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Introduction:
Achieving 100 accepted bug bounties on a elite platform like Intigriti is a monumental feat that separates amateur hunters from professional security researchers. This milestone, as demonstrated by Mahfujur Rahman, is not a product of luck but of a meticulous, tool-driven methodology targeting common vulnerability classes across modern web applications. This article deconstructs the technical command-line arsenal essential for replicating such success, moving beyond theory into practical, repeatable execution.
Learning Objectives:
- Master core command-line tools for automated reconnaissance and vulnerability discovery.
- Learn to chain commands for efficient subdomain enumeration, endpoint discovery, and live threat detection.
- Develop a methodology for validating and testing common web application vulnerabilities at scale.
You Should Know:
1. The Foundation: Subdomain Enumeration & Asset Discovery
Subdomain discovery is the critical first step in expanding your attack surface. The following commands use subfinder, amass, and `assetfinder` to cast a wide net.
subfinder -d target.com -o subdomains.txt amass enum -passive -d target.com >> subdomains.txt assetfinder --subs-only target.com | tee -a subdomains.txt sort -u subdomains.txt -o final_subs.txt
Step-by-step guide: These commands perform passive subdomain enumeration. `subfinder` uses numerous public sources, `amass` leverages its vast data sources and certificates, and `assetfinder` pulls from similar datasets. The `sort -u` command removes duplicates, creating a clean, unique list for further probing. Always run these tools passively initially to avoid triggering alarms.
2. Probing for Live Hosts & Web Servers
A list of subdomains is useless without knowing which are live and hosting active web services. `httpx` is the industry standard for this.
cat final_subs.txt | httpx -silent -ports 80,443,8080,8443 -tech-detect -title -status-code -o live_targets.txt
Step-by-step guide: This command takes the list of subdomains and probes them for HTTP/HTTPS services on common web ports. The `-tech-detect` flag identifies the technology stack (e.g., WordPress, React, Nginx), `-title` extracts the page title, and `-status-code` records the HTTP response code. The output provides a curated list of viable targets for deeper inspection.
3. Unearthing Hidden Endpoints & Parameters
Critical vulnerabilities often lie in hidden API endpoints and parameters. `gau` (GetAllURLs) and `waybackurls` fetch historical data, while `paramspider` extracts parameters.
gau target.com --o gau_output.txt waybackurls target.com >> gau_output.txt cat gau_output.txt | sort -u | grep -v ".woff|.ttf|.svg|.eot|.png|.jpeg|.jpg|.css|.ico" > filtered_urls.txt paramspider -d target.com -o params.txt
Step-by-step guide: `gau` and `waybackurls` pull URLs from sources like Common Crawl and the Wayback Machine. The `grep -v` command filters out common static file extensions to focus on dynamic pages. `paramspider` crawls the target to discover parameters (e.g., ?id=123), which are prime targets for SQLi and XSS testing.
4. Fuzzing for Critical Directory & File Discovery
Sensitive files like `.env` (containing API keys) or administrative panels are frequently left exposed. `ffuf` is a fast web fuzzer for discovering them.
ffuf -w /path/to/wordlist.txt -u https://target.com/FUZZ -mc 200,301,302,403 -t 100 ffuf -w /path/to/params.txt -u https://target.com/endpoint?FUZZ=test_value -fr "error" -t 100
Step-by-step guide: The first command fuzzes for directories and files. The `-mc` flag filters for “interesting” HTTP response codes. The second command fuzzes for parameters; the `-fr “error”` flag hides responses containing “error,” helping to find parameters that actually influence the application’s output, which are more likely to be vulnerable.
5. Automated Vulnerability Scanning with Nuclei
Nuclei allows you to run thousands of pre-built templates for known CVEs and misconfigurations at scale.
cat live_targets.txt | nuclei -t /path/to/nuclei-templates/ -severity low,medium,high,critical -o nuclei_results.txt
Step-by-step guide: This command pipes all live targets into nuclei, which runs a vast arsenal of community-powered vulnerability checks. The `-severity` flag allows you to focus on the most critical findings. This is essential for quickly identifying low-hanging fruit like exposed debug panels, default credentials, or known vulnerabilities in specific software versions.
6. JavaScript File Analysis for Hidden Secrets
Modern apps pack functionality into JS files, which can reveal API endpoints, secrets, and hidden parameters.
cat filtered_urls.txt | grep ".js$" | httpx -silent -status-code | awk '{print $1}' | tee js_files.txt
cat js_files.txt | while read url; do bash -c "echo -e '\n[bash]: $url' && curl -s $url" | grep -E "api\/|token|key|auth|endpoint|v1|v2"; done
Step-by-step guide: This pipeline first extracts all `.js` URLs from your list. Then, it checks they are live. Finally, it curls each file and greps for common keywords related to APIs and secrets. Manually reviewing these files often leads to the discovery of hardcoded API keys and internal endpoints.
- Validating SQL Injection (SQLi) & Cross-Site Scripting (XSS)
Automated tools catch easy bugs, but manual testing with custom payloads finds the complex ones.SQLi Probing with SQLmap sqlmap -u "https://target.com/v1/user?id=1" --batch --level=3 --risk=3 --dbs XSS Probing with a custom wordlist ffuf -w xss_payloads.txt -u "https://target.com/search?q=FUZZ" -fr "not found"
Step-by-step guide: For SQLi, `sqlmap` automates the process of detecting and exploiting injection flaws. The `–batch` flag runs non-interactively, while `–level` and `–risk` increase the depth of testing. For XSS, using `ffuf` with a list of curated payloads can quickly identify reflection points that warrant deeper manual investigation with a browser.
What Undercode Say:
- Automation is Non-Negotiable: The scale of modern bug bounty hunting makes manual reconnaissance impossible. Mastery of tool chaining via bash is the primary multiplier for a researcher’s efficiency.
- Data Trumps Speculation: A methodology driven by data—from subdomains, URLs, JS files, and parameters—provides a structured path to discovery, eliminating wasted time on dead ends. The 100-bug milestone is a direct result of a process that maximizes target data collection and analysis.
This approach underscores a shift from opportunistic hacking to systematic security research. The hunter’s role is evolving into that of a data engineer who curates and processes immense amounts of target information to pinpoint a handful of critical vulnerabilities. The commands listed are the levers used to manipulate this data pipeline.
Prediction:
The barrier to entry for effective bug bounty hunting will continue to lower as tooling becomes more sophisticated and integrated (e.g., AI-assisted recon), flooding platforms with more researchers. This will push top performers like Rahman to develop even more advanced, automated pipelines and focus increasingly on complex logic flaws and business-level vulnerabilities that automated scanners cannot find, further professionalizing the field. Platforms will likely respond with more targeted, private programs to manage signal-to-noise ratio.
🎯Let’s Practice For Free:
IT/Security Reporter URL:
Reported By: Mahfujwhh Bugbounty – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
