Heap Overflow in Axum with Jwt Tokens

A heap overflow in an Axum service that handles JWT tokens typically arises when token payloads are deserialized into fixed-size buffers or when string operations on token claims do not enforce length limits. Axum is a Rust web framework and does not inherently introduce heap overflows, but the way developers integrate JWT parsing and buffer management can create conditions where oversized or maliciously crafted tokens lead to out-of-bounds writes in heap-allocated memory.

Consider a scenario where a developer reads a JWT token from an Authorization header and copies its claims into a fixed-length array or a custom buffer before validation. If the token payload contains a large claim value, such as a base64-encoded blob or an unusually long string in a registered claim (e.g., jti or a custom field), a naive copy operation can exceed the buffer capacity. This results in a heap-based buffer overflow because Rust’s standard library heap allocations may be resized without proper bounds checking in unsafe code paths, potentially corrupting adjacent memory.

Additionally, if the application uses third-party JWT crates that internally rely on heap-allocated structures and do not enforce strict size limits on parsed inputs, an attacker can supply a token with deeply nested JSON or extremely long strings to trigger excessive memory growth or overflow during deserialization. This can expose the unauthenticated attack surface that middleBrick scans, particularly under the Input Validation and Unsafe Consumption checks. Such vulnerabilities may allow an attacker to manipulate control flow or extract sensitive data from process memory, which would be reflected in the scan’s findings related to data exposure and execution anomalies.

In the context of middleBrick’s LLM/AI Security checks, a heap overflow in JWT handling could also facilitate prompt injection if token contents are used to construct dynamic prompts or log messages without sanitization. middleBrick’s active prompt injection probes would test whether oversized or malformed JWT tokens can be used to escape expected input boundaries and influence downstream behavior, which would be flagged under the BFLA/Privilege Escalation and Input Validation categories.

Using middleBrick’s CLI tool, a developer can quickly assess whether their Axum endpoint exhibits such risks by running middlebrick scan <url> and reviewing findings related to input handling and memory safety. The dashboard further tracks these findings over time, helping teams prioritize fixes before deploying changes via the GitHub Action or MCP Server integrations.

To remediate heap overflow risks when handling JWT tokens in Axum, enforce strict bounds on all token claims and avoid unsafe buffer operations. Use well-maintained crates such as jsonwebtoken and validate claim lengths before processing. Below is a secure example of JWT validation in Axum that limits payload size and uses typed structures to prevent unbounded memory operations.

use axum::{{
    async_trait, 
    extract::{FromRequest, Request},
    response::Response,
    Extension,
}};
use jsonwebtoken::{decode, Algorithm, DecodingKey, Validation};
use serde::{Deserialize, Serialize};
use std::convert::Infallable;
use std::fmt;

#[derive(Debug, Deserialize, Serialize)]
struct Claims {
    sub: String,
    exp: usize,
    // Limit custom claim size explicitly
    #[serde(deserialize_with = "crate::deserialize_limited_string")]
    custom_data: String,
}

mod deserialize_limited_string {
    use super::*;
    pub fn deserialize<'de, D>(deserializer: D) -> Result<String, D::Error>
    where
        D: serde::Deserializer<'de>,
    {
        let s = String::deserialize(deserializer)?;
        if s.len() > 1024 {
            return Err(serde::de::Error::custom("claim too long"));
        }
        Ok(s)
    }
}

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

#[tokio::main]
async fn main() {
    let app = axum::Router::new()
        .route("/protected", axum::routing::get(protected_handler));

    axum::Server::bind(&"0.0.0.0:3000".parse().unwrap())
        .serve(app.into_make_service())
        .await
        .unwrap();
}

async fn protected_handler(
    Extension(claims): Extension<Claims>,
) -> Response {
    // Safe: claims are validated and bounded
    format!("User: {}", claims.sub).into_response()
}

This example includes a custom deserialization function to limit string claim lengths, preventing unbounded heap allocation. It also ensures that the JWT library handles signature validation and expiration checks securely, reducing the risk of heap overflow through malformed inputs.

Additionally, configure middleBrick’s Pro plan for continuous monitoring and CI/CD integration via the GitHub Action to automatically fail builds if a scan detects input validation issues related to JWT tokens. The MCP Server can be used during development in IDEs to scan API endpoints in real time, providing immediate feedback on unsafe token handling patterns.