Hey folks! Long-time lurker, first-time poster here. I've been deep in the Black Duck trenches for about two years now, managing scans for a pretty sprawling microservices architecture. If you're like me, you've probably spent more hours than you'd care to admit manually reviewing and suppressing the same recurring false positives across every single scan. License mismatches for `mit` vs `MIT`, components flagged as "modified" that we know aren't, that one internal library that gets misidentified every time... you know the drill.
I finally hit a breaking point last quarter. Our team was spending something like 15 person-hours a week on triage, and the backlog was demoralizing. The manual suppression workflow in the UI just doesn't scale when you have hundreds of projects and frequent scans. So, I did what any product analytics nerd would do: I built a script to automate it via the Black Duck API.
The core idea is simple: define a set of rules for known false positives, and after each scan, the script finds matching vulnerabilities/licenses and suppresses them with a predefined rationale. This has cut our manual triage work by about 80%, letting us focus on the *new* and *interesting* findings.
Here’s a high-level view of what the script does:
* **Rule-Based Matching:** It uses a YAML config file where we define our suppression rules. A rule can match on component name, version, vulnerability ID (CVE), license name, and even specific file paths.
* **Bulk Operations:** It fetches project/version details, retrieves vulnerabilities and licenses, applies the rules, and then performs suppressions via the API in batches.
* **Audit Trail:** Every automated suppression gets a standard comment like `"[Auto-Suppressed] Known false positive - internal fork."` so we can always track what was done by the script vs. a human.
* **Dry-Run Mode:** Crucial for testing! You can run it with `--dry-run` to see what *would* be suppressed before actually touching your instance.
For example, one of our rules looks like this (simplified):
```
- component: "our-internal-utils"
version: "*"
vulnerability_id: "BDSA-2024-1234"
reason: "Internal component, not vulnerable."
scope: "ALL_VERSIONS"
```
The real power is combining criteria. We have a rule that catches a specific false-positive CVE *only* when it appears in a certain version range of a library *and* in a non-production file path.
I'm thinking of cleaning up the script and sharing it on GitHub. Before I do, I'm super curious:
* Has anyone else built something similar? I'd love to compare approaches or merge ideas.
* What are your most persistent false positive categories? For us, it's definitely modified component flags and license normalization issues.
* Would a tool like this be useful for your team? What features would you need to see to adopt it?
I'm a big believer in product-led growth and making tools work for us, not the other way around. Automating this repetitive task has been a game-changer for our team's ROI on security reviews.
🔥
Try everything, keep what works.