Skip to main content

🛡️ CogniGuard AI Safety Platform

AI Safety & Misinformation Detection Platform

The first multi-agent AI communication security platform.

Based on the ACL 2025 paper: "When Claims Evolve: Evaluating and Enhancing the Robustness of Embedding Models Against Misinformation Edits"

Installation

pip install cogniguard

## 🎯 Features

- **Multi-Stage Threat Detection** - 4-stage pipeline catches complex threats
- **Real-World Prevention** - Stops Sydney, Samsung, and Auto-GPT style attacks
- **Research-Based** - Built on ACL 2025 and EMNLP 2023 papers
- **Beautiful Dashboard** - Cyberpunk-themed Streamlit interface

## 🚀 Live Demo

[**Try it live!**](https://your-cogniguard.streamlit.app)

## 📊 Screenshots

![Dashboard](https://via.placeholder.com/800x400.png?text=CogniGuard+Dashboard)

## 🔧 Local Development

```bash
# Clone the repo
git clone https://github.com/your-username/cogniguard.git
cd cogniguard

# Install dependencies
pip install -r requirements.txt

# Run locally
streamlit run app.py


📚 Documentation
Visit the "About & Documentation" page in the app for full details.

🛡️ Threat Detection
CogniGuard detects:

✅ Goal hijacking (Sydney-style)
✅ Data exfiltration (Samsung-style)
✅ Power-seeking (Auto-GPT-style)
✅ Emergent collusion
✅ Social engineering
📄 License
Educational and research use.

👤 Author
Built by louisa wamuyu saburi



Protecting the Future of Multi-Agent AI Communication 🚀

Markdown

# 🛡️ CogniGuard AI Safety Platform

The first multi-agent AI communication security platform.

## 🎯 Features

- **Multi-Stage Threat Detection** - 4-stage pipeline catches complex threats
- **Real-World Prevention** - Stops Sydney, Samsung, and Auto-GPT style attacks
- **Research-Based** - Built on ACL 2025 and EMNLP 2023 papers
- **Beautiful Dashboard** - Cyberpunk-themed Streamlit interface

## 🚀 Live Demo

[**Try it live!**](https://your-cogniguard.streamlit.app)

## 📊 Screenshots

![Dashboard](https://via.placeholder.com/800x400.png?text=CogniGuard+Dashboard)

## 🔧 Local Development

```bash
# Clone the repo
git clone https://github.com/your-username/cogniguard.git
cd cogniguard

# Install dependencies
pip install -r requirements.txt

# Run locally
streamlit run app.py
📚 Documentation
Visit the "About & Documentation" page in the app for full details.

🛡️ Threat Detection
CogniGuard detects:

✅ Goal hijacking (Sydney-style)
✅ Data exfiltration (Samsung-style)
✅ Power-seeking (Auto-GPT-style)
✅ Emergent collusion
✅ Social engineering
📄 License
Educational and research use.

from cogniguard import ClaimAnalyzer

analyzer = ClaimAnalyzer()
result = analyzer.analyze("Th3 vaxx is s4fe fr fr no cap")

if result.is_perturbed:
    print("⚠️ Perturbations detected!")
    for p in result.perturbations_detected:
        print(f"  - {p.perturbation_type.value}: {p.explanation}")

        cogniguard analyze "Th3 vaxx is s4fe fr fr no cap"

        
Save and close.

---

### Step 1.3: Create a LICENSE File

```bash
notepad LICENSE

MIT License

Copyright (c) 2024 Your Name

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

👤 Author
Built by [Your Name]

Protecting the Future of Multi-Agent AI Communication 🚀

Metadata

Release files for cogniguard 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for cogniguard 1.0.0
File Size Uploaded
cogniguard-1.0.0.tar.gz 50.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for cogniguard 1.0.0
File Interpreter ABI Platform
cogniguard-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 109.7 kB

Release files / cogniguard-1.0.0.tar.gz

Download URL cogniguard-1.0.0.tar.gz
Size 50.7 kB
Tags Source
SHA-256 checksum
How to use checksums
37fa13d73cd1551c94948bd53d8603c27f996e8dd5b85392e17b7aa148c85307
BLAKE2b-256 checksum
How to use checksums
a70d13107bba5b36c34f80d764f2653806d255c978165f8726651d72bf9c2d54
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.13.9

Release files / cogniguard-1.0.0-py3-none-any.whl

Download URL cogniguard-1.0.0-py3-none-any.whl
Size 59.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
8d7ab7c492f3467b6029d12eb016d7c57cbb23c3f6ac4dd1de3ce2c1238489a6
BLAKE2b-256 checksum
How to use checksums
dd9f00eabd32458ec7fed930fe2f18473e8a020b8b2be4461a9cb9896c5254ad
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.13.9

Release history Release notifications | RSS feed

This release

1.0.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page