Out Of Bounds Write in Axum with Jwt Tokens

An Out Of Bounds Write occurs when data is written to a memory location outside the intended allocation. In Axum, this risk can emerge in handling layers when JWT tokens are parsed and their claims are mapped into structures without strict length or bounds enforcement. Although Axum itself does not perform memory operations directly, the downstream Rust ecosystem crates used to decode and validate JWTs may interact with buffers that, if improperly managed, can expose out-of-bounds behavior through unsafe code or unchecked collections.

Consider a scenario where a developer deserializes a JWT payload into a custom claims structure and then copies user-controlled claim values (such as a sub or custom metadata fields) into fixed-size buffers or vectors without validating length. For example, if a header or payload field is expected to be a short string but an attacker provides an extremely long string, and that value is copied into a collection with an unchecked reserve or extend call, the internal buffer may be resized in an uncontrolled way. This pattern can lead to memory corruption when integrated with FFI or unsafe blocks that interface with C libraries for cryptographic operations, even though the unsafe path is typically hidden within the JWT library implementation.

In Axum, this often surfaces in middleware or extractors that process JWT tokens. If middleware reads a bearer token, decodes it using a crate like jsonwebtoken, and then maps claims into a structure that later feeds into business logic with unchecked indexing or buffer-like collections, the unchecked propagation of claim sizes can result in out-of-bounds conditions during later processing phases. For instance, if a developer assumes a claim will have a bounded number of elements (e.g., a list of roles) and does not validate the length before indexing, an oversized claim could cause reads or writes beyond allocated memory when the data is used in subsequent operations, such as constructing response buffers or serialization buffers.

Real-world relevance is heightened when JWT tokens carry large custom claims or when tokens are accepted from unauthenticated sources as part of an unauthenticated attack surface, a key testing area for security scanners. Attack patterns that exploit weak validation on input size mirror general buffer overflow techniques, adapted to the language runtime where memory safety depends on correct use of collections and bounds checks. The specific combination of Axum's extractor flexibility and JWT token variability increases the importance of validating and sanitizing all incoming claims before use.

To detect such issues, security scanning evaluates whether JWT-related parsing paths in Axum applications adequately constrain input sizes, enforce schema validation, and avoid unsafe propagation of unchecked data. Findings highlight missing length checks on claims, overly permissive deserialization configurations, and risky usage patterns when integrating with cryptographic libraries, all of which can contribute to an elevated security risk score if left unaddressed.

Remediation focuses on strict validation of JWT claims, using bounded data structures, and avoiding unchecked operations when handling token payloads in Axum. Developers should define precise claim structures with explicit size constraints and validate all incoming values before use. Below are concrete code examples that demonstrate secure handling of JWT tokens in Axum.

First, define a claims structure with bounded collections and use strong deserialization rules:

use jsonwebtoken::{decode, Algorithm, DecodingKey, Validation};
use serde::{Deserialize, Serialize};

#[derive(Debug, Serialize, Deserialize)]
struct Claims {
    sub: String,
    // Limit roles to a reasonable fixed size to prevent unbounded growth
    roles: [String; 5],
    exp: usize,
}

fn validate_token(token: &str) -> Result<Claims, jsonwebtoken::errors::Error> {
    let validation = Validation::new(Algorithm::HS256);
    let token_data = decode::<Claims>(token, &DecodingKey::from_secret("secret".as_ref()), &validation)?;
    Ok(token_data.claims)
}

This approach enforces a fixed-size array for roles, preventing uncontrolled memory growth. If variable-length lists are necessary, apply explicit length checks before processing:

fn process_claims(claims: &Claims) -> Result<(), &'static str> {
    // Enforce a maximum length on roles at runtime
    if claims.roles.len() > 5 {
        return Err("roles claim exceeds maximum length");
    }
    // Safe indexing is now guaranteed within bounds
    for role in &claims.roles {
        // business logic here
    }
    Ok(())
}

In Axum extractors, validate and clone only necessary fields, avoiding direct use of unchecked user input:

use axum::extract::Extension;
use jsonwebtoken::decode;

async fn jwt_middleware(
    Extension(state): Extension<AppState>,
    header: axum::http::Header<axum::http::header::AUTHORIZATION>
) -> Result<impl axum::response::IntoResponse, (axum::http::StatusCode, String)> {
    let token = header
        .to_str()
        .map_err(|_| (axum::http::StatusCode::BAD_REQUEST, "Invalid header".to_string()))?
        .strip_prefix("Bearer ")
        .ok_or_else(|| (axum::http::StatusCode::BAD_REQUEST, "Missing Bearer prefix".to_string()))?;

    let claims = validate_token(token).map_err(|e| {
        (axum::http::StatusCode::UNAUTHORIZED, format!("Invalid token: {:?}", e))
    })?;

    // Safe usage after validation
    let _user_id = claims.sub;
    // proceed with request handling
    Ok(axum::http::StatusCode::OK)
}

Additionally, configure the jsonwebtoken validation to reject tokens with unexpected algorithms and enforce strict audience and issuer checks to reduce the attack surface:

let mut validation = Validation::new(Algorithm::HS256);
validation.validate_exp = true;
validation.validate_nbf = true;
validation.audience = Some(vec!["myapp".to_string()]);
validation.issuer = Some(vec!["trusted-issuer".to_string()]);

By combining typed claims, bounded collections, and runtime length validation, developers using Axum can mitigate out-of-bounds write risks associated with JWT token handling while maintaining compatibility with standard Rust security practices.