ai-security
Safeguard articles tagged "ai-security" — guides, analysis, and best practices for software supply chain and application security.
593 articles
Securing AI-Generated Code: The New Risk Surface
40.73% of Copilot's suggested code contains a vulnerability, and one 2024 study found nearly 1 in 5 AI-recommended packages simply don't exist.
Securing LLM and Model Supply Chains
JFrog found roughly 100 malicious model files on Hugging Face in 2024 alone — model weights are now a build-pipeline attack surface, and most teams have no SBOM for them.
Security Practices for GitHub Copilot and AI Coding Assistants
Copilot suggested 2,702 hardcoded secrets from just 900 prompts in one study, and at least 200 were live credentials — adoption without policy is a leak waiting to happen.
The security risk of LLMs reviving abandoned open-source packages
USENIX Security 2025 found 19.7% of LLM code samples hallucinate a package name — and real, dormant packages carry the same blind trust.
Vetting third-party agent skills before you install them
AI agent skill marketplaces run installed code with your full permissions and no sandboxing — VS Code's 2025 extension attacks show exactly how that gets abused.
AI Bill of Materials (AI-BOM) for Model Supply Chains
An AI-BOM tracks every model, dataset, and dependency in your ML pipeline so a compromised base model or license issue can be traced in minutes, not weeks.
Slopsquatting: When AI Hallucinates a Package Attackers Register
AI coding assistants confidently recommend packages that do not exist. Attackers noticed. Slopsquatting turns a model's hallucination into a supply-chain foothold — and the fix is not to make models stop hallucinating.
What Is an AIBOM (AI Bill of Materials)? A 2026 Primer
An SBOM tells you what code you ship. An AIBOM answers the question that has no good answer today: what models, datasets, and prompts is our AI actually built on — and where did they come from?
Choosing a security tool for AI-generated code
GitHub reported in 2024 that Copilot writes up to 46% of code in enabled files — the same vulnerability classes humans write, now shipped at machine speed.
How the security industry is scaling partnerships for AI risk
No vendor covers model security, agent runtime policy, supply-chain risk, and code-level AppSec alone — partner-sourced ARR at one major vendor grew over 6x from 2023 to 2025.
How to build and justify an AI security budget
CVE-2025-6514 let a flawed MCP proxy escalate to full remote code execution — a preview of why AI/agentic risk needs its own budget line, not a slice of the AppSec line.
What agentic coding environments reveal about developer risk
Snyk analyzed nearly 10,000 real developer environments and found 43% run 2+ AI coding tools at once — with MCP servers and skills quietly widening the attack surface.
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