Prototype Pollution in Axum with Jwt Tokens

Prototype pollution in Axum involving JWT tokens typically arises when application code deserializes untrusted claims or merges them into mutable objects used during token construction or validation. Axum, a web framework for Rust, does not inherently introduce this issue, but patterns such as dynamically inserting validated claims into a claims struct or using serde_json::Value to forward claims into downstream logic can expose object prototype mutation risks in Rust when combined with JavaScript interoperability or unsafe deserialization practices.

Consider a scenario where an endpoint accepts an authorization header containing a JWT token, decodes the payload without strict schema validation, and then merges the claims into a serde_json::Value that is later used to build a response or pass into a business logic function. An attacker may supply crafted JSON objects with keys like __proto__, constructor, or other property names that affect object behavior in environments where the data is interpreted, such as when claims are serialized to JSON for external consumption or used in a context that interacts with WebAssembly or Node.js via FFI. Although Rust’s type system prevents classical prototype pollution found in dynamic languages, the resulting data can still lead to authorization bypass or logic manipulation if the merged claims influence access control decisions or are reflected in outputs without proper validation.

When JWT tokens are processed in Axum handlers using generic extraction patterns, the risk emerges if the handler does not enforce strict claim whitelisting and instead relies on dynamic merging. For example, using jsonwebtoken crate’s decode function with a generic Validation may accept unexpected fields if the validation parameters are misconfigured, and subsequent merging into application state or session objects can lead to unintended behavior. This becomes particularly relevant when the token payload is used to construct permissions or roles that are later evaluated in middleware, where polluted properties might escalate privileges or bypass intended constraints. Moreover, if Axum routes expose token introspection endpoints that echo decoded claims without normalization, an attacker can probe for side effects by injecting properties that alter serialization formats or influence logging behavior, indirectly affecting security-sensitive flows.

To identify such issues, middleBrick performs OpenAPI/Swagger spec analysis and aligns runtime findings with the OWASP API Top 10, specifically highlighting broken object level authorization when token claims are improperly handled. The scanner executes active tests against unauthenticated endpoints, checking whether injected properties propagate through JWT processing pipelines and whether they affect authorization outcomes. Findings include indicators of insecure deserialization patterns and missing claim constraints, mapped to compliance frameworks such as SOC2 and GDPR. Because Axum applications often integrate with JavaScript-heavy frontends or microservices that consume token data, ensuring strict schema validation and avoiding dynamic claim merging is essential to mitigate prototype pollution related risks in this context.

Remediation focuses on strict deserialization, claim validation, and avoiding dynamic merging when working with JWT tokens in Axum. Use the jsonwebtoken crate with a strongly typed claims struct and enforce validation parameters that reject unknown fields. This prevents attacker-controlled properties from affecting application logic or being reflected in downstream outputs.

Example of a secure Axum handler with typed JWT validation:

use axum::{routing::get, Router};
use jsonwebtoken::{decode, Algorithm, DecodingKey, Validation, TokenData};
use serde::{Deserialize, Serialize};

#[derive(Debug, Serialize, Deserialize, Clone)]
struct Claims {
    sub: String,
    role: String,
    exp: usize,
}

async fn validate_token(header_auth: &str) -> Result {
    let token = header_auth.trim_start_matches("Bearer ");
    let validation = Validation::new(Algorithm::HS256);
    decode<Claims>(token, &DecodingKey::from_secret("secret".as_ref()), &validation)
}

async fn profile_handler(authorization: Option<axum::extract::Header<axum::http::header::AUTHORIZATION>>) -> Result<String, (axum::http::StatusCode, String)> {
    let auth = authorization.ok_or((axum::http::StatusCode::UNAUTHORIZED, "Missing authorization header".to_string()))?;
    let token_data = validate_token(auth.as_ref()).map_err(|e| (axum::http::StatusCode::UNAUTHORIZED, e.to_string()))?;
    let claims = token_data.claims;
    Ok(format!("User: {}, Role: {}", claims.sub, claims.role))
}

fn app() -> Router {
    Router::new().route("/profile", get(profile_handler))
}

This approach ensures that only expected fields are accepted and that tokens with extra properties are rejected during decoding. The Validation struct can be further tightened by setting leeway and required claims to prevent token misuse.

Additionally, avoid passing raw token payloads into serde_json::Value or any mutable structures that could be exposed in logs or error messages. Instead, map claims directly to domain models and enforce role-based access control at the handler or middleware level. middleBrick’s CLI tool can be used to scan Axum endpoints and verify that JWT validation logic does not include permissive field acceptance, providing JSON output that highlights insecure patterns and maps them to the relevant security checks.

For continuous protection, the Pro plan’s GitHub Action can be integrated to fail builds if risk scores degrade, ensuring that any changes to token handling maintain strict schema compliance. The MCP Server allows developers to run scans from their IDE while working on Axum routes, embedding security checks directly into the coding workflow without requiring separate tooling setup.