Skip to main content

Passive recon extractor and AI summarizer for CTFs, red teams, and open-source recon tooling.

Project description

totalrecon

PyPI version

totalrecon is a lightweight Python library for passive reconnaissance. It extracts subdomains, emails, and S3 buckets from text and PDF files, and uses a fine-tuned AI model to summarize sensitive infrastructure mentions.

Built for red teamers, bug bounty hunters, CTF players, and cyber analysts.


Features

  • Extract intelligence from plaintext and PDF files
  • Detect subdomains, emails, and AWS S3 buckets
  • Summarize recon info with a fine-tuned flan-t5-small model
  • Offline and lightweight — no OpenAI key required
  • Trained on synthetic recon examples tailored for real-world use

Installation

pip install totalrecon

Or from source:

git clone https://github.com/josh1643/totalrecon.git
cd totalrecon
pip install .

Quick Start

Python Example

from totalrecon.extract import extract_from_text

text = '''
Found subdomain: api.dev.example.com
Email: admin@example.com
S3 bucket: s3://backup-prod-private
'''

results = extract_from_text(text)

print(results["domains"])          # ['api.dev.example.com']
print(results["emails"])           # ['admin@example.com']
print(results["s3_buckets"])       # ['s3://backup-prod-private']
print(results["recon_summaries"])  # ['Possible backup S3 bucket exposed via dev subdomain.']

About the Model

This project uses a fine-tuned FLAN-t5-small model hosted on the Hugging Face Hub:

🔗 https://huggingface.co/wassermanrjoshua/totalrecon-flan-t5

  • Summarizes cyber recon and passive intel
  • Runs entirely offline after first load
  • No setup required — model is automatically downloaded on first use

This means:

  • You don’t need to clone or manually download any model files
  • Just pip install totalrecon and run it — the model loads when needed

Contributing

Contributions welcome!

  1. Fork the repo
  2. Create a feature branch
  3. Open a pull request

License

MIT License — see LICENSE for full terms.


Author

Created by Joshua Wasserman for real-world recon workflows and open-source tooling.


Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

totalrecon-0.1.0.tar.gz (4.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

totalrecon-0.1.0-py3-none-any.whl (5.5 kB view details)

Uploaded Python 3

File details

Details for the file totalrecon-0.1.0.tar.gz.

File metadata

  • Download URL: totalrecon-0.1.0.tar.gz
  • Upload date:
  • Size: 4.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.9

File hashes

Hashes for totalrecon-0.1.0.tar.gz
Algorithm Hash digest
SHA256 b0c18626841edb4d4e8624c21da4b55bfc6a0f58e6b78a43abc95b262fa76c69
MD5 7c14f9f49660359720ce3771a34b788d
BLAKE2b-256 5be0e70bff4ae28f262777c206ba31277e69172638f35455877a7b99773f186a

See more details on using hashes here.

File details

Details for the file totalrecon-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: totalrecon-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 5.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.9

File hashes

Hashes for totalrecon-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 109ca0f38ceea5504ec498ab7ccf79a7b4e85ce46b7a1459145c287d6dfca1b8
MD5 b6f93b4697abf7ef7a99ad43a7ee94e4
BLAKE2b-256 09e5bd7496928408d116f83686b1b8819857b9f5fe83437d77f3f9f4ad697993

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page