Injection Flaws in Chi with Dynamodb

Injection flaws occur when untrusted data is interpreted as part of a command or query. In the context of Chi (a Go HTTP router) with DynamoDB as the backend, the risk typically arises when application code builds DynamoDB API requests—such as GetItem, Query, or Scan—using request-controlled inputs without strict validation or parameterization. Because DynamoDB operations often include key conditions, filter expressions, and expression attribute values, failing to isolate data from command logic can allow an attacker to manipulate intended query semantics.

Chi encourages clean routing and middleware composition, but developers must still ensure that any data used to construct DynamoDB inputs is treated as untrusted. For example, a path parameter like /users/{userID} might be directly embedded into a KeyConditionExpression or a filter expression. If user input is concatenated into the expression string rather than supplied via expression attribute values, an attacker may attempt to inject additional condition logic or affect pagination and filtering behavior.

DynamoDB itself does not support traditional SQL-style injection, but injection-like behavior can occur through expression manipulation. Consider a scenario where a Chi route reads a sort key value from a query parameter and appends it to a FilterExpression. If the input is not validated and expression attribute values are not used, an attacker could supply something like 1; DELETE FROM table-style syntax within a single expression context, attempting to exploit parser ambiguities or influence which items are returned. While DynamoDB will treat such input as a literal string in many cases, the broader concern is logic manipulation: changing which items are included or excluded, bypassing intended access controls, or causing inefficient scans that lead to denial of observable behavior.

An additional injection-adjacent risk surfaces when request parameters dictate which table or index is targeted. If a Chi handler dynamically selects a table name based on user input—such as a tenant identifier—and passes it directly to the DynamoDB API, this can lead to unintended data access across tenants or tables. Although DynamoDB enforces its own authentication-level permissions, the application-layer intent is subverted when the resource path is not strictly validated against an allowlist.

These patterns map clearly onto the broader category of BOLA/IDOR and improper input validation checks that middleBrick tests. The scanner does not rely on internal architecture but instead exercises the unauthentated attack surface to detect whether endpoints allow manipulation of data access patterns or expression logic. When paired with the LLM/AI Security checks—such as system prompt leakage or prompt injection probing—middleBrick illustrates how injection thinking extends beyond traditional web exploits into model and API interaction boundaries.

To summarize, the combination of Chi routing and DynamoDB usage creates injection-like vulnerabilities not through language-level injection, but through insufficient separation of data and command logic, missing input validation, and dynamic resource selection. These issues are detectable through behavioral testing and specification analysis, which is why integrating scanning tools like middleBrick into development workflows helps surface misconfigurations before exposure.

Remediation focuses on strict input validation, using expression attribute values, and avoiding dynamic construction of command components. Below are concrete, idiomatic examples for Chi that demonstrate safe patterns when interacting with DynamoDB.

1. Use expression attribute values for all user inputs

Never concatenate user input into expression strings. Instead, supply values through the ExpressionAttributeValues map. This ensures DynamoDB treats input as data only.

import (
    "context"
    "github.com/go-chi/chi/v5"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb"
    "github.com/aws/aws-sdk-go-v2/service/dynamodb/types"
)

func getUserHandler(dynamoClient *dynamodb.Client) http.HandlerFunc {
    return func(w http.ResponseWriter, r *http.Request) {
        userID := chi.URLParam(r, "userID")
        // Safe: userID is used as an expression attribute value, not in the expression itself
        input := &dynamodb.GetItemInput{
            TableName: aws.String("UsersTable"),
            Key: map[string]types.AttributeValue{
                "PK": &types.AttributeValueMemberS{Value: "USER#" + userID},
            },
            ExpressionAttributeNames: map[string]string{
                "#meta": "metadata",
            },
            ExpressionAttributeValues: map[string]types.AttributeValue{
                ":status": &types.AttributeValueMemberS{Value: "ACTIVE"},
            },
            FilterExpression: aws.String("#meta.status = :status"),
        }
        // Execute GetItem with controlled expressions
        _, err := dynamoClient.GetItem(r.Context(), input)
        if err != nil {
            http.Error(w, "Unable to fetch user", http.StatusInternalServerError)
            return
        }
        // Handle response...
    }
}

2. Validate and whitelist dynamic table or index references

If you must reference different tables based on a parameter, validate against a strict allowlist. Do not directly use request input as a table name.

func queryWithValidatedTable(r *http.Request, client *dynamodb.Client) error {
    tenant := chi.URLParam(r, "tenant")
    allowedTenants := map[string]string{
        "acme":     "TenantAcmeData",
        "globex":    "TenantGlobexData",
    }
    tableName, ok := allowedTenants[tenant]
    if !ok {
        return fmt.Errorf("invalid tenant")
    }
    input := &dynamodb.QueryInput{
        TableName: aws.String(tableName),
        KeyConditionExpression: aws.String("PK = :pk"),
        ExpressionAttributeValues: map[string]types.AttributeValue{
            ":pk": &types.AttributeValueMemberS{Value: "ORDER#2025"},
        },
    }
    _, err := client.Query(r.Context(), input)
    return err
}

3. Sanitize and constrain sort and filter keys

When sort keys or filter fields come from the client, map them to known safe values or enforce strict patterns (e.g., regex for alphanumeric + underscore). Avoid using raw input in KeyConditionExpression strings.

func buildKeyCondition(sortParam string) (string, map[string]types.AttributeValue, error) {
    // Allow only known sort keys to prevent injection-like manipulation
    allowed := map[string]bool{
        "created_at": true,
        "updated_at": true,
    }
    if !allowed[sortParam] {
        return "", nil, fmt.Errorf("invalid sort parameter")
    }
    keyExpr := sortParam + " = :val"
    attrs := map[string]types.AttributeValue{
        ":val": &types.AttributeValueMemberS{Value: "2025-01-01"},
    }
    return keyExpr, attrs, nil
}

4. Apply defense-in-depth with middleware validation

Use Chi middleware to sanitize and normalize inputs before they reach handlers. This centralizes validation and reduces the chance of accidental misuse in individual route handlers.

func ValidateUserID(next http.Handler) http.Handler {
    return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
        userID := chi.URLParam(r, "userID")
        if !regexp.MustCompile(`^[A-Za-z0-9_-]{1,64}$`).MatchString(userID) {
            http.Error(w, "invalid user identifier", http.StatusBadRequest)
            return
        }
        ctx := context.WithValue(r.Context(), "userID", userID)
        next.ServeHTTP(w, r.WithContext(ctx))
    })
}

By combining these strategies—expression attribute values, strict allowlists, input validation, and centralized middleware—you significantly reduce the risk of injection-like issues when using Chi with DynamoDB. These practices align with the checks performed by middleBrick, helping ensure your API surface remains secure and predictable.