Analysis
AI Security Lesson 39: Training Data Poisoning Explained for Teams
Publication date unknown · Discovered youtube.com
Page published
Publication date unknown · First observed: 11 Oct 2026
Coverage timeline
Single-source analysis — one report is available.
Why it matters
Training data poisoning lets attackers embed hidden malicious behavior into models that pass validation cleanly, making it a supply-chain risk defenders of ML and LLM pipelines must understand and screen for.
An educational YouTube video from SecureTechIn (AI Security Lesson 39) explains training data poisoning, covering label-flip attacks that shift a classifier's decision boundary and backdoor triggers that survive validation. It references prior work including BadNets (2017) and Sleeper Agents (2024), maps the threat to OWASP LLM04 and MITRE ATLAS, and walks through a toy demo plus a four-step defensive workflow (provenance, canaries, screening, backdoor scanning).