Hey folks, I just had one of those lightbulb moments that’s equal parts “wow, that’s clever” and “oh no, I’ve been doing it wrong” 😅. I’ve been deep in automating our security scan workflows via Veracode’s APIs, and I stumbled onto something crucial about policy configuration that isn’t immediately obvious in the docs.
We’ve been using the Policy API to enforce rules automatically after each scan, and I always assumed the platform evaluated all rules with equal weight, maybe in parallel. Turns out, **the sequence of your policy rules directly determines what gets flagged and what passes**. It’s not just a list of conditions—it’s an execution order!
Here’s a simplified snippet from our config that caused the headache. We initially had:
```json
{
"policy_rules": [
{
"rule_type": "severity",
"threshold": "high",
"action": "fail"
},
{
"rule_type": "cwe",
"identifier": "CWE-89",
"action": "warn"
}
]
}
```
The intent was to fail any build with a high-severity flaw *and* warn specifically for SQL injection (CWE-89). But because the severity rule came first, a high-sev SQL injection flaw would trigger the “fail” action and the CWE-specific rule never even got evaluated! We missed granular reporting on those specific CWEs because the policy stopped processing after that first match.
I restructured it to prioritize the specific CWE rule first, so we get the detailed warning *before* the overarching severity fail:
```json
{
"policy_rules": [
{
"rule_type": "cwe",
"identifier": "CWE-89",
"action": "warn"
},
{
"rule_type": "severity",
"threshold": "high",
"action": "fail"
}
]
}
```
Now, a high-severity SQL injection flaw logs both a CWE warning **and** triggers the build failure, giving us richer data in our webhook payloads to our incident channel.
Key takeaways for my fellow automation enthusiasts:
* **Policy rules are evaluated top-down, like a firewall ACL.** The first matching rule for a given flaw is applied, and evaluation can stop there unless you configure otherwise.
* This impacts what data surfaces in your API calls and webhooks—order shapes your feedback loop!
* If you’re building pipelines that react to policy results (e.g., via Jenkins, GitHub Actions, or an iPaaS like Make), double-check your rule sequence to ensure you’re capturing the nuance you need.
Has anyone else run into this? How are you ordering your rules to balance broad security gates with specific, actionable alerts? I’d love to compare notes—maybe there’s a best-practice pattern emerging.
Happy integrating, Bob
null
You're absolutely right about the implicit execution order, and it's a classic pitfall in declarative policy systems. This behavior mirrors how network firewalls or IAM policies work, where the first matching rule is the only one that fires. The system is essentially performing a short-circuit evaluation.
What's particularly subtle is that this often isn't a bug, but a design choice for performance and determinism. The policy engine stops processing on the first rule match to guarantee a single, unambiguous outcome. The documentation should be clearer, but you've correctly diagnosed the engine's behavior as a sequential decision tree rather than a parallel filter set.
A useful pattern I've adopted is to order rules from most specific to most general. For your case, placing the specific CWE-89 rule first would allow it to apply its "warn" action, while any other high-severity flaw (not CWE-89) would then be caught by the subsequent, broader rule. This gives you the granular control you intended.
—BJ