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Introduction:
In a recent wave of ethical hacking, security researcher Ahmed Hossny disclosed six distinct “Information Disclosure” vulnerabilities targeting the telecommunications giant Comcast. While often overshadowed by more glamorous remote code execution flaws, information disclosure represents a critical threat to enterprise security, often serving as the first step in a kill chain that leads to a full-scale breach. These vulnerabilities, typically found in misconfigured servers, exposed APIs, or verbose error messages, can leak sensitive data ranging from user credentials to internal network topologies. This article dissects the anatomy of these disclosures, providing a technical roadmap for bug bounty hunters to find similar flaws and for blue teams to harden their assets against data leaks.
Learning Objectives:
- Understand the various classifications and business impacts of Information Disclosure vulnerabilities.
- Master reconnaissance techniques to identify exposed .git repositories, configuration files, and cloud storage buckets.
- Learn to analyze JavaScript files and API responses for hardcoded secrets and sensitive data leaks.
- Implement mitigation strategies, including HTTP header hardening and cloud security group configuration.
You Should Know:
- The Low-Hanging Fruit: Exposed .git and Configuration Files
One of the most common sources of information disclosure is the accidental exposure of version control systems or backup files. Attackers scan for paths like `/.git/config` or backup files with extensions like.bak,.old, or~. If a developer deploys the `.git` folder to the production server, an attacker can reconstruct the entire source code, including database credentials and API keys.
Step‑by‑step guide for Recon (Linux):
Use `ffuf` or `gobuster` to fuzz for common sensitive directories.
Fuzzing for hidden directories and files ffuf -u https://target.com/FUZZ -w /usr/share/wordlists/dirb/common.txt -fc 403,404 Specifically check for .git disclosure curl -s https://target.com/.git/config | grep -i "repository" If accessible, use 'git-dumper' to download the repository git-dumper https://target.com/ ./dumped-repo/
Mitigation (Windows/IIS):
On Windows Servers running IIS, ensure hidden or system files are blocked.
Add deny rule in web.config to block .git access <configuration> <system.webServer> <security> <requestFiltering> <hiddenSegments> <add segment=".git" /> </hiddenSegments> </requestFiltering> </security> </system.webServer> </configuration>
- Source Code Digging: Secrets in JavaScript Files (JS Mapping)
Modern web applications are heavy with JavaScript. Developers often embed API keys, Firebase URLs, or internal endpoints directly into the JS code for front-end functionality. Tools like `LinkFinder` can extract these endpoints, while manual inspection can reveal hardcoded credentials.
Step‑by‑step guide: Extracting Endpoints (Linux/CLI)
- Fetch the main JS files using `waybackurls` or
gau.gau target.com | grep -i ".js$" | tee js-files.txt
- Download a specific JS file and grep for sensitive keywords.
wget https://target.com/static/js/main.chunk.js cat main.chunk.js | grep -E "(apiKey|secret|token|firebase|aws)"
- Use `jq` to parse exposed JSON configurations if found.
If a JSON object is exposed echo '{"config":{"apiKey":"AIzaSyA-s9n..."}}' | jq '.config.apiKey' -
Cloud Leakage: Open S3 Buckets and Azure Blobs
Comcast, like most enterprises, utilizes cloud storage. Misconfigured cloud buckets allow unauthenticated users to list, read, and sometimes write files. Tools like `s3scanner` check for public buckets.
Step‑by‑step guide: Auditing Cloud Storage
- Enumerate bucket names: Generate permutations based on the domain (e.g.,
comcast-assets,comcast-backup).
2. Scan for open buckets (Linux):
Install s3scanner git clone https://github.com/sa7mon/S3Scanner.git cd S3Scanner pip install -r requirements.txt Scan a list of potential bucket names python3 s3scanner.py --bucket-file buckets.txt --out-file open-buckets.csv
3. Check Azure Blobs (Windows/PowerShell):
Use AzCopy to list blobs if anonymous access is enabled $account = "comcaststorage" $container = "publicfiles" azcopy list "https://$account.blob.core.windows.net/$container?<SAS-token-if-any>"
4. API Endpoint Analysis: Verbose Error Messages
APIs often return stack traces or internal server paths when fed unexpected input. A simple SQL injection payload might not extract data but could trigger a detailed 500 error revealing the database type or file structure.
