Integer Overflow in Chi with Dynamodb

An integer overflow in a Chi application that interacts with DynamoDB can occur when arithmetic on user-supplied numeric values (e.g., quantity, price, or limit) wraps around before values are used to construct or validate DynamoDB request parameters. Chi is a lightweight routing library for Go, and while it does not directly manipulate integers, handlers built with Chi often parse integers from path or query parameters and pass them to DynamoDB via the AWS SDK. If an integer is not validated for range or overflow before use, a value such as math.MaxInt64 + 1 can wrap to a small number, leading to incorrect condition expressions or key construction in DynamoDB operations.

For example, consider a handler that computes a numeric identifier by adding an offset to a user ID to create a DynamoDB sort key. If the addition overflows, the resulting identifier may unintentionally collide with another record or bypass an expected partition, exposing data that should be isolated (contributing to BOLA/IDOR-like findings that middleBrick tests under its BOLA/IDOR and Property Authorization checks). Overflow can also affect rate-limiting counters or pagination tokens, causing unexpected behavior that may be surfaced in findings related to Input Validation or Unsafe Consumption checks.

DynamoDB expects correctly bounded numeric values for attributes used in condition expressions (e.g., attribute_exists or between). If an overflowed integer is used in a condition that targets a numeric attribute, the condition may evaluate to true for unintended items or fail to match the intended item, leading to inconsistent authorization checks or data exposure. middleBrick’s unauthenticated scan can surface these logic flaws by correlating OpenAPI specifications with runtime behavior, particularly where integer parameters are passed into operations that affect item keys or condition expressions.

Real-world attack patterns such as IDOR often exploit weak validation around identifiers; an integer overflow can weaken controls further by producing identifiers that appear valid but resolve to incorrect resources. Because DynamoDB does not inherently protect against application-level arithmetic errors, the responsibility falls to the service consumer to validate inputs and ensure arithmetic safety before constructing requests. The OWASP API Top 10 category of Broken Object Level Authorization and common weaknesses such as CWE-190 (Integer Overflow or Wraparound) are relevant when assessing this risk in Chi + DynamoDB integrations.

In practice, a security scan using middleBrick can highlight areas where integer parameters are used in DynamoDB-related routes without proper range checks or type-safe parsing. The scanner cross-references the OpenAPI spec (including x-amazon-apigateway-request-parameters or schema definitions) with observed runtime patterns to identify mismatches that could enable data exposure or privilege escalation. This helps teams prioritize remediation for endpoints where numeric inputs directly influence DynamoDB key construction or condition logic.

To remediate integer overflow risks in a Chi application that interacts with DynamoDB, validate and sanitize all integer inputs before using them in arithmetic or DynamoDB request construction. Use fixed-size integer types with explicit overflow checks or leverage libraries that provide safe arithmetic. Ensure that numeric values used in DynamoDB condition expressions and key construction remain within expected bounds and do not wrap.

Below are concrete Go code examples using Chi and the AWS SDK for DynamoDB that demonstrate safe handling of integer parameters.

// Safe parsing and validation of an integer query parameter for DynamoDB usage
package main

import (
    "context"
    "fmt"
    "net/http"
    "strconv"

    "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 main() {
    r := chi.NewRouter()
    r.Get("/items/{id}", func(w http.ResponseWriter, r *http.Request) {
        // Parse ID safely
        idStr := chi.URLParam(r, "id")
        id, err := strconv.ParseUint(idStr, 10, 64)
        if err != nil || id > 1_000_000_000 {
            http.Error(w, "invalid or out-of-range id", http.StatusBadRequest)
            return
        }

        // Safe arithmetic with explicit checks
        offset := uint64(100)
        var sortKey uint64
        if id > math.MaxUint64 - offset {
            http.Error(w, "arithmetic overflow risk", http.StatusBadRequest)
            return
        }
        sortKey = id + offset

        // Build DynamoDB GetItem input with bounded values
        input := &dynamodb.GetItemInput{
            TableName: aws.String("Items"),
            Key: map[string]types.AttributeValue{
                "PK": &types.AttributeValueMemberS{Value: fmt.Sprintf("ITEM#%d", id)},
                "SK": &types.AttributeValueMemberN{Value: fmt.Sprintf("%d", sortKey)},
            },
        }

        // Execute with context
        svc := dynamodb.NewFromConfig(awsConfig)
        _, err = svc.GetItem(r.Context(), input)
        if err != nil {
            http.Error(w, "unable to fetch item", http.StatusInternalServerError)
            return
        }

        w.WriteHeader(http.StatusOK)
    })
}

In this example, strconv.ParseUint ensures the incoming ID is a valid unsigned 64-bit integer, and an explicit upper-bound check prevents IDs that are too large. Before performing addition to derive a sort key, the code checks for potential overflow by comparing the base value against math.MaxUint64 - offset. This avoids wraparound that could lead to unintended key values and bypasses in access control. The resulting numeric values are then safely formatted as strings for DynamoDB attribute values, avoiding reliance on raw integer serialization that could overflow in downstream processing.

For APIs described by OpenAPI, ensure numeric schemas include minimum, maximum, and exclusiveMaximum where applicable so that middleBrick and other scanners can align spec expectations with runtime validation. Consistent validation at the edge reduces the likelihood of integer overflow reaching DynamoDB condition expressions, which is especially important for operations that use numeric attributes in attribute_exists or comparison conditions.