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Validates the existence of registered accounts across social & shopping platforms and extracts rich identity intelligence (Names, Photos, IDs).

Project description

Aarya (आर्य)

Email address to digital footprint for OSINT

PyPI version License: GPL v3 PyPI Downloads

Aarya is an OSINT tool that validates the existence of email addresses across social media, shopping, and professional platforms (e.g. Instagram, Amazon, Spotify) and extracts rich metadata like Google Map contributions, reviews and account creation dates for proton mail.

Aarya Demo

🚀 Features

  • Deep Analysis: Goes beyond simple "Yes/No" results to extract rich metadata like Google Maps reviews, Profile Pictures, Gaia IDs, and ProtonMail key creation dates.
  • Full Visibility: Reports positive hits, negative results, rate limits, and errors explicitly so you never miss a detail.
  • Smart Stealth: Automatically fetches the latest real-world User-Agents from the web to bypass simple bot detection filters.
  • Elegant UI: Professional, minimalist CLI design with responsive tables and clean link wrapping.

⚠️ Disclaimer

Aarya is designed for educational purposes, authorized security research, and personal digital footprint analysis only.

The developers are not responsible for any misuse of this tool. Scanning email addresses that do not belong to you or without the owner's explicit consent may violate privacy laws or platform Terms of Service in your jurisdiction. Use responsibly.

📦 Installation

Option 1: Install via PyPI (Recommended)

It is recommended to use a virtual environment to prevent conflicts.

Linux/macOS:

python -m venv .venv
source .venv/bin/activate
pip install aarya

Windows:

python -m venv .venv
.venv\Scripts\activate
pip install aarya

Option 2: Install from Source (Development)

If you want the latest features or updates directly from the repository:

git clone https://github.com/forshaur/aarya.git
cd aarya
pip install .

🛠 Usage

Basic Scan:

aarya target@example.com

Save Results:

aarya target@example.com -o results.json

🔍 Use Cases in Recon & Intel

1. Verification & Validation

Confirm if a target email is active. A "ghost" email (no accounts anywhere) is a high-risk indicator for fraud or burner accounts, whereas an email with established accounts verifies the identity exists.

2. Social Engineering Context

Aarya helps Red Teamers map the digital footprint of a target. Knowing a target uses Duolingo or Wattpad allows for highly tailored phishing pretexts (e.g., "Your Duolingo streak is in danger" vs generic corporate emails).

3. Identity Correlation

By extracting unique identifiers like the Google Gaia ID or ProtonMail public key date, Aarya helps correlate an email address with real-world timelines, locations, and other digital identities across the web.

4. Credibility of Credential Reuse (Post-Exploitation)

If a target's password is compromised (via phishing or a data breach) for one verified platform, Aarya provides a precise roadmap of other active services where that same password might be reused, highlighting critical risks for credential stuffing attacks.

5. Corporate OpSec Auditing

Security teams can scan corporate email domains to detect "Shadow IT" or policy violations. Discovering that an employee used their official name@company.com address to sign up for Instagram or Amazon highlights potential attack surfaces and credential leakage risks.

6. OSINT Pivot Points

Aarya acts as a signpost for deeper investigation. A confirmed Google account signals an investigator to search for public Maps reviews or Photos. A confirmed Instagram account invites a search for public profile associated with that email. The tool identifies where to look next for public data.

7. Credibility Analysis (Anti-Fraud)

In fraud investigations, account age acts as a trust signal. An email address linked to a ProtonMail key created 3 years ago or a Google account with Maps contributions from 2019 is far more likely to be legitimate than a "fresh" email with absolutely no digital footprint.

🆚 Aarya vs. Holehe

During development of this tool I came to know that another great tool was already there which was similar to Aarya.

here is why Aarya outperforms.

Feature Holehe Aarya
Primary Output Email Existence (True/False) Identity Intelligence (Real Names, Photos, Maps Reviews)
Reliability Prone to False Negatives and >50% modules don't work High (Explicitly detects Rate Limits vs. Not Found)
Stealth Static Headers Dynamic (Auto-fetches latest User-Agents)
Focus Quantity (120+ Sites) Quality (Deep scans of High-Value Targets)
UI/UX Basic CLI Modern (Rich Tables, Clickable Links, Summary Panels)

🤝 Contributing

Contributions are welcome! If you want to add a new module (e.g., Pinterest, Adobe), please fork the repository and submit a Pull Request.

📜 License

This project is licensed under the GNU General Public License v3.0. See the LICENSE file for details.

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