AI Security
Prompt injection, leakage, unsafe tool access, permissions, and production failure modes.
14 stories (7 articles · 7 videos)
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14 min readPrompt injection and LLM security: threat models and defense-in-depth
Prompt injection is a permanent LLM security class, not a prompt-writing mistake. A production guide to threat models, data boundaries, tool permissions, regression tests, monitoring, and incident response.
Advanced
10 min readCompany knowledge RAG: permissions, leakage, and source boundaries
A company knowledge assistant is only safe if retrieval respects permissions. How to design RAG source boundaries, ACL filtering, document ownership, logging, stale-source handling, and refusal behavior.
Advanced
11 min readSecure document ingestion for RAG: PDFs, OCR, metadata, and retention
RAG quality starts before retrieval. A secure ingestion guide for PDFs, OCR, metadata, permissions, source freshness, deletion, malware risk, and operational ownership.
AdvancedMore in this topic
20 minutesPermissions & Access Control for RAG - a Deep Dive Tutorial
Paragon. Walks through the production RAG permission problem and compares tool-calling, namespaces, ACL tables and relationship-based permissions. That directly supports the article's core rule: retrieval must only return sources the current user is allowed to see, and source-system permissions cannot be treated as an afterthought.
Advanced
69 minutesThe Agent Landscape - Lessons Learned Putting Agents Into Production
MLOps.community. Prosus's VP of AI and an AI engineer report what actually broke when they deployed agents across the group's portfolio companies: prompt-injection pen-testing before launch, an unsafe write when a Jira agent choked on human shorthand, stale context handled by making agents surface their assumptions, and fallback design that merged or killed agents once they added cognitive load. It reads like the article's failure-mode register replayed as a live postmortem.
Advanced
7 minutesUnlock Better RAG & AI Agents with Docling
IBM Technology. Explains the ingestion side of RAG and agents: preparing PDFs and other files so document structure, tables and layout survive into downstream retrieval. That supports the article's warning that RAG quality and safety begin before embedding, especially when parsing complex business documents.
Advanced
10 min readPrivate AI deployment patterns: local, VPC, self-hosted, and hybrid
Private AI is not one architecture. A practical comparison of local models, enterprise SaaS, VPC deployments, self-hosted inference, and hybrid patterns for SMEs that care about privacy and control.
Advanced
10 min readProduction AI failure modes: what breaks after the demo
AI systems usually fail in predictable ways: hallucination, stale context, sycophancy, prompt injection, unsafe tool use, schema drift, and weak fallbacks. A production failure-mode register for teams shipping real workflows.
Advanced
10 min readConnecting AI to your email, calendar, and CRM safely
Connecting AI to your real tools — email, calendar, CRM — is the productivity unlock and the risk. A practical guide to the integrations that work in 2026, the patterns that are safe, and the lines you should not cross.
Intermediate
8 min readPrivacy and data hygiene when using AI at work
A practical guide to using AI at work without accidentally exposing customer data, breaching your company's policy, or violating GDPR. The lines, the tools, and the habits to build.
Beginner
25 minutesOWASP's Top 10 Ways to Attack LLMs: AI Vulnerabilities Exposed
IBM Technology. Zooms out from prompt injection to the wider OWASP Top 10 for LLMs — insecure output handling, sensitive information disclosure, excessive agency — which is exactly the failure-mode catalogue you want in mind before you grant Gmail or HubSpot scopes to anything.
Intermediate
11 minutesWhat Is a Prompt Injection Attack?
IBM Technology. Jeff Crume's "buy an SUV for $1" example is the cleanest 10-minute explanation of why direct and indirect prompt injection are different problems, and why filtering can't fully solve either. It pairs directly with the article's argument that you need least-privilege scopes, a dedicated agent account, and a human in the loop on anything irreversible — not a cleverer system prompt.
Intermediate
13 minutesAttacking LLM - Prompt Injection
LiveOverflow. Frames prompt injection as a classic injection attack against systems that mix instructions and untrusted data — with a concrete content-moderation example where an attacker frames an innocent user. The mental shift from "the model is the target" to "the application is the target" is exactly the move the article opens with.
Advanced
17 minutesDefending LLM - Prompt Injection
LiveOverflow. Walks through the actual defence-in-depth playbook — taint analysis on LLM output, restricting expected output shapes, user isolation, few-shot scaffolds, fine-tuning, temperature 0 for determinism, redundancy for critical paths. It matches the article's defence-stack section almost item for item.
Advanced