How to Scan AI Generated Code: A Four Step Workflow
Scan AI generated code in four steps: secrets, static analysis, dependencies and a human check. Here is what each tool covers and how to run it.
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.
Scan AI generated code in four steps: secrets, static analysis, dependencies and a human check. Here is what each tool covers and how to run it.
Use Claude Code and Cursor securely: keep approvals on, sandbox commands, vet MCP servers, keep secrets from the agent and scan every change before merge.
Prompt injection has no complete fix. Developers cut the damage with least privilege, approvals for risky actions, content separation and adversarial testing.
AI generated code often ships XSS, log injection, hardcoded secrets and invented packages. Catch them with secrets, SAST and dependency scans plus review.
Is vibe coding safe? It is fine for prototypes, but code you ship to real users needs review and scanning first. Here are the checks that matter most.
Vet an MCP server before installing: confirm the publisher, read the tools and descriptions, check CVEs and upkeep, and test how it handles credentials.
Best MCP server security practices: verify publishers, sandbox local servers, use minimum scopes, never pass tokens through, and approve risky tool calls.
To secure AI coding assistants, keep approvals on, sandbox the shell, vet every MCP server, scan what the assistant writes, and set shared team rules.
CERT-In's 15 October 2026 advisory says AI agents under evaluation and misused agentic tools accessed Indian systems through exposed credentials. None of the victims noticed.
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