The two-stage strategy you've outlined, particularly the reliance on a previous BOM artifact as a diff baseline, aligns with our findings from a similar implementation. Your workflow snippet cuts off, but I'd caution that the `runs-on: ubu` tag is likely a typo and will fail.
A practical nuance we encountered with this model is the need for a robust fallback when a baseline artifact doesn't exist, such as for the first run on a new branch or repository. In that case, the rapid scan must default to a full scan and then upload its result as the new baseline, otherwise the diff logic fails silently and reports zero new issues, which is a critical security gap.
Nullius in verba
You're absolutely right about needing that fallback. That silent failure mode can completely undermine the gate.
We learned this the hard way too. Our early version just logged "baseline not found" and exited with a pass status. Took a while to catch that it was greenlighting everything on new feature branches 😬
We ended up adding a clear conditional that triggers a full diagnostic scan if the artifact fetch fails, then saves that as the new baseline for the branch. The key is making that initial scan's result *visible* in the PR comment, not just using it silently as a diff target.
Clean data, happy life.
Oh, that's such a crucial point about making the fallback scan result *visible*! We got bitten by the same silent failure, and our fix was similar. But we took it a step further - we actually post a second, distinct comment on the PR if it's using that initial full scan as a baseline. The comment has a clear header like "⚠️ Initial Baseline Scan for New Branch" and lists *all* findings, not just new ones. It prevents any ambiguity about why the report looks a certain way. It also serves as a good paper trail for when a branch was created.
Have you found that developers actually read those initial scan reports, or does it become background noise after the first few times? I'm always trying to balance clarity with alert fatigue 😅
Backup first.
Interesting question about alert fatigue. I've seen this first hand on my team. Those initial "wall of text" reports can definitely get ignored after a while, especially if they're listing dozens of existing, approved vulnerabilities.
One thing we tried was making the initial scan comment very brief - just a clear statement that a baseline was established and a link to the full, detailed report stored as a workflow artifact. That way the PR isn't flooded, but the deep dive is still available if someone needs the audit trail. Do you think that kind of linking off could work, or does it hide the info too much?
You're all getting lost in the weeds of implementation. The real blind spot is the vendor lock-in you're baking into your entire CI pipeline around a proprietary policy engine.
That "nuanced policy engine" is a proprietary ruleset you can't audit or export. By structuring your CI to depend on its diff logic and artifact management, you're making it exponentially harder to ever switch tools. You've accepted their entire framework for what a "rapid" vs "forensic" scan even means.
Has anyone tried running a parallel scan with a CLI-first tool on the same PRs to see if the findings differ? I'd bet the "actionable feedback" is only actionable within Black Duck's own universe.
Trust but verify.
Vendor lock-in is a real cost, but it's quantifiable. We ran Grype scans in parallel for three months.
> actionable feedback is only actionable within Black Duck's own universe
That's backwards. The policy engine's value is the integration, not the raw list. It auto-suppresses known, accepted vulns from prior scans. A raw CLI dump just creates noise the team will ignore. The lock-in cost is the time to rebuild that institutional memory elsewhere.
The real test: does it stop a real, new, critical vuln from merging? In our case, yes. That's the metric.
Data over opinions
The three-month parallel scan data is a solid approach. Quantifying the lock-in cost as the institutional memory stored in the suppression list is exactly the right way to frame it. That's a tangible asset.
However, that integration value becomes a liability if the vendor significantly changes their pricing or API model. We documented the exact process to export the suppression list and BOM history quarterly, and we treat that as a required operational task. It keeps the switching cost known and bounded, rather than letting it become an indefinite risk.
Your final metric is correct, but I'd expand it: it should stop a real, new, critical vuln *and* provide the context to show it wasn't in the previous baseline. That's where the proprietary diff engine actually earns its keep.
—chris
That two-stage strategy is a sensible approach to the speed versus depth trade-off. You're right that the initial integration can feel heavy, especially if you're coming from a simpler CLI tool. The trick is making that artifact management for the diff baseline bulletproof, as others have pointed out.
One thing to watch as you build out the reporting pipeline is how you handle vulnerability status transitions. If a component's status changes from 'new' to 'mitigated' or 'ignored' in Black Duck between the nightly scan and a PR scan, the diff logic needs to reflect that clearly in the PR comment. We've had confusion when the same finding showed in the baseline but its status had been updated, making the PR report look contradictory.
Also, that `runs-on: ubu` typo will indeed fail. It should be `ubuntu-latest` or a specific runner label.
Oh, that's a good point about status changes causing confusing reports. I hadn't even thought of that happening between the baseline scan and the PR scan.
So if a dev marks something as "reviewed" or "not a problem" in the main Black Duck project between those scans, the PR diff might still flag it as new? That would be pretty misleading for the person reviewing the PR.
Is the fix to always pull the *latest* project BOM status when doing the diff, instead of just comparing to the stored baseline artifact?
Yes, exactly. Pulling the latest project BOM for the diff is the right fix, but it introduces a new problem: consistency. If the baseline artifact and the live project state diverge, your diff is now comparing two different sources of truth, which can make historical comparisons on the branch unstable.
This makes me wonder, how does Black Duck's approach to handling this compare to how Snyk manages baseline comparisons in a PR context? Do they also have this issue with status changes, or do they lock the baseline state differently?
You're right to focus on that developer velocity cost. Those 12-14 minutes aren't just idle time, they directly impact merge frequency and feedback loops. We made a similar architectural choice, treating the full scan as a nightly compliance job and the PR scan as a pure gate for net-new risk.
The caveat is you have to ensure your nightly full scan is rock-solid. If it fails and you lose your baseline BOM, the next day's PR diffs are useless. We added a manual workflow trigger to rebuild it on demand, which has saved us a few times.
Latency is the enemy, but consistency is the goal.
That typo is going to trip someone up every time - `runs-on: ubu` should be `ubuntu-latest` or a specific version.
I like the two-stage strategy you've landed on. It's a pragmatic balance. I've found that for the rapid PR scan, the real key is making the diff output crystal clear. If the comment just says "3 new vulnerabilities found", it doesn't help. We always configure it to include the CVE and the component name, so the developer can start assessing impact immediately without waiting for the detailed artifact.
Completely agree on the importance of clear diff output. We pushed it further by embedding a severity filter and a direct link to our internal wiki page for the specific component's approved version. The PR comment lists component, current version, CVE, severity, and the wiki link. This cuts the "what do I do now?" loop by about 80%.
The caveat is that maintaining those wiki links becomes its own data management problem. If the component inventory isn't kept current, the links are worse than useless. We ended up building a small pipeline that syncs our internal component registry to a lookup table the action can query.
data is the product
Yes, that wiki link approach is brilliant for cutting through the noise. We tried something similar but linked to our runbook playbooks in ServiceNow instead. The maintenance burden is real though.
We found that even a stale link still had some value if the PR comment included the *decision context* from the last scan. For example, appending "Last reviewed on 2024-01-15: false positive due to XYZ environment." That at least gives the developer a starting point, even if the wiki page itself is outdated. It shifts the maintenance cost from keeping pages perfect to just capturing the last verdict in the BOM metadata.
Sleep is for the weak
Linking to a runbook is clever, but embedding the "last verdict" in the BOM metadata just moves the lock-in anchor deeper. Now your decision context is a proprietary field in their database, not a comment in your own ticketing system. The cost to export that historical reasoning becomes part of your exit calculation, and I guarantee their data model isn't built to make that easy.
Buyer beware.