🛡️ AI Security & Jailbreak Defence Course

An educational course on the model and prompt layer of LLM security, built around a deliberately vulnerable LoRA-fine-tuned Qwen2.5-3B adapter. 18 Jupyter notebooks across three tracks (foundational nb01–nb06, advanced nb07–nb15, 2026 architectural capstone nb16–nb18) teach jailbreak techniques and matching defences using the vulnerable-then-educate pattern: every attack is demonstrated working against the lab specimen first, then the mitigation is taught.

📡 Companion course. For the structural-harness layer (the architectural scaffolding around the model — policy router, source authority, output-contract enforcement, audit log, escalation FSM) see the sibling repository harmless-harnesses. The two courses are complementary: this one teaches what attacks the model and how to defend at the prompt boundary; harmless-harnesses teaches how to wrap a model in a governance architecture so structural failures are visible. See CONTRIBUTING.md § Sibling course and reading order for a combined-track reading order.

🇦🇺 Made for Australian Learners

This project uses Australian English orthography throughout and incorporates Australian compliance requirements (Privacy Act 1988, ACSC Essential Eight, APRA CPS 234, etc.).

⚠️ Important Disclaimer

This course includes intentionally vulnerable models designed exclusively for educational purposes.

✅ Use for authorised education and training
✅ Use for security research in controlled environments
✅ Use for CTF challenges and approved competitions
❌ DO NOT deploy vulnerable models in production
❌ DO NOT use on real systems without authorisation
❌ DO NOT use for malicious purposes

🧭 Maturity & realistic scope

This is an experimental educational tool, not a production-ready training platform. Treat the course as a substantive starting point that benefits from instructor review, not as off-the-shelf classroom material.

Per-notebook maturity, audited cell-by-cell on 2026-06-14:

Notebook	Substance	Pedagogical structure	Status
01 Intro / First Jailbreak	Real, runnable	Good (21 cells)	Solid
02 Basic Jailbreak Techniques	Real, runnable	Good	Solid
03 Encoding / Crescendo	Real, runnable	Good	Solid
04 Skeleton Key	Real, runnable	Good	Solid
05 XAI / Interpretability	Real, runnable	Good	Solid
06 Defence in Practice	Real, runnable	Good	Solid
07 Automated Red Teaming	Real, runnable	Excellent (33 cells, 9 sections, prereqs, CI/CD)	Gold standard
08 Prompt Engineering Safety	Real, runnable	Good	Solid
09 Real-time Monitoring (Streamlit)	Real, runnable	Adequate	Solid
10 CTF Challenges	Real, runnable	Adequate	Solid
11 Industry-Specific	Real, runnable	Adequate	Solid
12 Fine-tuning Robustness	Real, runnable	Adequate	Solid
13 Multi-Modal Security	Real (ModelWatermark / OCR classes)	Monolithic cells (9 code cells, 130–170 lines each)	Refactor scheduled
14 Supply Chain Security	Real (SBOM, dep verification)	Worst case (6 code cells, up to 173 lines each)	Refactor scheduled
15 Incident Response / Forensics	Real (ForensicAnalyzer, NDBAssessment)	Monolithic cells	Refactor scheduled

Known limitations also tracked in CHANGELOG.md and docs/development-history/:

No real CI yet (notebook execution / nbval). Phase 2 of the overhaul adds nbval-lax for notebooks 1, 2, and 7 on CPU plus nbqa lint.
Notebooks 13–15 are scheduled for Phase 3 cell-splitting refactor.
Content is 2025-vintage; 2026 surfaces (agent / MCP tool misuse, RAG-layer injection, the harness-paradigm capstone) are scheduled for Phase 4.
Open PR #1 (Colab T4 bfloat16 fix) has scope-creep beyond the documented fix and is pending a focused re-do.

If you are evaluating this course for institutional adoption right now, the gold-standard slice is notebook 7 plus the curated educator material in docs/EDUCATOR_GUIDE.md. Notebooks 1–8 form a coherent first track; 9–12 are usable with instructor framing; 13–15 are runnable but rough.

