Rapid Development of Spam Trap Detection in Go for QA Under Pressure

#go #qa #spam

In the fast-paced environment of quality assurance and email deliverability, avoiding spam traps is critical to maintaining sender reputation and compliance. As a Lead QA Engineer, faced with a looming deadline, I had to develop a reliable solution in Go that could identify potential spam traps within our mailing lists efficiently. This post shares the approach, challenges, and the Go implementation that helped us meet our tight schedule.

The Challenge

Spam traps are email addresses set up by ISPs or anti-spam organizations to catch poorly maintained mailing lists. If your system inadvertently sends emails to these addresses, your IP could be blacklisted, impacting deliverability. Our task was to create a tool capable of scanning large lists, flagging suspected spam traps based on defined heuristics, all within a constrained timeframe.

Key Requirements

Fast performance over millions of email addresses
Minimal false positives
Easy integration with existing QA pipelines
Clear, maintainable code

Given the performance demands, Go emerged as the optimal choice due to its concurrency support and compiled efficiency.

Approach

The core of our detection logic relied on common spam trap indicators: domains known for spam traps, timeout-based checks, and syntax validation. To begin, I curated a list of known spam trap domains from industry sources, which served as a baseline.

In Go, I implemented concurrent checks to expedite processing. The main components included:

Email syntax validation
Domain verification against spam trap list
DNS MX record checks for domain existence

Sample Code

package main

import (
    "fmt"
    "net"
    "regexp"
    "sync"
)

// Regular expression for simple email syntax validation
var emailRegex = regexp.MustCompile(`^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$`)

// Known spam trap domains
var spamTrapDomains = map[string]bool{
    "spamdoma.in": true,
    "trapdomain.org": true,
    // Add more as needed
}

// validateEmailSyntax checks email format
func validateEmailSyntax(email string) bool {
    return emailRegex.MatchString(email)
}

// isSpamTrapDomain checks if domain is a known spam trap
func isSpamTrapDomain(domain string) bool {
    return spamTrapDomains[domain]
}

// checkDomainExistence verifies MX records
func checkDomainExistence(domain string) bool {
    mxRecords, err := net.LookupMX(domain)
    if err != nil || len(mxRecords) == 0 {
        return false
    }
    return true
}

func processEmail(email string, wg *sync.WaitGroup, results chan<- string) {
    defer wg.Done()
    if !validateEmailSyntax(email) {
        return
    }
    domain := email[strings.LastIndex(email, "@")+1:]
    if isSpamTrapDomain(domain) {
        results <- email + " - suspected spam trap (known domain)"
        return
    }
    if !checkDomainExistence(domain) {
        results <- email + " - invalid domain"
        return
    }
    // Further heuristics can be added here
}

func main() {
    emails := []string{"user1@example.com", "bademail@spamdoma.in", "invalid@@domain.com"}
    var wg sync.WaitGroup
    results := make(chan string, len(emails))

    for _, email := range emails {
        wg.Add(1)
        go processEmail(email, &wg, results)
    }
    wg.Wait()
    close(results)

    for res := range results {
        fmt.Println(res)
    }
}

This code demonstrates parallelized email validation and spam trap detection, allowing rapid scanning of large datasets. Additional heuristics, such as checking email engagement and TTL analysis, could further enhance accuracy.

Lessons Learned

Concurrency is vital for performance under tight deadlines.
Precompiled lists and simple regexes speed up processing.
Modular design facilitates future enhancements.

In conclusion, leveraging Go's concurrency features and a systematic approach enabled us to deliver a functional spam trap detection tool within the deadline, significantly reducing our risk of blacklistings. This experience underscores the importance of choosing the right tools and techniques for rapid, reliable solutions in QA environments.