Ssrf Server Side in Gin with Dynamodb

Server-side request forgery (SSRF) in a Gin application that interacts with DynamoDB typically occurs when user-supplied input is used to form HTTP requests or to construct parameters that affect how backend services retrieve data from DynamoDB. In this stack, an attacker can supply a malicious URL or table reference that causes the server to make unintended internal calls, bypassing expected network boundaries and data access controls.

Gin does not inherently validate or restrict URLs used for HTTP client calls; if your routes accept a table name or key and then call an internal AWS metadata service (e.g., http://169.254.169.254/latest/meta-data/iam/security-credentials/) or another internal service based on user input, you expose an SSRF vector. When combined with DynamoDB, this can lead to data exfiltration from other tables, discovery of internal AWS resources, or abuse of linked IAM credentials. Common patterns include using a user-provided prefix to select a DynamoDB table or using a URL parameter to control conditional expressions that determine which item is fetched.

An illustrative unsafe Gin route might read a table name from a query parameter and then invoke the AWS SDK to get an item, without validating or restricting the table name. If the backend also makes an HTTP request to fetch metadata or transform input based on an unchecked URL, an attacker can direct the server to reach internal endpoints that are not intended to be exposed. Because DynamoDB operations are performed with the permissions of the calling role, SSRF can amplify impact by allowing an attacker to issue GetItem or Scan operations on sensitive tables using the instance profile’s credentials.

OpenAPI/Swagger analysis can surface these risks by showing that an endpoint accepts arbitrary URLs or table identifiers without schema validation or strict allowlists. When the spec includes parameters that flow into HTTP client calls or DynamoDB request construction, runtime findings can flag SSRF-related inputs that reach network calls or AWS SDK operations. This is especially important when the spec references internal endpoints or metadata paths that should never be user-controlled.

Remediation focuses on strict input validation, avoiding user-controlled URLs for internal calls, and applying least privilege to DynamoDB requests. Do not construct table names or keys directly from user input; instead, map user values to a controlled set of tables or use parameterized queries.

Safe DynamoDB GetItem in Gin with whitelisting

Use an allowlist for table names and validate key schemas explicitly. Below is a realistic, working example that avoids SSRF by not forwarding user input to URLs and by validating against a known set of tables.

//go
package main

import (
	"context"
	"net/http"

	"github.com/gin-gonic/gin"
	"github.com/aws/aws-sdk-go-v2/aws"
	"github.com/aws/aws-sdk-go-v2/config"
	"github.com/aws/aws-sdk-go-v2/service/dynamodb"
	"github.com/aws/aws-sdk-go-v2/service/dynamodb/types"
)

var allowedTables = map[string]bool{
	"users_prod": true,
	"config_staging": true,
}

func GetItemHandler(client *dynamodb.Client) gin.HandlerFunc {
	return func(c *gin.Context) {
		tableName := c.Query("table")
		keyVal := c.Query("id")
		if !allowedTables[tableName] {
			c.JSON(http.StatusBadRequest, gin.H{"error": "table not allowed"})
			return
		}
		if keyVal == "" {
			c.JSON(http.StatusBadRequest, gin.H{"error": "id is required"})
			return
		}

		out, err := client.GetItem(c, &dynamodb.GetItemInput{
			TableName: aws.String(tableName),
			Key: map[string]types.AttributeValue{
				"id": &types.AttributeValueMemberS{Value: keyVal},
			},
		})
		if err != nil {
			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
			return
		}
		c.JSON(http.StatusOK, out.Item)
	}
}
//go

Avoid using user input in HTTP calls that may be chained to DynamoDB

If your workflow includes fetching external metadata to enrich DynamoDB requests, validate and restrict destinations. Do not allow arbitrary URLs to guide internal AWS calls. Instead, use internal service discovery or configuration.

When you must call external services, use a strict allowlist of hostnames and prefer static endpoints over user-provided hosts. For DynamoDB-related operations, ensure the AWS SDK is configured with least-privilege credentials so that even if SSRF is partially reachable, the blast radius is limited.

Additional measures

• Apply schema validation for all query and body parameters before they reach business logic.
• Use environment-controlled configuration for endpoints rather than runtime assembly from user data.
• Instrument logs to detect unexpected internal requests to metadata or unusual DynamoDB patterns, which can indicate SSRF probing.

middleBrick can help identify these SSRF patterns and DynamoDB exposure risks during scans. With the Pro plan, you can enable continuous monitoring and GitHub Action integration to fail builds when insecure patterns are detected in your API definitions. The MCP Server allows you to scan APIs directly from your IDE, providing early feedback while you develop.