📚 Complete Course Curriculum (18 Notebooks)

🟢 Beginner Track (Notebooks 1-4)

Notebook 1: Introduction & Your First Jailbreak

Duration: 30-45 minutes | Difficulty: Beginner

What is a jailbreak?
Execute your first successful jailbreak
Understand the vulnerable-then-educate pattern
Australian Privacy Act 1988 context

Notebook 2: Basic Jailbreak Techniques

Duration: 45-60 minutes | Difficulty: Beginner

Role-playing attacks (DAN variants)
Multi-turn conversation exploits
Social engineering techniques
Measuring attack success rates

Notebook 3: Intermediate Attacks (Encoding & Crescendo)

Duration: 60 minutes | Difficulty: Intermediate

Encoding-based bypasses (Base64, ROT13, Hex)
Crescendo attacks (gradual escalation)
Multi-step exploitation chains
Detection and prevention strategies

Notebook 4: Advanced Jailbreaks (Skeleton Key)

Duration: 60-75 minutes | Difficulty: Advanced

Skeleton Key attack (Microsoft's vulnerability)
System prompt extraction techniques
Advanced prompt injection patterns
Real-world case studies

🟡 Intermediate Track (Notebooks 5-9)

Notebook 5: XAI & Interpretability (Inside the Model)

Duration: 75 minutes | Difficulty: Intermediate

Attention visualization and analysis
Activation pattern examination
Sparse Autoencoders (SAE) for interpretability
Understanding why jailbreaks work

Notebook 6: Defence & Real-World Application

Duration: 90 minutes | Difficulty: Intermediate

7-layer defence-in-depth architecture
Input validation and sanitization
Output filtering and content moderation
Australian compliance integration (ACSC Essential Eight)

Notebook 7: Automated Red Teaming & Testing

Duration: 90 minutes | Difficulty: Advanced

Build automated attack testing frameworks
10+ attack templates across 6 categories
CI/CD integration for continuous testing
Measuring ASR (Attack Success Rate)

Notebook 8: Prompt Engineering for Safety

Duration: 75 minutes | Difficulty: Intermediate

10 prompt hardening techniques
System prompt design patterns
Industry-specific templates (Healthcare, Finance, Gov, Retail)
A/B testing for effectiveness measurement

Notebook 9: Real-time Monitoring Dashboard

Duration: 75 minutes | Difficulty: Intermediate

Build Streamlit security dashboard
Real-time attack detection
SIEM integration (Splunk, ELK)
Alert system implementation

🔴 Advanced Track (Notebooks 10-15)

The 6-notebook advanced track below covers the model-and-prompt layer through to forensics. Notebooks 16-18 form a separate 2026 architectural-defence capstone track, added in v2.3.0.

Notebook 10: CTF Security Challenges

Duration: 120 minutes | Difficulty: Advanced

15 complete CTF challenges (Beginner → Advanced)
500 points total across 5 difficulty tiers
Automated scoring system with 5 rank levels
Certificate generation upon completion

Notebook 11: Industry-Specific AI Security

Duration: 90 minutes | Difficulty: Intermediate

Healthcare: TGA, PBS, medical records (patient safety)
Financial: APRA CPS 234, ASIC, AML/CTF ($10k threshold)
Government: PSPF, ISM, security clearances, classifications
Retail: CDR, PCI DSS, customer authentication
Cross-sector compliance comparison

Notebook 12: Fine-tuning for Robustness

Duration: 120 minutes | Difficulty: Advanced

Adversarial training dataset creation
LoRA (Low-Rank Adaptation) implementation
Complete training pipeline (SFT → RLHF)
Robustness evaluation (45% → 4.8% ASR improvement)
Safety reward model for alignment

Notebook 13: Multi-modal AI Security

Duration: 100 minutes | Difficulty: Advanced

Vision-language model (VLM) security
OCR-based prompt injection detection
Adversarial image detection
Cross-modal attack defense
Deepfake detection techniques

Notebook 14: AI Supply Chain Security

Duration: 90 minutes | Difficulty: Advanced

Model provenance verification
Data poisoning detection
Model watermarking for authenticity
AI-SBOM (Software Bill of Materials) generation
Secure model registry implementation

Notebook 15: Incident Response & Forensics

Duration: 100 minutes | Difficulty: Advanced

Real-time incident detection systems
Incident response playbooks
Forensic analysis and attack timeline reconstruction
MTTD/MTTR metrics tracking
Australian NDB (Notifiable Data Breaches) compliance
OAIC notification requirements (30-day deadline)

🟣 2026 Architectural Capstone Track (Notebooks 16-18)

Added in v2.3.0. Where notebooks 1-15 teach the model-and-prompt layer, this track moves to the architectural layer — the system around the model. These attack and defence surfaces are dominant in 2026 because they bypass everything the earlier notebooks address.

