Ugh, those webinars are the worst, right? All vision, zero concrete details you can actually use for a budget request.
To your points: the "diff" is real, but it's about removing noise, not finding new critical bugs. Our biggest win was getting rid of all those log4j tickets for dependencies that were declared but never actually packaged. That alone might justify the cost if your team is wasting cycles triaging those.
For your pipeline question, don't use their separate stage setup. It's a trap. Just add the binary scan command as the final step in your existing build job where the artifact is already local. That bypasses the whole fingerprinting mess with tags. I can send you our stripped-down GitLab snippet if you want - it's basically three lines.
null
You're describing the exact architectural limitation that undermines their marketing. Collapsing back into the build job is the only reliable pattern for concurrent pipelines, but it completely reframes the ROI calculation. You're not paying for faster scans, you're paying for accurate filtering at the cost of a longer, heavier build stage.
The speed benefit of incremental analysis only exists in a theoretical, linear pipeline. In practice, with teams pushing to `main` or `latest` from multiple feature branches, the fingerprinting logic fails and you're back to full scans every time. The vendor's case studies never seem to include that fan-in/fan-out scenario.
Our cost justification shifted entirely to the labor savings from eliminating false tickets for unlinked dependencies. The pipeline time became a fixed, accepted overhead.
PM by day, reviewer by night.
Exactly. That network overhead for the initial pull is a significant and often hidden cost, especially if you're billed for compute in that separate stage. A 15-minute scan means 15 minutes of runner time you wouldn't incur if the scanner ran where the artifact was built.
Your point on state confusion with concurrent builds is the architectural flaw. The cost isn't just in slower pipelines, it's in wasted compute from unnecessary full rescans. We had to implement a manual check on the artifact SHA before the scanner step to avoid it, which added more complexity.
CloudCostHawk
You've got the right reaction. If they can't show the diff, it's because it wouldn't look impressive.
That vendor-provided config is probably the one that spins up a separate container for the scanner and tries to pull the artifact. It's a disaster if your registry has any latency.
The "zero false positives" claim is nonsense on its face. It reduces a *specific class* of false positives from unlinked dependencies, but it introduces its own novel class around build toolchain components and compiler optimizations. You'll just get different, more confusing tickets.
Their incremental analysis falls apart with concurrent builds. It's a full rescan if two commits land close together, which is most CI systems.
Trust but verify
Oh, that point about the vendor configs being for show really resonates. I tried using one of their "quick start" jobs last week and spent an hour just trying to get the artifact path right. It's like they assume your pipeline has nothing else in it.
The memory limit warning is new to me, though. When you say set hard limits or it will OOM, do you mean a memory limit directly on the container in the CI job? I'm still getting used to all these YAML settings.
Yes, the shift in ROI justification is spot on. That's exactly the conversation we had internally. It's not about speed at all - it's a pure trade of compute time for team time.
Our finance folks actually got that math right away once we showed them the hours spent closing false-positive tickets. Even with a longer build stage, the total cost went down.
Do you think the vendor will ever address that fingerprinting flaw, or is it just baked into the architecture? It seems like a fundamental mismatch with modern CI patterns.
still learning
You're right to focus on the operational reality, the marketing rarely lines up with it. The zero false positives claim is exactly what you think - marketing fluff. It eliminates one class (unlinked dependencies) but introduces new, weird ones, often around compiler artifacts or stripped symbols.
On your integration pain, yes, their provided configs are for demos, not production. The separate stage is a trap. You'll want to collapse it into your final build step where the artifact is local to avoid all the fingerprinting and registry-pull overhead others mentioned.
The incremental analysis works, but only in a perfect linear flow. With concurrent commits or tags, it frequently defaults to a full rescan, which for a large binary is painful. The 30% uplift is hard to justify on speed; it's really about the time your team saves not triaging phantom log4j tickets. That's the only math that worked for our budget.
That exact config block is a lifesaver. We ran into the OOM issue during our first week because we didn't set that limit.
You mentioned it cuts noise by 80% for Go services. Has that reduction held up across different artifact types for you? We've seen it be very effective for compiled binaries, but the benefit was significantly less for our container scans, where unpacking still pulls in a lot of transitive OS packages that aren't truly "unlinked."
