Sql Injection in Gorilla Mux with Dynamodb

SQL Injection is commonly associated with SQL databases, but injection concepts can manifest in NoSQL contexts when query construction is driven by unchecked user input. With DynamoDB, the primary risk is not traditional SQL injection but injection-like behavior in expression-based APIs, such as the DynamoDB ConditionExpression or FilterExpression, where untrusted input can alter query logic. When using Gorilla Mux as a router, if path parameters, query strings, or body values are directly interpolated into DynamoDB API calls without validation or parameterization, you expose an injection surface.

Consider a handler where a user-supplied id is used in a ConditionExpression to fetch an item:

condition := fmt.Sprintf("id = '%s'", r.URL.Query().Get("id"))
input := &dynamodb.GetItemInput{
    TableName: aws.String("Users"),
    Key: map[string]*dynamodb.AttributeValue{
        "id": {S: aws.String(r.URL.Query().Get("id"))},
    },
    ConditionExpression: aws.String(condition),
}
_, err := svc.GetItem(context.TODO(), input)

If the id query parameter contains something like id = 'anything' OR attribute_exists(aws_role), the resulting expression changes intent, potentially bypassing authorization checks or causing unexpected item access. Gorilla Mux variables like {id} in the route are similarly risky if used to build expressions without escaping or type-safe construction. DynamoDB does not parse SQL-like syntax, but expression injection can lead to authentication bypass, data leakage, or unintended writes. The scanner’s checks for Input Validation and Property Authorization highlight these risks when dynamic strings reach the SDK layer.

Another pattern involves building KeyConditionExpression for queries. Suppose a route declares a path parameter pk and uses it directly in an expression:

pk := mux.Vars(r)["pk"]
keyCond := fmt.Sprintf("pk = '%s' AND begins_with(sk, :v)", pk)
input := &dynamodb.QueryInput{
    TableName:            aws.String("Items"),
    KeyConditionExpression: aws.String(keyCond),
    ExpressionAttributeValues: map[string]*dynamodb.AttributeValue{
        ":v": {S: aws.String("item_")},
    },
}
_, err := svc.Query(context.TODO(), input)

An attacker could set pk to pk' OR attribute_exists(aws_access_key_id)-- or other crafted values to manipulate partition/sort key logic. Even though DynamoDB uses its own expression syntax, untrusted input concatenated into these strings can change semantics, violating the intended access pattern. The BOLA/IDOR and Property Authorization checks are designed to surface such unsafe usage, especially when combined with Gorilla Mux routing that exposes identifiers in paths.

Remediation centers on strict input validation, using DynamoDB’s native parameterization via expression attribute values, and avoiding string interpolation for expressions. Gorilla Mux routes should treat path and query parameters as untrusted, and all user-controlled data must be passed as values, not as part of the expression text.

Use placeholders (e.g., :id) and supply values through ExpressionAttributeValues. For a GetItem with a known attribute name, validate the attribute name against a whitelist and only use expression attribute values for data values:

id := mux.Vars(r)["id"]
if !isValidID(id) { // e.g., length and charset checks
    http.Error(w, "invalid id", http.StatusBadRequest)
    return
}
input := &dynamodb.GetItemInput{
    TableName: aws.String("Users"),
    Key: map[string]*dynamodb.AttributeValue{
        "id": {S: aws.String(id)},
    },
    ConditionExpression: aws.String("id = :val"),
    ExpressionAttributeValues: map[string]*dynamodb.AttributeValue{
        ":val": {S: aws.String(id)},
    },
}
_, err := svc.GetItem(context.TODO(), input)

For query patterns, parameterize both the partition key value and any sort key conditions:

pk := mux.Vars(r)["pk"]
skPrefix := r.URL.Query().Get("sk_prefix")
// Validate pk and skPrefix format before use
input := &dynamodb.QueryInput{
    TableName: aws.String("Items"),
    KeyConditionExpression: aws.String("pk = :pkval AND begins_with(sk, :skval)"),
    ExpressionAttributeValues: map[string]*dynamodb.AttributeValue{
        ":pkval": {S: aws.String(pk)},
        ":skval": {S: aws.String(skPrefix)},
    },
}
result, err := svc.Query(context.TODO(), input)

When attribute names must be dynamic (rare), use a strict allowlist and map them safely rather than interpolating:

allowedAttributes := map[string]bool{"status": true, "category": true}
attr := mux.Vars(r)["attr"]
if !allowedAttributes[attr] {
    http.Error(w, "invalid attribute", http.StatusBadRequest)
    return
}
input := &dynamodb.ScanInput{
    TableName: aws.String("Products"),
    FilterExpression: aws.String(fmt.Sprintf(#34;#f = :v", attr)),
    ExpressionAttributeNames: map[string]*string{
        "#f": aws.String(attr),
    },
    ExpressionAttributeValues: map[string]*dynamodb.AttributeValue{
        ":v": {BOOL: aws.Bool(true)},
    },
}
_, err := svc.Scan(context.TODO(), input)

Additionally, enforce server-side validation for data formats, apply length and pattern checks, and use the CLI tool to verify configurations. The GitHub Action can enforce a minimum security score before merges, while the MCP Server enables rapid scanning from your IDE to catch such issues early. Refer to findings from the scanner’s Input Validation and Property Authorization checks to iteratively harden endpoints.