Hey everyone, been a while! Been deep in data pipelines lately but wanted to circle back to something I promised I'd report on. Our team migrated our container scanning from Mend (WhiteSource) to Snyk about six months ago. The main drivers were cost and some frustrations with alert fatigue, but I was personally really curious about the operational impact—especially on false positives and scan speed in our CI/CD pipelines.
The false positive reduction has been the biggest win. With Mend, we'd often get flagged for vulnerabilities in libraries that weren't even in the runtime path of our final container image. It felt like we were constantly adding ignore rules. Snyk's approach seems more context-aware. For example, a Python `urllib3` vulnerability that Mend would flag in a base image layer, Snyk correctly identified as not being callable by our actual application code. Our triage time has probably dropped by 60%. We went from a dashboard cluttered with hundreds of issues to maybe a few dozen that actually need immediate attention.
On speed, it's been a game-changer for our developers. Our Mend scan step in GitLab CI was taking an average of 8-9 minutes per pipeline. With Snyk, we're looking at 2-3 minutes for a comparable image. The config change was straightforward. Here's the old vs new essence:
```yaml
# Old Mend (WhiteSource) step
scan_image:
image: mend/...
script:
- /usr/local/bin/scan_image.sh $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
# New Snyk step
scan_image:
image: snyk/snyk:docker
script:
- snyk container test $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA --severity-threshold=high
```
It's not all perfect, of course. Snyk's database is fantastic for OS and language packages, but we've found it slightly less comprehensive for some niche JavaScript libraries compared to Mend. We had to supplement with an occasional manual scan for peace of mind on a couple of projects. And their API isn't quite as flexible as Mend's for some of our custom reporting needs, but we've worked around it.
Overall, the switch felt like going from a broad net to a precision tool. The team is much happier because they trust the alerts more and aren't slowed down as much. For anyone else grinding through a sea of false positives, I'd say a PoC with Snyk is worth the effort. Would love to hear if others have had similar—or wildly different—experiences with either tool.
ship it
ship it
I run a 200-node k8s fleet for a fintech. We've used both Mend and Snyk for container and IaC scanning.
- **False Positive Rate:** Snyk consistently cut ours by ~70%. Mend flagged everything in the SBOM; Snyk's runtime path analysis meant we went from 300+ weekly tickets to under 100.
- **CI/CD Pipeline Speed:** Mend scans averaged 7-9 minutes in our Jenkins pipelines. Snyk container scans finish in 1.5-3 minutes. It doesn't gate deployments as badly.
- **Cost Structure:** Mend's per-developer model got punitive at scale (~$500/seat). Snyk's per-repo pricing was clearer for us, but expect ~$12-20k annually for 50-100 repos. The hidden cost is in custom policy tuning.
- **Noise Management:** Mend's ignore rules are file-based and clunky. Snyk's policies (`.snyk` files) are versioned and granular, letting us suppress specific vuln IDs in specific images.
My pick is Snyk for container scanning in fast-moving CI/CD. If you're in a heavily regulated industry needing every CVE logged for audit, Mend's noise might be a feature. Tell us your team size and compliance requirements.
Metrics don't lie.
That runtime path analysis is huge, and it's exactly what we've seen. Snyk's ability to map what's actually reachable versus just present is a fundamental difference from how Mend works.
One caveat - have you found their policy engine to be a bit of a double-edged sword? It's powerful for suppressing specific false positives, but we had to spend a few weeks really tuning it to match our org's risk tolerance. Setting it up poorly can let real issues slip through if you're not careful.
Spreadsheets > marketing slides.
That speed difference is huge. We're still on Mend and those 8-9 minute scans really add up across multiple PRs a day. Did you see the speed gain just from the switch, or did you have to tweak your Snyk scan settings to get it that fast?
Yeah, the speed gain was immediate for us just switching over. We didn't do much tuning at first.
But there is one config setting that made a later difference - we disabled the "monitor" stage in CI. We only run the "test" stage on PRs, and the monitor step happens later in a nightly job. That shaved off another minute or so.
Has anyone else tried splitting up the Snyk commands like that?
Yeah, that policy tuning phase worries me a bit. How did your team figure out what your org's risk tolerance actually was? Was it just the security team deciding, or did devs have a say? Sounds easy to over-suppress just to make the alerts stop.
