AI Security
In-depth guides and analysis on ai security from the Safeguard engineering team.
676 articles
Can AI write secure code? Auditing AI-generated code
AI writes code fast, but studies from 2021 to 2025 show it also reproduces insecure patterns and invents fake dependencies. Here's what the data says.
GitHub Copilot code security: XSS vulnerabilities found in React
Copilot commonly suggests dangerouslySetInnerHTML and unsanitized DOM writes in React. Here's the data on AI-generated XSS risk and how to catch it.
How Copilot amplifies insecure codebases
Copilot writes ~46% of code where enabled, and studies show ~40% of its security-relevant suggestions are vulnerable. Here's the data on the risk.
How to Audit the Dependencies of an AI Agent
An AI agent's dependency tree spans packages, MCP servers, models, and system prompts. A step-by-step audit method that actually enumerates all four layers.
AI-Generated Code Security: risks and controls
AI now writes up to 40%+ of new code, and models hallucinate nonexistent packages in 5-22% of outputs. Here's why Black Duck-style SCA misses that risk, and what controls actually work.
5 best practices for adopting GitHub Copilot securely
GitHub Copilot has 1.3M+ paid seats. Five concrete, evidence-based practices for locking down content exclusion, licensing, code quality, and prompt injection risk.
AI hallucinations and their security implications for developers
LLMs hallucinate nonexistent packages in up to 1 in 5 code samples — and slopsquatting attacks are already exploiting that predictability in the wild.
Security in AI Systems: What Actually Changes
Security in AI systems isn't a wholly new discipline, but prompt injection, training data provenance, and model supply chains introduce risks traditional AppSec tooling wasn't built to catch.
Introducing Agentic Development Security (ADS)
As AI agents now author up to half of production commits, Safeguard introduces Agentic Development Security (ADS) — a new framework for securing autonomous coding.
Safeguard Now Supports Every Major AI Model Family for Zero-Day Discovery: Anthropic, OpenAI, Gemini, Microsoft, Meta, and Your Own Models
You should not have to choose between your organization's AI strategy and your security platform. Safeguard's agentic zero-day discovery and remediation pipeline now works on Anthropic Claude Fable 5, OpenAI GPT, Google Gemini, Microsoft Phi, Meta Llama, Safeguard native models, and privately hosted custom models — all running as first-class agents in the same Multi-Agent TAOR Deep Think AI Engine.
Anthropic Claude Mythos Releases Tomorrow: Capabilities, Benchmarks, and What Security Teams Must Do Now
Anthropic's Claude Mythos model goes public on June 10, 2026 — a frontier AI that scored 97.6% on the Math Olympiad, completed expert-level hacking tasks at 73% success, and found 271 vulnerabilities in Firefox 150. Here is everything security teams need to know before it lands, and how Safeguard already supports Mythos zero-day discovery natively.
Claude Fable 5: Anthropic's Most Capable Public Model Is Here — Benchmarks, Capabilities, and What It Means for Security
Anthropic just released Claude Fable 5, its most capable publicly available model and the first Mythos-class AI open to everyone. 80.3% on SWE-Bench Pro, 88% on Terminal-Bench 2.1, state-of-the-art across software engineering, vision, and scientific research. Safeguard has already integrated Fable 5 natively — here is everything you need to know.