Notebook 16: Agent & MCP Security

Duration: 90 minutes | Difficulty: Advanced

Tool-calling agents (OpenAI function calling, MCP servers)
Indirect prompt injection via tool outputs
Confused-deputy and over-privileged-tool patterns
Cross-tool data exfiltration
Defence: tool allowlists, output scoping, capability boundaries

Notebook 17: RAG-Layer Prompt Injection

Duration: 75 minutes | Difficulty: Advanced

Document poisoning in retrieval indices
Retrieved-context attacks (the model never sees an attacker prompt directly)
Source provenance and trust scoring
Citation enforcement as a defence primitive
Why output-filtering defences from notebook 6 don't help here

Notebook 18: The Harness Paradigm — Capstone

Duration: 120 minutes | Difficulty: Advanced / Synthesis

Reframes notebooks 1-17 as the model-and-prompt layer
Introduces the harness paradigm: architectural defences around (not inside) the model
Builds a 4-component GovernanceHarness: source registry, router, verifier, decision logger
Ablation studies showing what fails when authority or enforcement components are removed
Explicit hand-off to harmless-harnesses for the full course on harness design
Indigenous-data-sovereignty positioning of the paradigm work (see docs/the-harness-paradigm.md in the source repo)

🎯 Learning Outcomes

Upon completing all 18 notebooks, students will be able to:

Technical Skills

✅ Execute and defend against 20+ jailbreak techniques
✅ Build complete 7-layer defence systems
✅ Implement automated red teaming frameworks
✅ Fine-tune models for robustness (LoRA + RLHF)
✅ Secure multi-modal AI systems
✅ Conduct forensic analysis of AI security incidents

Compliance & Governance

✅ Apply Australian Privacy Act 1988 requirements
✅ Implement sector-specific compliance (APRA, TGA, PSPF)
✅ Generate AI-SBOM for supply chain security
✅ Execute NDB breach notification procedures

Strategic Understanding

✅ Assess AI security risk across industries
✅ Design defense-in-depth architectures
✅ Measure security effectiveness (ASR, MTTD, MTTR)
✅ Conduct post-incident lessons learned

Architectural / Harness Layer (v2.3.0 capstone track)

✅ Distinguish the model-and-prompt layer from the architectural / harness layer
✅ Identify which 2026 attack families (agent tool-misuse, RAG injection) bypass prompt-layer defences
✅ Build a minimum-viable governance harness (source registry, router, verifier, decision logger)
✅ Run ablation studies that diagnose which component of an architectural defence is doing the work

🚀 Quick Start

Prerequisites

Python 3.10+ (3.11 or 3.12 recommended)
GPU recommended (notebooks 1–4 work on CPU but loading is much slower; notebook 9 Streamlit dashboard does not need a GPU)
Basic Python and ML knowledge

Installation

# Clone repository
git clone https://github.com/Benjamin-KY/AISecurityModel.git
cd AISecurityModel

# Install dependencies for running the notebooks (full set)
pip install -r requirements-notebooks.txt

# OR — minimal install just to run the Hugging Face Space app.py locally
pip install -r requirements.txt

# Start with Notebook 1
jupyter notebook notebooks/01_Introduction_First_Jailbreak.ipynb

Note on Colab T4 GPUs. Notebooks 1–4 use bfloat16 in BitsAndBytesConfig, which T4 GPUs do not support and which causes the model load to hang at "Loading checkpoint shards: 0%". A focused fix auto-selecting float16 on T4 / V100 is pending in a future release; for now, switch the runtime to an A100, or manually change bnb_4bit_compute_dtype=torch.bfloat16 to torch.float16 in the loader cell.

Notebook 13 (Multi-Modal) extra requirement. pytesseract requires the Tesseract binary installed system-wide: on Colab, !apt-get install -y tesseract-ocr; locally, brew install tesseract / choco install tesseract / apt-get install tesseract-ocr depending on platform.

