Cache Poisoning in Rocket with Dynamodb

Cache poisoning in the Rocket framework when using DynamoDB as a backend typically occurs when an attacker manipulates cache keys or cacheable responses so that malicious or incorrect data is stored and subsequently served to other users. In a Rocket application, caching is often implemented at the route or handler level, and if the cache key is derived from user-supplied input without proper validation or normalization, an attacker can force cache entries that overwrite legitimate entries or store attacker-controlled content.

DynamoDB itself does not provide caching, so caching is usually implemented in the application layer (e.g., using a Redis or in-memory cache). The risk arises when the cache key includes unvalidated parameters such as user IDs, resource identifiers, or query parameters that are directly influenced by the client. For example, if a Rocket handler builds a cache key like format!("user:{user_id}") where user_id is taken directly from a request parameter or header without strict validation, an attacker can supply crafted values to pollute the cache namespace or cause cache collisions.

Another vector specific to Rocket and DynamoDB integrations is caching of database query results that include authorization context. If query results are cached based on a subset of input parameters (for example, a partition key) and the authorization context (e.g., requester identity) is not part of the cache key or is incorrectly normalized, one user may receive another user’s cached data (a form of BOLA/IDOR facilitated by caching). This can expose sensitive DynamoDB responses or allow an attacker to inject poisoned data that is later read by other users.

Additionally, if the Rocket application caches HTTP responses or rendered templates that include data fetched from DynamoDB, an attacker who can control part of the request that affects the DynamoDB response (such as a sort key filter or a query parameter) may cause the cache to store maliciously altered content. This is particularly relevant when the caching layer does not differentiate responses by critical request attributes such as tenant identifiers or scoped tokens. Because Rocket routes are composable and parameters are often passed as route guards or request guards, failing to include those scopes in the cache key can create subtle poisoning scenarios where cached responses leak across security boundaries.

These issues are not inherent to Rocket or DynamoDB but stem from how caching decisions are made in the integration. The combination of a dynamic web framework and a NoSQL database that returns flexible schema data increases the importance of carefully designing cache keys and ensuring that authorization context is always considered when storing and retrieving cached items.

To remediate cache poisoning when using Rocket with DynamoDB, ensure cache keys incorporate authorization context and strictly validate all inputs used to construct them. Below are concrete patterns and code examples for Rocket applications integrating DynamoDB via the official AWS SDK for Rust.

Validate and normalize inputs before building cache keys

Always validate and normalize identifiers before using them in cache keys. Use strongly typed request guards and enforce constraints at the parameter level.

use rocket::serde::json::Json;
use rocket::request::Request;
use rocket::outcome::Outcome;
use aws_sdk_dynamodb::Client;
use std::sync::Arc;

#[rocket::async_trait]
impl<'r> rocket::request::FromRequest<'r> for AuthenticatedUser {
    type Error = ();

    async fn from_request(request: &'r Request<'_>) -> rocket::request::Outcome {
        // extract and validate user identity, e.g., from JWT
        // return Outcome::Success or Outcome::Failure(())
    }
}

#[get("/users/")]
async fn get_user(
    user_id: String,
    user: AuthenticatedUser,
    db: & rocket::State<Arc<Client>>
) -> Json<serde_json::Value> {
    // normalize and validate user_id (e.g., UUID format)
    let normalized_user_id = normalize_user_id(&user_id);
    let cache_key = format!("user:{}:tenant:{}", normalized_user_id, user.tenant_id);
    // proceed with DynamoDB call using a parameterized query
    let item = fetch_user_from_dynamo(&db, &user.tenant_id, &normalized_user_id).await;
    Json(item)
}

fn normalize_user_id(input: &str) -> String {
    // basic example: ensure lowercase, trim, reject unexpected chars
    input.trim().to_lowercase()
}

Include tenant or user context in cache keys and query parameters

Ensure cache entries are scoped to the requesting tenant or user to prevent cross-user cache reads. Include tenant identifiers derived from authentication, not from unvalidated user input.

async fn fetch_user_from_dynamo(
    db: & Client,
    tenant_id: &str,
    user_id: &str
) -> serde_json::Value {
    let key = aws_sdk_dynamodb::model::PrimaryKey::from([
        ("PK", aws_sdk_dynamodb::model::AttributeValue::S(format!("USER#{}", user_id))),
        ("SK", aws_sdk_dynamodb::model::AttributeValue::S(format!("METADATA")))
    ]);
    let resp = db.get_item()
        .table_name("AppTable")
        .set_key(Some(key))
        .consistent_read(Some(true))
        .send()
        .await
        .unwrap();
    // deserialize and return
    serde_json::json!({})
}

By ensuring the cache key includes the tenant context and that the DynamoDB query uses parameterized key values, you reduce the risk of cache poisoning across users or tenants.

Do not cache sensitive or user-specific responses without strict scoping

If caching responses that include data retrieved from DynamoDB, differentiate cache entries by request scope, including tenant ID and user permissions. Avoid caching responses that contain sensitive fields unless the cache key incorporates all dimensions of the security context.

let cache_key = format!("resp:tenant:{}:user:{}:scope:{}", tenant_id, user_id, scope_hash);

Use this approach in combination with Rocket’s fairing or request guards to ensure that cache hits are only returned when the full request context matches the stored context.