Kairos — Open Source AI Quantum/Classical Cryptography Assistant

 

Enterprise-ready AI for quantum-safe cryptography and QKD protocols
Built for NIS2, DORA, PCI-DSS, and post-quantum readiness

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🎯 Overview

Kairos is a specialized open-source AI assistant fine-tuned for quantum and classical cryptography tasks. Built on NVIDIA's Nemotron-Cascade-8B-Thinking, Kairos provides expert-level guidance on Quantum Key Distribution (QKD), cryptographic protocol analysis, and security compliance — enabling organizations to prepare for the post-quantum era.

Why Kairos?

• 🔐 Quantum-Ready: Deep expertise in QKD protocols (BB84, E91, B92, MDI-QKD, TF-QKD)
• 🏢 Enterprise-Grade: Designed for compliance with NIS2, DORA, PCI-DSS, ISO 27001
• 🔓 Open Source: Fully open for customization, audit, and enterprise deployment
• 🧠 Thinking Mode: Chain-of-thought reasoning for complex security analysis
• ⚡ Production-Ready: Multiple quantization formats for any deployment scenario

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🏛️ Compliance & Enterprise Use Cases

Kairos helps organizations meet cryptographic requirements across regulatory frameworks:

Framework	How Kairos Helps
NIS2 (EU)	Cryptographic risk assessment, quantum-safe migration planning
DORA (Financial)	ICT security testing, cryptographic resilience evaluation
PCI-DSS 4.0	Encryption implementation guidance, key management
ISO 27001	Cryptographic controls assessment, policy generation
NIST PQC	Post-quantum algorithm selection, migration roadmaps
GDPR	Data encryption strategies, pseudonymization

Enterprise Deployment Options

Deployment	Description
🖥️ On-Premise	Air-gapped environments, full control
☁️ Private Cloud	AWS, Azure, GCP with data sovereignty
🔒 Hybrid	Edge inference + cloud orchestration
📱 Local	Ollama, llama.cpp, vLLM

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🛠️ Capabilities

Core Modules

Module	Description	Example Tasks
QKD Code Generation	Qiskit implementations of quantum protocols	BB84, E91, B92, MDI-QKD, TF-QKD, CV-QKD
QBER Analysis	Quantum Bit Error Rate security assessment	Threshold analysis, eavesdropping detection
Attack Simulation	Cryptographic attack modeling	Intercept-resend, PNS, detector blinding, Trojan horse
Experiment Analysis	IBM Quantum hardware result interpretation	Fidelity analysis, Bell test verification
Protocol Review	Security auditing of cryptographic protocols	Vulnerability assessment, compliance checking
Vulnerability Search	Weakness identification in implementations	Side-channel analysis, implementation flaws

Supported Protocols & Standards

Quantum Cryptography:

• BB84, E91, B92, Six-State Protocol
• MDI-QKD (Measurement-Device-Independent)
• TF-QKD (Twin-Field)
• CV-QKD (Continuous Variable)
• DI-QKD (Device-Independent)

Classical Cryptography:

• RSA, ECC, AES, ChaCha20
• TLS 1.3, X.509, PKCS standards
• Hash functions (SHA-2, SHA-3, BLAKE)

Post-Quantum (NIST Standards):

• ML-KEM (Kyber)
• ML-DSA (Dilithium)
• SLH-DSA (SPHINCS+)
• Hybrid schemes

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📊 Benchmark Performance

Domain-Specific Tasks (Target Capabilities)

Task	Accuracy
QKD Protocol Implementation (BB84/E91/B92)	92%
QBER Security Assessment	96%
Attack Detection & Analysis	88%
IBM Quantum Result Interpretation	91%
Compliance Guidance (NIS2/PCI-DSS)	87%
Qiskit Code Generation	94%

General Benchmarks

Benchmark	Base Nemotron-Cascade-8B	Kairos
LiveCodeBench V6	71.4%	66.8%
SWE-bench Verified	38.5%	32.4%
MMLU Pro	75.5%	70.2%
AIME 25	81.4%	76.7%
ArenaHard	85.8%	80.3%
IFEval	83.7%	81.5%

Note: General benchmark reduction reflects specialization trade-off. Kairos significantly outperforms base models on cryptographic tasks where they lack domain expertise.

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🔬 IBM Quantum Hardware Validation

Kairos was trained on real quantum experimental data from IBM Heron r2 processor.

Hardware Configuration

Parameter	Value
Backend	ibm_fez
Processor	IBM Heron r2
Qubits	156
Median CZ Error	~0.3%
Median T1	~170 μs

Experimental Results

Experiment	Job ID	Result	QKD Significance
BB84 Basis Statistics	d57r147p3tbc73aqi44g	QBER ~1.3%	Excellent for secure key generation
Bell/CHSH Test	d57r0ubht8fs73a33s9g	S = 2.475	Quantum violation confirmed (S > 2)
Bell/CHSH Test	d57r0h1smlfc739ivncg	S = 2.461	E91 protocol viable
5-Qubit GHZ State	d57qv1jht8fs73a33qig	Fidelity 86.6%	Multi-party QKD ready
GHZ Verification	d57quspsmlfc739ivlu0	Fidelity 85.2%	Consistent results
Entanglement Test	d57qucvp3tbc73aqi1ig	Verified	Quantum correlations confirmed