That first bullet point about incremental analysis versus full rescans is the critical one, and the thread already confirms my suspicion. The operational reality is it's a full rescan far more often than the sales material suggests, especially in any environment with concurrent development or frequent merges.
My question, based on the discussion of collapsing the scan into the final build step to avoid fingerprinting issues, is about artifact storage. If you're scanning the binary locally right after creation, does that mean you're storing the raw, unscanned artifact somewhere first, or are you effectively forced to keep the runner alive for the entire duration of the scan before you can push to a repository? That seems like it would tie up expensive CI/CD resources.
The 30% cost justification, then, really does hinge entirely on that labor savings from eliminating false tickets for unused dependencies. I haven't seen a single post here claiming it finds more *real* vulnerabilities than a good source scan.
That webinar format is a classic vendor tactic, focusing on strategic buzzwords to gloss over implementation gaps. The absence of a concrete diff is a red flag.
The "zero false positives" claim is, as you suspect, a gross oversimplification. In practice, it reduces noise from transitive dependencies by analyzing the linked binary, but introduces new false positives related to compiler runtime libraries and stripped debug symbols. Your log4j ticket volume might drop, but you'll trade it for puzzling alerts on standard libc functions or Go runtime components.
For integration, collapsing it into the final build step is the only sane pattern to avoid the fingerprinting issues others have mentioned. But this forces you to keep the runner active for the scan duration, directly trading CI/CD resource time for the promised accuracy. The 30% uplift has to be justified by your team's hourly cost to triage false alarms versus the increased compute time per pipeline run.
—at
You're dead on about the trade-off being compute time versus team time. The vendor never puts it that way because it exposes their weak spot, which is that their efficiency claims only hold if your CI minutes are cheaper than your engineers'.
> puzzling alerts on standard libc functions
This is the real catch. We had to build and maintain an internal allowlist for libc, musl, and the Go runtime. It cut the new noise in half, but now that list is a separate piece of security debt we have to manage. It's just shifted, not eliminated.
And yes, keeping the runner alive is exactly what you have to do. That's where the real cost lives, and why the "30% faster" marketing is so misleading. It's 30% faster than their own awful separate-stage setup, not faster than doing nothing. You're paying for those runner minutes in full.
Speed up your build
Yep, that internal allowlist is a hidden tax. We did the same for our Go services, and now we're stuck curating it for every new toolchain version.
The runner cost is the real kicker. It's not just the minutes, it's also the queue time in a shared pool. When the scan runs for 12 minutes on a hefty binary, you're blocking other jobs. That queue delay adds up fast across the team.
Your point about the 30% being relative to their own bad setup is perfect. It's like getting a discount on a more expensive problem they created.
You're absolutely right about the queue delay being the hidden multiplier. It's not just the 12 minutes of compute, it's the queue buildup during peak merge times. When a 12-minute job sits queued for another 8 minutes waiting for a runner, the *perceived* pipeline delay is 20 minutes, which is what the development team actually feels.
That internal allowlist tax compounds with each new base image or toolchain bump. We found we had to version the allowlist itself and treat it as a separate, vulnerable artifact. It needs its own review cycle, which ironically creates more process around what was supposed to be an automated time-saver.
The only way we made the runner cost tolerable was to implement a dedicated, autoscaling node pool specifically for the final build+scan stage, isolated from the general job queue. But that's yet more operational overhead.
—BJ
The hidden queue delay multiplier is such a real cost that never gets modeled. Your point about perceived delay is spot on, that's exactly what burns team morale.
We tried the dedicated node pool route too, and it worked, but you're right about the overhead. It became another thing to monitor and pay for, which just adds to the total cost of ownership the module promised to reduce. Feels like you're just moving the problem around sometimes.
Keep it simple.
You're asking the right questions. They didn't show the diff because it would show the extra cost isn't just licensing, it's pipeline time and new false positives.
> zero false positives
Pure nonsense. You trade log4j noise for weird flags on compiler libs. Now you have to build an allowlist, which is just more work you own.
The GitLab config they give is useless. It hangs because it doesn't handle the artifact pull properly. You have to collapse it into the build stage, which means your runner is tied up for the whole scan. For a big binary, that's 10-15 minutes of paid CI time blocking the queue.