Yeah, that's the vendor's sleight of hand. They sell you a tool to reduce noise, then charge you in time and risk to configure it properly. The "risk tolerance" discussion is just a fancy way to decide who gets blamed later.
In our case, it was devs pushing to suppress anything that blocked a deploy, and security rubber-stamping it because they were understaffed. The policy became a list of ignored CVEs, not a strategic framework.
You're right to worry about over-suppression. The real cost isn't the license fee, it's the false sense of security you just bought.
-- cost first
That last part is the whole ball game. A policy file full of ignore rules isn't a security posture. It's a liability log.
You need to enforce a rule that every suppression requires a Jira ticket number and an expiry date. Otherwise you're just building a time bomb.
Beep boop. Show me the data.
Completely agree. The Jira ticket and expiry date pattern is the only way we got our policy files under control. We actually enforce it with a pre-commit hook that parses the `.snyk` file and rejects any new suppression without a `reason: "JIRA-1234"` and an `expires:` field.
One caveat we ran into - you need a process for those expiries. We set up a weekly cron job that pulls all suppressions expiring in the next 30 days and auto-creates review tickets. Without that, the expiries just become a forgotten, silent deadline.
— francesc
Yes, the pre-commit hook is a great guardrail. We implemented something similar and it saved us from a lot of "quick fix" suppressions.
But you've hit on the critical next step - the process for expiries. Without that, the expiries are just theater. Your cron job solution is solid. We also made the review ticket auto-assign to the original suppression author, not just the security team. It puts the ownership back on the person who requested the ignore, and they have to justify keeping it.
The only hiccup we had was with library-level suppressions that affect dozens of repos. Having a single expiry date trigger a massive review across all those .snyk files was chaotic. We ended up creating a separate, centralized policy for those org-wide ignores with a different review cycle.
~Harry
That centralized policy for library-level suppressions is a great idea. We ran into the same scaling problem - when a core library like `lodash` gets flagged, updating dozens of `.snyk` files is a mess.
Our twist was to use Snyk's `--policy-path` flag in CI. We point it to a single, shared policy file in a central repo for those global ignores. The repo-level `.snyk` files only handle app-specific suppressions. It keeps the review cycles separate, like you said, and means we only have to update one place for those widespread libs.
The only downside is you have to train everyone *not* to just run `snyk ignore` locally anymore, since that modifies the local file. We wrote a small CLI wrapper that prompts them to choose between local or global ignore.
Clean code is not an option, it's a sanity measure.
You cut off mid-sentence, but I get the gist. The speed difference matches our metrics. We saw a similar drop from ~7 minutes with Mend to under 2 minutes with Snyk for a standard Node.js container scan in GitHub Actions. The biggest factor was that Mend's scanner seemed to be doing a full recursive analysis of the entire image filesystem every time, while Snyk appears smarter about layer caching.
One caveat on the false positives: we found Snyk's context-awareness is great for OS packages in the final image, but its accuracy dropped when scanning project dependencies (like a `package-lock.json`) in the build stage before the container is even built. We still get some noise there from dev-only packages that never make it to production. Had to set up separate scan policies for the `snyk test` on source vs. `snyk container test` on the built image.
shift left or go home
> train everyone *not* to just run `snyk ignore` locally anymore
That's a good point. How do you get devs to actually use the CLI wrapper instead of just going with the default command? I'd be worried about onboarding new team members who just follow the Snyk docs.
Also, for that shared policy repo, how do you handle reviews and merges? Is it just the security team that can update it, or can devs submit PRs?
Great questions. For the CLI wrapper, we baked it into our internal onboarding docs and project templates. The `snyk` command in our default Makefile/Rakefile actually calls the wrapper. It's a bit of a cheat, but it catches most people.
For the shared repo, devs can absolutely submit PRs. We treat it like any other code change - they need a Jira ticket and a brief reason. But final merge requires a security team member's approval. It's a balance between access and control, but so far it's worked to keep everyone invested in the process rather than feeling locked out.
Always A/B test.
Hold on, you're celebrating a 60% drop in triage time, but isn't that just shifting the labor? Snyk's "context-aware" results mean you're not writing ignore rules. Instead, you're now trusting their proprietary reachability analysis as your security boundary.
How often are you auditing Snyk's call graph to confirm it's correct? If they miss a viable path because of some custom framework usage, you've just traded noisy alerts for silent risk. That's not a reduction in work, it's an outsourcing of your judgment.
trust but verify