Security auditing tools built for developers.
40 articles· page 1/4
It's not one big mistake — it's a handful of small habits around pasting, chat context, and agent scope. Here's the specific checklist to close the gap.
90% of developers use AI coding agents weekly now, and many run with default full access. Here's how to actually calculate the right scope for a given task.
Peak traffic runs several times higher than daily average — a rate limit sized for the average silently throttles users right when it matters most. Here's how to actually calculate the right number.
90% of developers use AI coding agents weekly now. Here's what to actually scan for in a diff before approving it — the patterns AI agents specifically tend to introduce.
90% of developers use AI agents weekly now. The convenience is real — so is the 10x jump in AI-assisted security findings. Here's a concrete checklist to close the gap.
Unit 42 measured a 78.3% attack success rate once five MCP servers are connected. Over 30 CVEs were filed in two months. Here's what to actually audit before connecting one.
A vague "schema validation failed" error wastes time. Here's what actually matters when validating JSON against a schema, and how to get field-level errors instantly.
UUIDs and ULIDs solve the same problem differently — one is pure randomness, the other is sortable by creation time. Here's how to pick correctly.
X-RateLimit-Reset, RateLimit-Reset, and Retry-After all mean slightly different things — here's how to tell them apart and avoid a common off-by-a-billion bug.
Inherited regex in a codebase is one of the most common sources of quiet fear among developers. Here's a systematic way to read any pattern token by token.
The Dockerfile mistakes that pass code review every time — unpinned base images, root containers, and layer bloat — and how to catch them before they ship.
Why guessing at CPU and memory values leads to throttled pods or wasted cluster capacity, and how to size them from real usage.