How do you secure an AI coding assistant for a team?
Secure an AI coding assistant by limiting what it can read, what it can run, who approves its actions, and what checks run on its code before merge.
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.
Secure an AI coding assistant by limiting what it can read, what it can run, who approves its actions, and what checks run on its code before merge.
Run npm audit in a project that has a package-lock.json. It sends your dependency list to the registry and returns known vulnerabilities and fixes.
Run dependency, code, secret and config checks on each pull request and fail only on new high severity findings. Steps, gate rules and mistakes.
Add an SCA plugin such as OWASP Dependency-Check to your Maven build, inspect the dependency tree, and expect some false positives from name matching.
Scan each layer of a GPU inference image: OS, GPU libraries, Python packages and your app. Build an SBOM at build time and rescan after release.
Run a short passive baseline on every merge, a deeper active scan nightly or pre-release, and decide up front which exit codes fail the pipeline.
Run apt-get update and install in one RUN step, skip recommended extras, and clear package lists. Here is why each choice matters for size and security.
Delete the imports, run go mod tidy, and use go get module@none when needed. How to confirm a Go dependency is gone from go.mod, go.sum and the binary.
A wheel filename encodes name, version, Python tag, ABI tag and platform tag. Learn to decode py3-none-any and cp312 style names and spot a wrong wheel.
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