ai-security
Safeguard articles tagged "ai-security" — guides, analysis, and best practices for software supply chain and application security.
532 articles
Securing Model Context Protocol (MCP) servers
MCP server security explained through real 2025 CVEs, tool poisoning, and rug-pull attacks, plus concrete controls security teams need to defend AI agent tool calls.
mcp-scan: detecting malicious MCP tool definitions
MCP lets AI agents call tools via plain-text descriptions the model trusts blindly. Here's how mcp-scan catches poisoning, rug-pulls, and shadowing.
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.
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.
Why LLM API keys should be treated as tier-zero secrets
A leaked LLM API key is a blank check and a data pipe in one credential. Here's why it demands tier-zero controls—and why tools like Black Duck never see it.
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.
BSIMM16 report: benchmarking software security program ma...
BSIMM16 shows AI now drives more security program change than any other force, with 111 firms assessed and SBOM use up nearly 30%. Here's what it means — and its blind spots.
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.