Prototype Pollution in Echo Go with Cockroachdb

Prototype pollution in an Echo Go application that uses Cockroachdb typically arises when user-controlled input is merged into server-side objects used to construct database queries or session data. In Go, this often occurs through libraries that perform shallow copies or iterative updates on map structures. If input is deserialized into a map and then used to build dynamic query arguments for Cockroachdb, an attacker can inject keys such as __proto__, constructor, or other properties that affect object inheritance chains in JavaScript-based tooling or configuration objects that your Go service generates for downstream clients. While Go itself does not exhibit prototype pollution at runtime, the vulnerability manifests when the data shapes influence JSON serialization, template rendering, or client-side artifacts that are later interpreted by JavaScript runtimes.

With Cockroachdb, the risk is not in the database engine’s core behavior but in how application-layer code builds SQL strings or ORM conditions from polluted maps. For example, a developer might construct a WHERE clause by iterating over a map derived from user input, inadvertently allowing an injected key to change the logical structure of the query. A crafted payload could add unintended filters or modify field values, leading to information exposure or unauthorized data access. Because middleBrick tests input validation and property authorization across 12 parallel checks, it can identify whether query construction logic is overly permissive and whether the application properly sanitizes keys before they reach the Cockroachdb interaction layer.

Another scenario involves OpenAPI spec generation and runtime reflection. If an Echo Go service exposes an endpoint that accepts a JSON body and uses it to dynamically generate SQL for Cockroachdb without strict schema validation, an attacker can submit properties that modify behavior across the object graph. The presence of $ref resolution in the spec analysis means that definitions shared across endpoints can propagate polluted structures. middleBrick’s checks for input validation and property authorization highlight cases where the service fails to restrict which fields can influence query parameters, reducing the risk that tainted data reaches the database layer.

To remediate prototype pollution risks in Echo Go with Cockroachdb, enforce strict schema validation on all incoming data before it is used to construct queries. Use strongly typed structs for request binding and avoid mapping arbitrary user input directly to map[string]interface{} that later influences SQL generation. For dynamic queries, prefer parameterized statements and whitelisted field names.

// Example: safe query construction with Cockroachdb in Echo Go
package main

import (
	"context"
	"github.com/labstack/echo/v4"
	"github.com/lib/pq"
	"database/sql"
	_ "github.com/cockroachdb/cockroach-go/v2/crdb"
)

type SearchRequest struct {
	Status  string `json:"status" validate:"oneof=pending completed"`
	OwnerID int64  `json:"owner_id" validate:"required,min=1"`
}

func getTasks(c echo.Context) error {
	req := new(SearchRequest)
	if err := c.Bind(req); err != nil {
		return echo.NewHTTPError(400, "invalid request")
	}
	if err := c.Validate(req); err != nil {
		return echo.NewHTTPError(400, err.Error())
	}

	// Use parameterized query with explicitly selected columns
	query := `SELECT id, title, status, owner_id FROM tasks WHERE status = $1 AND owner_id = $2`
	rows, err := c.Get("db").(*sql.DB).QueryContext(c.Request().Context(), query, req.Status, req.OwnerID)
	if err != nil {
		return echo.NewHTTPError(500, "database error")
	}
	defer rows.Close()
	// process rows...
	return c.JSON(200, rows)
}

func main() {
	db, err := sql.Open("postgres", "postgresql://root@localhost:26257/mydb?sslmode=disable")
	if err != nil {
		panic(err)
	}
	e := echo.New()
	e.POST("/tasks/search", getTasks)
	e.Logger.Fatal(e.Start(":8080"))
}

This pattern ensures that only known fields influence the query. If your use case requires dynamic filters, maintain a strict allowlist of column names and validate them server-side before concatenation. Avoid building SQL by string concatenation with map keys derived from user input, as this is a common vector for indirect data manipulation that could affect Cockroachdb query semantics.

Additionally, review serialization settings to ensure that responses written back to clients do not include internal metadata that could be leveraged for further pollution in consuming applications. middleBrick’s Data Exposure and Encryption checks can verify whether sensitive fields or internal identifiers are unintentionally surfaced in API responses, complementing your remediation efforts.