Regex Dos in Actix with Cockroachdb

A Regex Denial of Service (ReDoS) pattern occurs when a regular expression performs excessive backtracking on certain inputs. In an Actix web service that uses CockroachDB as the backend, this typically manifests in user-controlled data—such as request IDs, query parameters, or JSON fields—that is validated with a non-anchored, repetitive regex before the data is forwarded to CockroachDB. Because Actix processes many requests concurrently, a single malicious payload can consume significant CPU on the worker handling that request, increasing tail latencies and potentially starving other requests.

When the regex operates on strings that resemble database identifiers or SQL-like tokens destined for CockroachDB, the risk is compounded. For example, a route like /api/users/{id} might apply a regex such as ^(a+)+$ to the path parameter. An attacker can craft an input like aaaaa....!@#$% (a long sequence of a followed by a character that forces backtracking) that causes catastrophic backtracking. In a typical deployment, the Actix runtime uses asynchronous tasks; if the regex evaluation blocks the thread (or occupies a worker for the full 5–15 seconds scan window), the service becomes unresponsive to legitimate traffic.

If the validated input is later used in dynamic SQL for CockroachDB—such as building a query with string concatenation rather than parameterized statements—the regex validation step does not prevent SQL issues, but the ReDoS remains the immediate concern. middleBrick’s checks for Input Validation and Unsafe Consumption are designed to detect such regex patterns and flag the absence of parameterized queries, highlighting that even if the regex passes, the downstream database interaction should always use placeholders. The scanner does not assume an architecture internally, but it does correlate regex-heavy validation logic with database interaction patterns to prioritize findings with high severity.

For context, common vulnerable patterns include repeated groups without atomic groups or possessive quantifiers (e.g., (a+)+), optional overlapping alternatives (e.g., (a|aa)*), and missing boundary anchors that allow the engine to explore many paths. Because CockroachDB is often used in distributed systems where request volume is high, an exploitable regex in Actix can degrade the entire service faster than a single-threaded backend would reveal the issue during manual testing.

Remediation focuses on two areas: replacing vulnerable regexes with safe validation, and ensuring database interactions use parameterized queries. Below are concrete Actix snippets that demonstrate a secure approach.

1. Replace catastrophic regex with simple character checks

Instead of a complex regex to validate a numeric ID, use direct parsing and length checks. This removes backtracking entirely.

use actix_web::{web, HttpResponse, Result};

fn is_valid_user_id(candidate: &str) -> bool {
    // Allow only digits, with a reasonable length for CockroachDB INT/BIGINT ranges
    if candidate.len() < 1 || candidate.len() > 20 {
        return false;
    }
    candidate.chars().all(|ch| ch.is_ascii_digit())
}

async fn get_user(web::Path(id): web::Path<String>) -> Result<HttpResponse> {
    if !is_valid_user_id(&id) {
        return Ok(HttpResponse::BadRequest().body("Invalid user identifier"));
    }
    // Use parameterized query with a CockroachDB Rust driver (e.g., cockroach-client or sqlx)
    // Example with sqlx (pseudocode):
    // let row = pool.query_one("SELECT username FROM users WHERE id = $1", &[&id]).await?;
    Ok(HttpResponse::Ok().body(format!("User: {}", id)))
}

2. Use parameterized queries instead of string building for CockroachDB

Even if input passes regex or parsing, always use placeholders to avoid SQL injection and remove any incentive for fragile regex-based sanitization.

// Example using sqlx with PostgreSQL-compatible CockroachDB
use sqlx::postgres::PgPoolOptions;

async fn safe_fetch(pool: &sqlx::PgPool, user_id: &str) -> sqlx::Result<()> {
    // The driver ensures proper encoding; no regex is required for SQL safety
    let row: (String,) = pool
        .query_one(
            "SELECT username FROM users WHERE id = $1",
            &[&user_id],
        )
        .await?;
    // Process row
    Ok(())
}

3. If regex is required, use atomic groups or possessive quantifiers

When regex is unavoidable, restructure patterns to prevent exponential backtracking. For example, replace (a+)+ with a++ (possessive) or use an explicit loop with early exit.

// Vulnerable: (a+)+ can cause exponential time on certain inputs
// Safer: a++ (possessive) or a non-regex loop
fn contains_only_a(input: &str) -> bool {
    input.chars().all(|c| c == 'a')
}

// If you must use regex, anchor and simplify:
use regex::Regex;
let re = Regex::new(r"\Aa++\z").expect("valid pattern");
assert!(re.is_match("aaaa"));

4. Apply middleware to reject suspiciously long or repetitive paths

In Actix, add a lightweight guard that rejects requests where path segments contain highly repetitive substrings that commonly trigger ReDoS.

use actix_web::dev::ServiceRequest;
use actix_web::Error;

fn reject_repetitive_segments(req: &ServiceRequest) -> Result<(), Error> {
    if let Some(path) = req.path().split('/').find(|seg| {
        // naive repetition check: more than 30 repeated single-char groups
        seg.chars().collect::<Vec<char>>().windows(5).any(|w| w.windows(2).all(|w| w[0] == w[1]))
    }) {
        return Err(actix_web::error::ErrorBadRequest("Suspicious input"));
    }
    Ok(())
}

These steps ensure that Actix routes interacting with CockroachDB remain robust against Regex Dos while maintaining correctness and performance. middleBrick’s scans can highlight the original vulnerable patterns so you can prioritize refactoring before they impact availability.