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.
Deep dives, practical guides, and incident analyses from engineers who build Safeguard. No fluff, no vendor FUD — just what you need to ship secure software.
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.
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 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.
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?
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.
Snyk's Evo Agentic Development Security, in open preview since June 23, 2026, hooks directly into an agent's tool calls — proof that pre-deployment review can't govern a decision made mid-session.
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.
Snyk found 76 confirmed-malicious skills among 3,984 analyzed and roughly a third of public MCP servers carrying exploitable flaws — legacy AppSec never modeled an agent as the author.
Claude's May 2026 enterprise and desktop expansion put MCP tool calls in front of compliance teams and IDEs alike — governance can no longer be an afterthought.
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