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In a recent bug bounty program, a significant finding was made during reconnaissance: a file named `js[.]zip` containing all JavaScript files of a subdomain. This discovery led to the identification of 391 URLs/endpoints, many of which belonged to an administration application that would have otherwise remained hidden.
The key takeaways from this discovery:
- Use targeted wordlists—generic lists may miss critical paths. For example, a folder named `CompanyNamesrc` required a customized approach.
- Automate aggressively—while automation won’t always find bugs directly, it saves time and uncovers hidden attack surfaces.
- Fuzz everything—unexpected files (like `.zip` archives) can reveal valuable endpoints.
You Should Know: Practical Commands and Techniques
1. Automated Recon with `ffuf`
Fuzz directories and files using a custom wordlist:
ffuf -w custom_wordlist.txt -u https://target.com/FUZZ -t 50 -rate 10
– -t: Threads for faster scanning.
– -rate: Requests per second (adjust to avoid rate-limiting).
2. Decompressing and Analyzing Files
Extract and search for endpoints in a `.zip` file:
unzip js.zip -d extracted_js grep -rE "https?://[^\"]+" extracted_js/
3. Generating Targeted Wordlists
Modify existing wordlists to include target-specific patterns:
sed 's/^/CompanyName/' default_wordlist.txt > custom_wordlist.txt
4. Slow Fuzzing for Rate-Limited Targets
Use `-p` (delay) in `ffuf` to avoid blocks:
ffuf -w wordlist.txt -u https://target.com/FUZZ -p "0.5s"
5. Broken Access Control Testing
Check endpoints for misconfigured permissions with `curl`:
curl -X GET https://target.com/admin_endpoint -H "Cookie: admin_session=123"
6. Automating with Python
A script to extract URLs from JS files:
import re
with open("file.js", "r") as f:
urls = re.findall(r'https?://[^\s<>"]+', f.read())
print(urls)
What Undercode Say
Recon and fuzzing are foundational in bug hunting. The discovery of `js[.]zip` underscores the importance of:
– Custom wordlists (e.g., `CompanyName` variants).
– Toolchains (ffuf, grep, unzip).
– Persistence—slow fuzzing still yields results.
For deeper analysis:
Expected Output:
A structured recon workflow combining automation, targeted fuzzing, and manual validation to uncover hidden endpoints and vulnerabilities.
Note: Telegram/WhatsApp URLs and non-IT comments were removed.
References:
Reported By: Martinmarting Reason – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
