Prototype Pollution in Actix with Jwt Tokens

Prototype pollution in an Actix-based API that uses JWT tokens can occur when user-controlled data is merged into objects that later influence token creation, validation, or claims handling. While Actix itself does not mutate prototypes in the JavaScript sense, the term here refers to the extension or modification of application-level structures, such as configuration maps, claims containers, or session objects, through crafted input.

Consider an endpoint that accepts JSON payload fields and uses them to build or augment JWT-related data before signing. If the application performs a shallow merge of incoming properties into a claims map or options object, an attacker can inject keys such as __proto__, constructor, or other special properties that affect behavior when the claims are later processed. In Rust, this typically manifests as unexpected entries in a HashMap or struct fields being overwritten because the code iterates over raw key-value pairs and applies them without filtering.

When combined with JWT tokens, prototype pollution can lead to privilege escalation or token manipulation. For example, an attacker might inject a role or permissions claim into a mutable claims map. If the map is reused across requests or not properly isolated, the polluted claims may be serialized into a new token or used to bypass authorization checks. In Actix, this often happens when middleware or handlers share mutable state across threads or when request data is merged into configuration-like structures without strict schema validation.

Another scenario involves the deserialization of token metadata. If an Actix handler uses a serde_json::Value to extract dynamic fields from a request and then merges those fields into a base claims object using methods like as_object_mut, an attacker-controlled key can traverse or overwrite nested structures. Because JWT validation often depends on exact claim values, altered metadata can change how tokens are interpreted, potentially allowing unsigned tokens or tokens with modified scopes to be accepted.

Because middleBrick scans the unauthenticated attack surface, it can detect endpoints that reflect or store user input into token-related logic without proper sanitization. Findings may highlight missing input validation around claims fields, excessive data exposure in error messages, or unsafe consumption patterns where mutable structures are updated based on raw JSON. These issues map to common categories such as Input Validation and Unsafe Consumption in the OWASP API Top 10, and remediation focuses on strict schema enforcement and isolation of token handling logic.

To secure JWT token handling in Actix, ensure that all user input is validated against a strict schema and never merged into shared or mutable claim structures. Use strongly typed structures with serde deserialization and avoid dynamic merging of raw JSON into token-related objects.

Example of unsafe code that is vulnerable to prototype-like pollution:

use actix_web::{post, web, HttpResponse};
use serde_json::json;

#[post("/login")]
async unsafe_login_handler(input: web::Json) -> HttpResponse {
    let mut claims = serde_json::Map::new();
    claims.insert("sub".to_string(), json!("user123"));

    // Vulnerable: merging raw user input into claims
    for (k, v) in input.as_object().unwrap() {
        claims.insert(k.clone(), v.clone());
    }

    let token = encode(&Header::default(), &claims, &EncodingKey::from_secret("secret".as_ref())).unwrap();
    HttpResponse::Ok().body(token)
}

In this example, an attacker can send a payload like { "__proto__": "admin" } or { "role": "admin" }, and the fields will be directly inserted into the claims map, potentially altering token semantics.

Secure remediation uses a dedicated struct and explicit field mapping:

use actix_web::{post, web, HttpResponse};
use serde::{Deserialize, Serialize};
use jsonwebtoken::{encode, Header, EncodingKey};

#[derive(Debug, Deserialize, Serialize)]
struct LoginRequest {
    username: String,
    password: String,
}

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

#[post("/login")]
async fn secure_login_handler(form: web::Form) -> HttpResponse {
    let claims = Claims {
        sub: form.username.clone(),
        role: "user".to_string(),
    };

    let token = encode(
        &Header::default(),
        &claims,
        &EncodingKey::from_secret("secret".as_ref()),
    )
    .unwrap();

    HttpResponse::Ok().body(token)
}

This approach guarantees that only expected fields are used, and no attacker-controlled keys can influence the claims structure. For dynamic data that must be stored, validate and sanitize keys explicitly, and avoid reusing mutable maps across request handling.

middleBrick can identify endpoints where user input is directly merged into token-related logic by analyzing OpenAPI specs and runtime behavior. The scanner flags Input Validation and Unsafe Consumption findings, providing remediation guidance that aligns with secure coding practices for JWT usage in Actix.