Step‑by‑step guide: Triggering Disclosure via API
Use `curl` to manipulate HTTP verbs and headers.
1. Change the HTTP method
curl -X PUT https://api.comcast.com/user/profile -H "Content-Type: application/json" -d "{}"
<ol>
<li>Send malformed JSON
curl -X POST https://api.comcast.com/billing/invoice -H "Content-Type: application/json" -d "{badjson:}"</p></li>
<li><p>Use Path Traversal in parameters
curl "https://api.comcast.com/download?file=../../../../etc/passwd"</p></li>
<li><p>Check for DEBUG headers
curl -I -H "X-Forwarded-For: 127.0.0.1" https://api.comcast.com/admin
5. HTTP Header Analysis: Fingerprinting and Leaks
Information disclosure isn’t always in the body; sometimes it’s in the headers. Server versions (e.g., Apache/2.4.49), X-Powered-By headers, and verbose `Location` redirects can leak backend technologies vulnerable to specific exploits.
Step‑by‑step guide: Hardening Headers (NGINX/Apache)
Check current headers:
curl -I https://target.com
Remediation Commands:
- NGINX (Linux): Edit `/etc/nginx/nginx.conf`
server { listen 80; server_name localhost; Hide Nginx version server_tokens off; Remove X-Powered-By proxy_hide_header X-Powered-By; add_header X-Content-Type-Options "nosniff" always; } - Apache (Linux): Edit `.htaccess` or `httpd.conf`
ServerTokens Prod ServerSignature Off Header unset X-Powered-By
6. Exploiting IDOR for Mass Data Harvesting
Insecure Direct Object References (IDOR) are a subset of information disclosure. If a user can change an ID in the URL (/invoice/1234 to /invoice/1235) and view another user’s invoice, that’s an IDOR. Ahmed Hossny’s report likely included this type of logic flaw.
Step‑by‑step guide: Testing for IDOR (Burp Suite)
- Capture a request for a user-specific resource (e.g.,
GET /account/56789).
2. Send it to Burp Intruder.
- Set the numeric ID (
56789) as the payload position. - Use a payload set of sequential numbers (e.g., 1-1000).
- Analyze the response length. A response length different from the standard “Not Found” (403) indicates a valid, accessible resource belonging to another user.
7. The Human Element: Debug Parameters
Developers often leave debug parameters active in production. Parameters like ?debug=true, ?test=1, or `?dev=1` can force the application to output raw SQL queries, memory dumps, or configuration arrays.
Step‑by‑step guide: Fuzzing for Debug Params
Use `ffuf` with a custom parameter wordlist:
Create a debug_params.txt file containing: debug, test, dev, internal, trace, etc. ffuf -u "https://target.com/dashboard?FUZZ=1" -w debug_params.txt -fc 400,401,403 -ac
If `https://target.com/dashboard?debug=1` returns a verbose SQL query or an array of `$_SERVER` variables, you have successfully triggered an information disclosure.
What Undercode Say:
- Recon is King: The six vulnerabilities discovered were likely found through meticulous reconnaissance, not complex exploitation. Bug bounty hunters must prioritize automating the discovery of exposed `.git` folders, cloud buckets, and JS secrets before moving to active exploitation.
- Defense in Depth is Non-Negotiable: Information disclosure flaws are almost always configuration errors. Implementing automated CI/CD pipeline checks that scan for secrets in code and block deployments with `server_tokens` on would eliminate 90% of these issues.
- The Data is the Target: In the context of a telecom like Comcast, information disclosure can leak customer PII, billing details, or internal network architecture. This data is often more valuable to attackers than the ability to crash a server, as it enables highly targeted social engineering and identity theft.
Prediction:
As AI-powered coding assistants become more prevalent, we will see a surge in “AI-Hallucination” disclosures, where code assistants generate and developers accidentally commit non-existent but functional-looking internal API endpoints or placeholder secrets. Bug bounty programs will need to adapt their scopes to include these synthetic leaks. Furthermore, automated scanners powered by Large Language Models (LLMs) will soon be able to read exposed JavaScript not just for strings, but for logical context, identifying complex business logic flaws that lead to data disclosure, dramatically increasing the volume of valid, high-severity reports.
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IT/Security Reporter URL:
Reported By: Ahmed Hossny – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