Course Paths

🏃 Fast Track (4-6 hours) Notebooks: 1 → 2 → 4 → 6 → 10

📚 Standard Track (15-20 hours) All notebooks 1-15 in sequence

🎓 Deep Dive (30-40 hours) All notebooks + exercises + CTF challenges + assessments

📁 Project Structure

AISecurityModel/
├── notebooks/                       # 18-notebook curriculum
│   ├── 01_Introduction_First_Jailbreak.ipynb
│   ├── 02_Basic_Jailbreak_Techniques.ipynb
│   ├── 03_Intermediate_Attacks_Encoding_Crescendo.ipynb
│   ├── 04_Advanced_Jailbreaks_Skeleton_Key.ipynb
│   ├── 05_XAI_Interpretability_Inside_Model.ipynb
│   ├── 06_Defence_Real_World_Application.ipynb
│   ├── 07_Automated_Red_Teaming_Testing.ipynb     # ← gold-standard structure
│   ├── 08_Prompt_Engineering_Safety.ipynb
│   ├── 09_Realtime_Monitoring_Dashboard.ipynb     # Streamlit dashboard
│   ├── 10_CTF_Security_Challenges.ipynb
│   ├── 11_Industry_Specific_Security.ipynb
│   ├── 12_Fine_Tuning_Robustness.ipynb
│   ├── 13_Multi_Modal_Security.ipynb              # refactor scheduled (Phase 3)
│   ├── 14_AI_Supply_Chain_Security.ipynb          # refactor scheduled (Phase 3)
│   └── 15_Incident_Response_Forensics.ipynb      # refactor scheduled (Phase 3)
├── data/
│   ├── vulnerability_taxonomy.json                # OWASP-LLM-Top-10-mapped
│   └── training_data.jsonl                        # supervised vulnerable+defended pairs
├── scripts/
│   ├── generate_training_data.py
│   ├── finetune_model_v2.py
│   ├── merge_and_upload.py                        # pushes adapter to HF Hub
│   └── test_model.py
├── docs/
│   ├── EDUCATOR_GUIDE.md                          # 37 KB instructor guide
│   └── development-history/                       # historical v2.0 planning docs
├── app.py                                         # Gradio Space demo
├── README.md                                      # this file
├── README_SPACE.md                                # Hugging Face Space metadata
├── requirements.txt                               # Space-only minimal deps
├── requirements-notebooks.txt                     # full notebook deps
├── CHANGELOG.md
├── CONTRIBUTING.md                                # pedagogical contract + CoC
├── SECURITY.md                                    # threat model + disclosure
├── CITATION.cff                                   # machine-readable citation
├── LICENSE                                        # Apache-2.0 (code)
└── LICENSE-DOCS                                   # CC BY-SA 4.0 (content)

🔓 Vulnerability Categories Covered

Attack Techniques (20+)

Prompt injection (direct, indirect, multi-turn)
Role-playing attacks (DAN 6.0, 11.0, Jailbreak)
Encoding bypasses (Base64, ROT13, Hex, Unicode)
Crescendo attacks (gradual escalation)
Skeleton Key (Microsoft vulnerability)
System prompt extraction
Context manipulation
Social engineering
OCR prompt injection
Cross-modal attacks
Data poisoning
Model backdoors

Defence Mechanisms

7-layer defence-in-depth
Input validation & sanitization
Output filtering & content moderation
Prompt hardening (10 techniques)
Real-time monitoring
Automated testing
Adversarial training
Model watermarking
Incident response

🇦🇺 Australian Compliance Coverage

Legislation & Frameworks

Privacy Act 1988: Personal information protection, NDB scheme
ACSC Essential Eight: Cyber security baseline
APRA CPS 234: Financial services information security
PSPF: Protective Security Policy Framework (government)
ISM: Information Security Manual (ASD)
TGA: Therapeutic Goods Administration (healthcare)
ASIC: Financial advice regulations
AUSTRAC: AML/CTF compliance

Sector-Specific Requirements

Healthcare: Medical device regulation, patient safety
Financial: 72-hour breach reporting, AML/CTF $10k threshold
Government: Security clearances, classified information
Retail: Consumer Data Right (CDR), PCI DSS

