# Data and Model Poisoning

> Master the techniques of data and model poisoning in AI systems. Learn how attackers corrupt training data, inject backdoors, and defend against integrity attacks.

Canonical: https://codelivly.com/learning-paths/data-model-poisoning
Last updated: 2026-10-12

| | |
|---|---|
| Level | Intermediate |
| Category | Cybersecurity |
| Rooms | 5 |
| Lessons | 14 |
| Estimated time | 2 h 30 min |

This intermediate learning path explores the critical vulnerabilities of data and model poisoning in machine learning and AI systems. You will learn how adversaries inject malicious data during the training, fine-tuning, or RAG ingestion phases to create backdoors, introduce bias, or degrade model performance. Through hands-on methodologies and defensive countermeasures, you will master techniques like data provenance tracking, anomaly detection, and model sanitization to secure the AI lifecycle.

## Rooms in this path

1. [What is Data Poisoning and Its Real-World Impact](https://codelivly.com/rooms/what-is-data-poisoning-its-real-world-impact) - Understand the fundamentals of data poisoning in machine learning.
2. [Training-Time vs Inference-Time Poisoning](https://codelivly.com/rooms/training-time-vs-inference-time-poisoning) - Differentiate between training-time and inference-time data poisoning.
3. [Backdoored Models](https://codelivly.com/rooms/backdoored-models) - Understand how attackers distribute and deploy backdoored AI models via supply chain attacks, and learn to detect and…
4. [Model Supply Chain Attacks](https://codelivly.com/rooms/model-supply-chain-attacks) - Master the vulnerabilities of the AI supply chain. Learn how attackers compromise model repositories, exploit…
5. [Guided Lab: Identifying a Poisoned Model Artifact](https://codelivly.com/rooms/guided-lab-identifying-a-poisoned-model-artifact) - A hands-on guided lab demonstrating how to detect hidden backdoors in AI models using activation clustering and…

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