Type Confusion in Axum with Cockroachdb

Type confusion in an Axum service that interacts with CockroachDB typically occurs when application code deserializes request or database data into an incorrect Rust type. Because Axum leaves deserialization choices to the developer and CockroachDB returns column values based on SQL types, mismatches between what the code expects and what the database provides can lead to runtime type errors or unsafe behavior. This becomes a security-relevant issue when an attacker can influence the shape or type of stored data, for example by inserting JSON with alternate structures into a JSONB column or by triggering polymorphic behavior through crafted query inputs.

Consider a scenario where an endpoint accepts a JSON payload and stores it in a CockroachDB JSONB column, later retrieving it and attempting to deserialize it into a fixed Rust struct. If the stored JSON varies across rows or is supplied by an attacker, blindly calling serde_json::from_value on the column value can produce type confusion: numeric fields may arrive as strings, nested objects may be missing, or new fields may appear. Axum extractors such as Json<T> or manual deserialization via serde do not enforce strict schema evolution, so a mismatch between the runtime representation and the expected type can cause panics or information leakage.

Another vector involves integer or string type confusion when application code interprets database-supplied identifiers or enums. CockroachDB adheres to PostgreSQL wire types, so an INT column is reliably an integer, but if the application layer misinterprets an enum-like integer as a different category (for example treating a permission flag as a user role), logic errors can arise. In Axum, this often manifests in route handlers that pattern-match on numeric status or role values without validating the full range of possibilities. An attacker who can indirectly influence stored values through other interfaces might cause the handler to follow an unintended branch, leading to privilege escalation or unauthorized data access patterns that align with BOLA/IDOR or privilege escalation checks in middleBrick scans.

The combination of Axum’s flexible extractor ecosystem and CockroachDB’s rich SQL+JSON typing increases the surface for type confusion if deserialization is not strict and validated. middleBrick’s checks for Input Validation and Unsafe Consumption are designed to surface these risks by validating runtime behavior against expected schemas, while the LLM/AI Security probes can detect whether prompt or logic injection could coax a handler into type-unsafe paths. Because the scanner operates without credentials in black-box mode, it can highlight endpoints where type confusion may be triggered through manipulated payloads or stored data, enabling developers to tighten deserialization logic before deployment.

Remediation centers on strict schema enforcement, explicit type conversions, and defensive deserialization. Prefer strongly typed structures over raw JSON when the shape is predictable, and validate all inputs before they interact with the database or are deserialized into domain models. The following examples illustrate secure patterns for Axum routes communicating with CockroachDB.

1. Use strongly typed structures with serde and validate required fields instead of relying on loosely typed JSON:

use axum::{routing::post, Router};
use serde::{Deserialize, Serialize};
use sqlx::postgres::PgPoolOptions;
use sqlx::FromRow;

#[derive(Debug, Deserialize, Serialize, FromRow)]
struct UserRecord {
    id: i32,
    name: String,
    role: String,
}

async fn create_user(
    axum::extract::Json(payload): axum::extract::Json,
) -> Result, (axum::http::StatusCode, String)> {
    // Strict validation instead of blind deserialization
    let id = payload.get("id")
        .and_then(|v| v.as_i64())
        .ok_or_else(|| (axum::http::StatusCode::BAD_REQUEST, "missing or invalid id".to_string()))? as i32;
    let name = payload.get("name")
        .and_then(|v| v.as_str())
        .ok_or_else(|| (axum::http::StatusCode::BAD_REQUEST, "missing or invalid name".to_string()))?
        .to_string();
    let role = payload.get("role")
        .and_then(|v| v.as_str())
        .ok_or_else(|| (axum::http::StatusCode::BAD_REQUEST, "missing or invalid role".to_string()))?
        .to_string();

    let pool = PgPoolOptions::new()
        .connect(&std::env::var("DATABASE_URL").unwrap_or_else(|_| "postgres://user:pass@localhost/db".into()))
        .await
        .map_err(|e| (axum::http::StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;

    sqlx::query_as!(UserRecord,
        "INSERT INTO users (id, name, role) VALUES ($1, $2, $3) RETURNING id, name, role",
        id,
        name,
        role
    )
    .fetch_one(&pool)
    .await
    .map_err(|e| (axum::http::StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;

    Ok(axum::Json(serde_json::json!({
        "status": "ok",
        "id": id
    })))
}

App::new().route("/users", post(create_user));

2. When working with JSONB columns, enforce schema validation on read and write using serde and reject unexpected shapes:

use serde_json::Value;

async fn get_user_metadata(
    pool: &sqlx::PgPool,
    user_id: i32,
) -> Result {
    let row: (Value,) = sqlx::query_as("SELECT metadata FROM users WHERE id = $1")
        .bind(user_id)
        .fetch_one(pool)
        .await
        .map_err(|e| (axum::http::StatusCode::INTERNAL_SERVER_ERROR, e.to_string()))?;

    // Validate expected structure instead of passing through raw JSON
    let metadata = &row.0;
    if metadata.get("email").and_then(Value::as_str).is_none() {
        return Err((axum::http::StatusCode::BAD_REQUEST, "invalid metadata schema".to_string()));
    }
    // Further strict checks can be applied here
    Ok(metadata.clone())
}

3. Avoid interpreting numeric enums without range checks; map database integers to known variants explicitly:

#[derive(Debug, PartialEq)]
enum Permission {
    Read = 1,
    Write = 2,
    Admin = 3,
}

impl TryFrom for Permission {
    type Error = (axum::http::StatusCode, String);

    fn try_from(value: i32) -> Result {
        match value {
            1 => Ok(Permission::Read),
            2 => Ok(Permission::Write),
            3 => Ok(Permission::Admin),
            _ => Err((axum::http::StatusCode::BAD_REQUEST, "invalid permission level".to_string())),
        }
    }
}

async fn set_permission(
    axum::extract::Json(body): axum::extract::Json,
) -> Result, (axum::http::StatusCode, String)> {
    let perm_val = body.get("permission")
        .and_then(Value::as_i64)
        .ok_or_else(|| (axum::http::StatusCode::BAD_REQUEST, "permission must be an integer".to_string()))? as i32;
    let _perm = Permission::try_from(perm_val)?;
    // proceed with safe usage
    Ok(axum::Json(()))
}

These patterns reduce the risk of type confusion by ensuring that database values are validated and that deserialization fails safely when types do not match expectations. They align with remediation guidance that can be surfaced by middleBrick’s checks such as Input Validation, Property Authorization, and LLM/AI Security, especially when stored data is influenced by external sources.