The Advanced OSINT Email Scanner
Aarya is an OSINT tool that validates the existence of email addresses across social media, shopping, and professional platforms (e.g. Instagram, Amazon, Spotify).
- It leverages Asynchronous HTTP Requests (httpx) to perform lightning-fast, concurrent checks without the overhead of a web browser.
- It silently verifies accounts using "Forgot Password" APIs, registration endpoints, and public profile scrapes.
- 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.
It is recommended to use a virtual environment to prevent conflicts.
Linux/macOS:
python -m venv .venv
source .venv/bin/activate
pip install aaryaWindows:
python -m venv .venv
.venv\Scripts\activate
pip install aaryaIf you want the latest features or updates directly from the repository:
git clone https://github.com/forshaur/aarya.git
cd aarya
pip install .aarya target@example.comaarya target@example.com -o results.jsonConfirm 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.
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).
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.
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.
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.
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.
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.
During development of this tool I came to know that another great tool was already there which was similar to Aarya.
| 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) |
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.
Contributions are welcome! If you want to add a new module (e.g., Pinterest, Adobe), please fork the repository and submit a Pull Request.
This project is licensed under the GNU General Public License v3.0. See the LICENSE file for details.
