Excessive Data Exposure in Echo Go with Dynamodb

Excessive Data Exposure occurs when an API returns more data than necessary for a given operation. In an Echo Go service that uses Dynamodb as its persistence layer, this commonly arises when query or scan operations retrieve entire items or unfiltered attribute sets and then return them directly in HTTP responses. Unlike relational stores where row-level permissions can sometimes be enforced in SQL, Dynamodb is a NoSQL key-value/document store; access patterns and data exposure are defined by how you construct requests and serialize results.

Echo Go applications often define handlers that call GetItem or Scan with a key condition or filter expression, but then omit explicit attribute selection. For example, a user profile endpoint might fetch an item by user ID and return the full DynamoDB record, which can contain sensitive fields such as internal identifiers, administrative flags, password hashes, or session tokens. Because scanning and query operations without projection expressions return all attributes by default, developers inadvertently expose data that should remain internal.

Additionally, if the service embeds sensitive metadata (e.g., internal versioning attributes, debug flags, or PII) in items, and these are returned in responses, the API surface grows unnecessarily. Attackers can leverage these extra data points for privilege escalation, social engineering, or to infer internal schemas. This is especially risky when combined with weak authentication or authorization, where an attacker can iterate over identifiers and observe whether different data exposures occur based on permissions or item contents.

With middleBrick’s LLM/AI Security checks, you can also detect scenarios where large language models interact with such endpoints. An LLM-facing endpoint that mirrors DynamoDB responses without scrubbing may leak system prompts, internal logic, or PII present in the stored data. middleBrick tests for system prompt leakage and output scanning for PII and API keys, which is valuable when API responses include raw DynamoDB items that may contain sensitive information.

To identify this class of issue, scans review whether responses include unexpected attributes and whether least-privilege data selection is enforced. Findings will highlight missing attribute filtering, unrestricted scan or query usage, and improper serialization of DynamoDB data formats (e.g., nested type descriptors like S, N, BOOL) that may expose structure beyond intended content.

Remediation focuses on narrowing the data returned from DynamoDB and ensuring responses contain only what the consumer needs. Use projection expressions in GetItem, Query, and Scan to restrict attributes, and avoid returning raw DynamoDB attribute value descriptors to clients.

Example of an unsafe pattern that returns all attributes:

// Unsafe: retrieves full item and returns raw DynamoDB map
func getUserProfile(c echo.Context) error {
    input := &dynamodb.GetItemInput{
        TableName: aws.String("Users"),
        Key: map[string]*dynamodb.AttributeValue{
            "user_id": {S: aws.String(c.Param("id"))},
        },
    }
    result, err := svc.GetItem(context.Background(), input)
    if err != nil {
        return echo.NewHTTPError(http.StatusInternalServerError, err.Error())
    }
    // This returns the entire DynamoDB item, potentially exposing sensitive attributes
    return c.JSON(result.Item)
}

Safer approach with explicit projection and attribute normalization:

// Safe: uses ProjectionExpression and returns only needed fields
func getUserProfile(c echo.Context) error {
    input := &dynamodb.GetItemInput{
        TableName: aws.String("Users"),
        Key: map[string]*dynamodb.AttributeValue{
            "user_id": {S: aws.String(c.Param("id"))},
        },
        // Limit returned attributes to only those required by the client
        ProjectionExpression: aws.String("user_id,username,email,profile_image_url"),
    }
    result, err := svc.GetItem(context.Background(), input)
    if err != nil {
        return echo.NewHTTPError(http.StatusInternalServerError, err.Error())
    }
    if result.Item == nil {
        return echo.NewHTTPError(http.StatusNotFound, "user not found")
    }
    // Transform DynamoDB representation into a clean response structure
    resp := map[string]interface{}{
        "user_id": *result.Item["user_id"].S,
        "username": *result.Item["username"].S,
        "email": *result.Item["email"].S,
        "profile_image_url": *result.Item["profile_image_url"].S,
    }
    return c.JSON(resp)
}

For Query operations, apply ProjectionExpression and paginate appropriately to avoid returning entire tables:

// Safe: Query with projection and pagination
input := &dynamodb.QueryInput{
    TableName: aws.String("UserSessions"),
    KeyConditionExpression: aws.String("user_id = :uid"),
    ExpressionAttributeValues: map[string]*dynamodb.AttributeValue{
        ":uid": {S: aws.String(userID)},
    },
    ProjectionExpression: aws.String("session_id,created_at,expires_at"),
    Limit: aws.Int64(50),
}
var sessions []map[string]interface{}
for {
    out, err := svc.Query(context.Background(), input)
    if err != nil {
        return echo.NewHTTPError(http.StatusInternalServerError, err.Error())
    }
    for _, item := range out.Items {
        sessions = append(sessions, map[string]interface{}{
            "session_id": *item["session_id"].S,
            "created_at": *item["created_at"].S,
            "expires_at": *item["expires_at"].S,
        })
    }
    if out.LastEvaluatedKey == nil {
        break
    }
    input.ExclusiveStartKey = out.LastEvaluatedKey
}
return c.JSON(sessions)

For Scan operations, which should be used sparingly, always include a FilterExpression and a ProjectionExpression to reduce data exposure and cost:

// Safe: Scan with filter and projection
input := &dynamodb.ScanInput{
    TableName: aws.String("AuditLogs"),
    FilterExpression: aws.String("severity = :level"),
    ExpressionAttributeValues: map[string]*dynamodb.AttributeValue{
        ":level": {S: aws.String("ERROR")},
    },
    ProjectionExpression: aws.String("timestamp,service,message"),
}

Finally, ensure that internal attributes used for application logic (e.g., _internal_flag, password_hash) are never projected or returned. Combine these practices with proper IAM policies to enforce read-level restrictions at the DynamoDB table level, reducing the impact of any accidental exposure.