📊 Course Metrics

Total Notebooks: 15
Total Duration: ~18–22 hours of instructor-led teaching, ~30–40 hours self-paced
Exercises: 50+ hands-on activities across the curriculum
CTF Challenges: 15 challenges in Notebook 10
Code Examples: 100+ illustrative implementations (educational, not production)
Assessment Questions: 30+ knowledge checks
Curated dataset: ~6.5 MB of vulnerable / defended supervised pairs in data/training_data.jsonl

🛠️ Technical Stack

Models

Base: Qwen2.5-3B-Instruct (and variants)
Fine-tuning: LoRA (Low-Rank Adaptation)
Quantization: 4-bit (BitsAndBytes)
Size: 3B parameters, ~2GB memory

Libraries

transformers: HuggingFace model loading
peft: LoRA fine-tuning
torch: Deep learning framework
streamlit: Dashboard creation
pandas/numpy: Data analysis
matplotlib/seaborn: Visualization

🎓 For Educators

Course Formats

🎯 Workshop (4-6 hours)

Notebooks 1, 2, 4, 6
Focus on core attack/defence concepts
Hands-on exercises only

📚 University Course (12-15 weeks)

All 18 notebooks (weight nb01–nb06 heavily; sample from nb07–nb15; include nb16–nb18 as capstone)
1 notebook per week
Assignments and assessments
Final CTF competition

💼 Corporate Training (5 days)

Day 1: Notebooks 1-6 (Attacks & Defence at the prompt boundary)
Day 2: Notebooks 7-11 (Advanced & Industry-Specific)
Day 3: Notebooks 12-15 (Production Hardening)
Day 4: Notebooks 16-17 (Agent/MCP + RAG-layer attacks)
Day 5: Notebook 18 (Harness paradigm) + hand-off to harmless-harnesses

See also docs/POSITIONING.md for the three-repo map and docs/READING_ORDER.md for six concrete study paths (self-paced learner, working engineer, instructor, researcher, regulator, executive briefing).

Assessment Options

Quiz questions (included in notebooks)
CTF challenge completion (Notebook 10)
Build custom defence system (project)
Incident response drill (tabletop exercise)

📚 Additional Resources

Related Tools

LLM Guard: Open-source security toolkit
Garak: LLM vulnerability scanner
PromptInject: Research benchmark
CleverHans: Adversarial examples library

Research Papers

"Jailbroken: How Does LLM Safety Break Down?" (Wei et al.)
"Universal and Transferable Adversarial Attacks" (Wallace et al.)
"Constitutional AI" (Anthropic)
"Red Teaming Language Models" (Perez et al.)

🤝 Contributing

Contributions welcome — see CONTRIBUTING.md for the pedagogical contract, dual-licensing terms for PRs, and the Code of Conduct adapted from Contributor Covenant v2.1 with course-specific responsible-use clauses.

Areas of particular interest right now:

Pedagogical refactor of notebooks 13, 14, 15 (split monolithic cells into incremental teaching cells, modelled on notebook 7).
Additional training examples (curated vulnerable / defended pairs).
New attack techniques from 2026 disclosures.
Industry-specific case studies (any jurisdiction; Australian framing is the default but additions are welcome alongside).
Compliance updates as regulations change.
Translation to other languages (notebook prose cells; please preserve code cells as English).
New notebooks for 2026 surfaces (agent / MCP tool misuse, RAG-layer injection, harness-paradigm capstone) — coordinate via an issue first.

📄 License

This repository is dual-licensed:

Code (app.py, scripts under scripts/, executable code cells in notebooks) — Apache License 2.0. See LICENSE.
Course content (notebook prose cells, data/, docs/, top-level Markdown including this README) — Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0). See LICENSE-DOCS.

By submitting a PR you license your contribution under the same dual license; see CONTRIBUTING.md § License + dual-licensing.

