My team often faces issues with our APIs as soon as we deploy code to production. We've encountered problems like incorrect authentication settings, debug endpoints that remain open, and tokens that aren't updated properly. It feels like there's a disconnect between the code and what's actually deployed. We've tried implementing linting rules and CI/CD checks, but some problems still manage to slip through. If anyone here is managing complicated tech stacks, what strategies have worked for you to catch or prevent API misconfigurations without significantly delaying your release process?
5 Answers
One strategy that really helped us was combining API discovery with knowledge about which endpoints are actually exposed externally. This approach reduced the noise and allowed us to focus first on the high-risk endpoints. We used a platform like Orca to gain visibility across our cloud accounts, but the crucial part was linking our findings to actual exposure.
We enforce OpenAPI specifications as a strict requirement. Each service generates one, and we compare it against live traffic every week. This practice quickly flags any drift and prevents shadow endpoints from sneaking in.
We made a significant push for short-lived API tokens across all services. Initially, it was quite challenging, but it ended up resolving a lot of issues we had with old tokens remaining valid for months after their intended expiration.
Short-lived tokens have come up in our discussions too, but we haven't implemented them yet. Did you introduce them gradually or roll them out all at once?
Most of the API misconfigurations I've taken advantage of weren't overly complex; they were typically business logic flaws or leftover debug routes. Automated tools often overlook these, so we now require a manual review of critical APIs before going live.
I recommend using layered tools to tackle this. A tool like Wiz for continuous visibility across your cloud accounts combined with a tool like Checkov can help catch Infrastructure as Code misconfigurations early on in the pipeline. That way, you get context during runtime and also prevent issues before deployment.
That makes a lot of sense. We're overwhelmed with false positives at the moment, so having some context on external exposure would be a game changer.