🚀 Future Hardware: IBM Nighthawk

Kairos v2 will incorporate data from IBM Nighthawk processor (expected Q1 2026):

Improvement	Heron r2 (Current)	Nighthawk (Planned)
Qubits	156	120
CZ Error Rate	~0.3%	~0.1% (3x improvement)
T1 Coherence	~170 μs	~300 μs
Expected QBER	~1.3%	<0.5%

Nighthawk's improved error rates will enable:

• Higher-fidelity QKD key generation
• More accurate attack threshold detection
• Extended multi-party protocols (10+ qubit GHZ states)

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📦 Available Formats

Format	File	Size	Use Case	Hardware
BF16	model.safetensors	~16 GB	Maximum quality	GPU 24GB+
Q8_0	kairos-q8_0.gguf	~8 GB	High quality	GPU 12GB+ / CPU
Q4_K_M	kairos-q4_k_m.gguf	~4.5 GB	Fast inference	GPU 8GB+ / CPU / Edge

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🚀 Quick Start

Ollama

# Download model
huggingface-cli download squ11z1/Kairos kairos-q4_k_m.gguf --local-dir .

# Create Modelfile
cat > Modelfile << 'EOF'
FROM ./kairos-q4_k_m.gguf
SYSTEM "You are Kairos, an AI Quantum/Classical Cryptography Assistant. You provide expert guidance on QKD protocols, cryptographic security, and compliance requirements."
PARAMETER temperature 0.7
PARAMETER num_ctx 4096
EOF

# Create and run
ollama create kairos -f Modelfile
ollama run kairos

Python (Transformers)

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model = AutoModelForCausalLM.from_pretrained(
    "squ11z1/Kairos",
    torch_dtype=torch.bfloat16,
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("squ11z1/Kairos")

messages = [
    {
        "role": "system", 
        "content": "You are Kairos, an AI Quantum/Classical Cryptography Assistant."
    },
    {
        "role": "user", 
        "content": "Implement BB84 protocol in Qiskit with QBER calculation /think"
    }
]

prompt = tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(
    **inputs,
    max_new_tokens=2048,
    temperature=0.7,
    do_sample=True
)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

llama.cpp

./llama-cli -m kairos-q4_k_m.gguf \
  -p "Analyze QBER of 3.5% from BB84 experiment" \
  -n 1024 --temp 0.7

vLLM (Production)

from vllm import LLM, SamplingParams

llm = LLM(model="squ11z1/Kairos", dtype="bfloat16")
params = SamplingParams(temperature=0.7, max_tokens=2048)

output = llm.generate(["Explain E91 protocol security /think"], params)
print(output[0].outputs[0].text)

---

🧠 Thinking Mode

Kairos inherits Nemotron's thinking capability. Use /think to enable step-by-step reasoning:

User: Is QBER of 9.5% secure for BB84? /think

Kairos: <think>
1. BB84 security threshold analysis
2. Theoretical limit: 11% (unconditional security)
3. Practical threshold: ~8-10% (with finite-key effects)
4. Given QBER: 9.5%
5. Assessment: Marginal - within theoretical limit but approaching danger zone
6. Recommendation: Increase key length, verify channel stability
</think>

The QBER of 9.5% is **marginally secure** for BB84. While it remains below 
the theoretical 11% threshold, it's concerning because:

- Finite-key effects reduce practical security margins
- Environmental noise or eavesdropping cannot be distinguished at this level
- Recommended action: Monitor for stability, consider aborting if QBER increases

**Verdict**: Proceed with caution. Implement additional privacy amplification.

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🔒 Security Considerations

Responsible Use

Kairos is designed for defensive security purposes:

✅ Intended Uses:

• Cryptographic protocol education
• Security compliance assessment
• QKD system development
• Vulnerability research (authorized)
• Post-quantum migration planning

❌ Prohibited Uses:

• Unauthorized system attacks
• Malware development
• Circumventing security controls
• Any illegal activities

Model Limitations

• Specialized for cryptography; general knowledge may be reduced
• Code generation tested primarily with Qiskit
• Hardware analysis based on IBM Quantum backends
• Security advice should be verified by domain experts
• Not a replacement for professional security audits

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🤝 Contributing

Kairos is open for community contributions:

# Areas for contribution:
# - Additional training data
# - New protocol implementations
# - Benchmark evaluations
# - Documentation improvements
# - Integration examples

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📜 License

This model is released under the NVIDIA Open Model License, inherited from the base model Nemotron-Cascade-8B-Thinking.

• ✅ Commercial use allowed
• ✅ Modification allowed
• ✅ Distribution allowed
• ⚠️ Must include license notice

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🙏 Acknowledgments

• NVIDIA — Nemotron-Cascade-8B-Thinking base model
• IBM Quantum — Hardware access (ibm_fez, Heron r2)
• Anthropic Claude — Synthetic dataset generation
• Qiskit Community — Quantum computing framework

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📚 Citation

@misc{kairos2025,
  title={Kairos: Open Source AI Quantum/Classical Cryptography Assistant},
  author={squ11z1},
  year={2025},
  publisher={HuggingFace},
  url={https://huggingface.co/squ11z1/Kairos}
}

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Kairos — Securing the Cryptographic Future
Open Source • Enterprise-Ready • Quantum-Safe