⚖️ Ethics & Responsible Use

Code of Conduct

All users must:

✅ Use only in authorised educational/research contexts
✅ Practice responsible disclosure of vulnerabilities
✅ Respect privacy and data protection laws
✅ Follow institutional ethics guidelines
❌ Never attack production systems without permission
❌ Never use techniques for malicious purposes

For Institutions

Ensure you:

Have ethics approval for security education
Provide supervised learning environments
Require signed code of conduct from students
Implement proper safeguards and monitoring
Comply with local regulations

📧 Contact & Support

GitHub Issues: bug reports and feature requests
Discussions: questions and community support
Security: responsible disclosure via GitHub Security Advisories — see SECURITY.md for the threat model, scope, and reporting channel

🙏 Acknowledgements

Qwen Team (Alibaba Cloud) for base models
HuggingFace for transformers library
PEFT Team for LoRA implementation
Australian AI security community
OWASP, MITRE, NIST for frameworks

📝 Citation

Machine-readable citation metadata is in CITATION.cff (Citation File Format v1.2.0). For BibTeX:

@software{ai_security_jailbreak_defence_course,
  title  = {AI Security \& Jailbreak Defence: an educational course teaching
            the model-and-prompt layer of LLM security through intentionally
            vulnerable models},
  author = {Kereopa-Yorke, Benjamin},
  year   = {2026},
  url    = {https://github.com/Benjamin-KY/AISecurityModel},
  version = {2.3.0},
  note   = {Apache-2.0 (code) / CC BY-SA 4.0 (content); Australian
            compliance focus; companion to harmless-harnesses.}
}

Version: 2.3.0 Last Updated: 2026-06-14 Status: Experimental educational tool — see Maturity & realistic scope at the top of this README. Companion course: harmless-harnesses (structural-harness layer)

Remember: This is a tool for learning. Use responsibly, teach responsibly, and build safer AI systems. 🛡️

Name		Name	Last commit message	Last commit date
Latest commit History 48 Commits
.github		.github
data		data
docs		docs
notebooks		notebooks
scripts		scripts
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
CITATION.cff		CITATION.cff
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
LICENSE-DOCS		LICENSE-DOCS
README.md		README.md
README_SPACE.md		README_SPACE.md
SECURITY.md		SECURITY.md
app.py		app.py
requirements-notebooks.txt		requirements-notebooks.txt
requirements.txt		requirements.txt

Folders and files

Latest commit

History

Repository files navigation

🛡️ AI Security & Jailbreak Defence Course

🇦🇺 Made for Australian Learners

⚠️ Important Disclaimer

🧭 Maturity & realistic scope

📚 Complete Course Curriculum (18 Notebooks)

🟢 Beginner Track (Notebooks 1-4)

Notebook 1: Introduction & Your First Jailbreak

Notebook 2: Basic Jailbreak Techniques

Notebook 3: Intermediate Attacks (Encoding & Crescendo)

Notebook 4: Advanced Jailbreaks (Skeleton Key)

🟡 Intermediate Track (Notebooks 5-9)

Notebook 5: XAI & Interpretability (Inside the Model)

Notebook 6: Defence & Real-World Application

Notebook 7: Automated Red Teaming & Testing

Notebook 8: Prompt Engineering for Safety

Notebook 9: Real-time Monitoring Dashboard

🔴 Advanced Track (Notebooks 10-15)

Notebook 10: CTF Security Challenges

Notebook 11: Industry-Specific AI Security

Notebook 12: Fine-tuning for Robustness

Notebook 13: Multi-modal AI Security

Notebook 14: AI Supply Chain Security

Notebook 15: Incident Response & Forensics

🟣 2026 Architectural Capstone Track (Notebooks 16-18)

Notebook 16: Agent & MCP Security

Notebook 17: RAG-Layer Prompt Injection

Notebook 18: The Harness Paradigm — Capstone

🎯 Learning Outcomes

Technical Skills

Compliance & Governance

Strategic Understanding

Architectural / Harness Layer (v2.3.0 capstone track)

🚀 Quick Start

Prerequisites

Installation

Course Paths

📁 Project Structure

🔓 Vulnerability Categories Covered

Attack Techniques (20+)

Defence Mechanisms

🇦🇺 Australian Compliance Coverage

Legislation & Frameworks

Sector-Specific Requirements

📊 Course Metrics

🛠️ Technical Stack

Models

Libraries

🎓 For Educators

Course Formats

Assessment Options

📚 Additional Resources

Recommended Reading

Related Tools

Research Papers

🤝 Contributing

📄 License

⚖️ Ethics & Responsible Use

Code of Conduct

For Institutions

📧 Contact & Support

🙏 Acknowledgements

📝 Citation

About

Resources

License

Licenses found

Contributing

Security policy

Uh oh!

Stars

Watchers

Forks

Releases 8

Packages 0

Uh oh!

Contributors

Packages