseudo-call, assuming svc is a DynamoDB client)
    // result, err := svc.GetItem(input)

    c.Logger().Infof("fetching item: user_id=%s, sort_key=%s", userID, sortKey)
    return c.JSON(200, map[string]string{"status": "ok"})
}

func isValidUUID(s string) bool {
    // Simple pattern check; replace with full RFC 4122 validation if needed.
    return len(s) == 36
}

3. Structured logging with explicit field mapping

Instead of interpolating raw values into free-form messages, log structured fields. This reduces ambiguity during parsing and avoids injection through delimiters:

c.Logger().Infof("dynamodb_request",
    zap.String("user_id", sanitizeLogValue(c.Param("userID"))),
    zap.String("sort_key", sanitizeLogValue(c.Param("sortKey"))),
)

With structured logging, parsers treat each field independently, making it significantly harder for injected newlines to create false entries. This approach pairs well with DynamoDB because you can reliably correlate log entries with specific item keys without risking line-based injection.

4. Control attribute content in stored items

If you store request-derived values as DynamoDB string attributes, enforce server-side validation and normalization before writing. For example, reject attributes containing newline or tab characters that could later be exported into logs:

func validateAttribute(v string) error {
    if strings.ContainsAny(v, "\r\n\t") {
        return errors.New("attribute contains disallowed control characters")
    }
    return nil
}

// When preparing PutItemInput:
if err := validateAttribute(userSuppliedString); err != nil {
    return echo.NewHTTPError(400, err.Error())
}