#Data Leakage — Kunal Ganglani

system logs terminal laptop screen code — illustration for article on LLM Data Leakage Playbook [2026]:

LLM Data Leakage Playbook: Logging, Retention, Redaction

A practitioner playbook for preventing data leakage in LLM apps by hardening logging, retention, and redaction across the entire prompt→tools→model→observability path, with audit-ready evidence you can hand to compliance.

A security and privacy dashboard with its status.

AI and Machine Learning

RAG Data Leakage Test Suite: CI Red-Team Setup

Build an automated red-team suite for RAG apps: canary tokens, regex + similarity detectors, multi-step prompt-injection attacks, and a CI risk score that blocks risky merges.

Keep exploring

Close to this topic, not on this page.

How to Implement Field-Level Redaction for RAG Pipelines An auditor-friendly RAG privacy pattern: deterministic redaction, optional reversible tokenization, TTLs, deletion propagation, and a… 9 min read
Data Privacy in RAG: Redaction, Retention and Audit Trails A practical engineering playbook for data privacy in RAG: what to redact, where privacy leaks happen, default retention periods, and audit… 12 min read
Prevent Sensitive Data Leakage in RAG: A 7-Step Playbook RAG leaks rarely happen in the model. 12 min read