AI Security
In-depth guides and analysis on ai security from the Safeguard engineering team.
786 articles
Prompt Injection Prevention: A Defense-in-Depth Guide
Prompt injection is the top risk on the OWASP list for LLM applications for a reason: there is no single patch. Preventing it means layering controls around a model that cannot reliably tell instructions from data.
Embedding Model Supply Chain Risks
Embedding models are the silent dependency under every RAG system. We cover poisoning, deprecation, and provenance gaps that break retrieval in production.
AI Model Supply Chain Attacks: How Weights Become Malware
You would never run an unknown binary from a stranger, but teams pull unknown model weights off public hubs every day. Loading them can be code execution — and that is only the most obvious link in the chain.
What Is Agentic Development Security?
When an AI agent can read your repo, run commands, open pull requests, and call external tools on its own, the security model shifts from reviewing code to governing an actor. Here is what agentic development security means and why it is different.
MCP Server Security: 8 Best Practices for 2026
The Model Context Protocol connects AI agents to your tools and data. That power cuts both ways. Here are eight concrete practices for running MCP servers without handing attackers a remote control.
Securing Vector Databases: The Overlooked Attack Surface in AI Apps
Vector databases became critical infrastructure the moment RAG went mainstream, but most are deployed with the security posture of a cache. Embeddings leak, indexes get poisoned, and tenants bleed into each other.
AI Security Software: A Buyer's Guide for 2026
The label 'AI security software' now covers two different markets — tools that secure AI systems, and security tools powered by AI. How to tell them apart, what to evaluate, and the questions that expose thin products.
How Copilot Autofix generates AI-powered vulnerability fi...
Copilot Autofix pairs CodeQL with an LLM to patch code-scanning alerts up to 3x faster. Here's how it works, its limits, and where supply chain risk still slips through.
AI Agent Tool-Use Security: Locking Down What Agents Can Do
The moment you give an LLM tools, it stops being a chatbot and becomes an actor in your systems. Tool-use security is about making sure a compromised agent hits a wall instead of a credential.
RAG Security Best Practices for 2026
Retrieval-augmented generation wired an untrusted-content pipeline straight into your model's context window. Here are the practices that keep a poisoned document or a leaked chunk from becoming an incident.
Securing AI-Generated Code: A Practical 2026 Guide
AI now writes a large share of the code shipping to production, and it reproduces the same insecure patterns humans do — at machine speed. Here is how to keep AI-authored code from becoming your next incident.
Claude Sonnet 4.5 System Card: Security Reading
Anthropic shipped Claude Sonnet 4.5 on September 29, 2025 with a 70-page system card. We pull the supply-chain-relevant findings out of it.
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