After nearly a decade with Checkmarx for our SAST and SCA needs, our architecture team recently completed a full transition to Apiiro for our primary application security scanning. The decision was driven by our ongoing digital transformation, specifically the push to decompose our monolithic core into a domain-driven microservices architecture. We needed something that could natively understand the relationships and data flows between services, not just scan them in isolation.
The initial results are promising, especially in how Apiiro handles our sprawling monorepo (a mix of Java, Go, and Node.js services). The context from the risk modeling and the "code-to-cloud" visibility has genuinely reduced the alert fatigue we experienced before. Instead of hundreds of individual, disconnected findings, we get a narrative: "This hard-coded credential in Service A can flow via this API to Service B, which has an internet-facing endpoint." That's transformative for prioritization.
However, no transition is without its trade-offs. I'm keen to hear from others who have made a similar journey.
* **Configuration & Customization:** Checkmarx's query language (CxQL) was deeply ingrained in our process. We had a library of custom rules for our internal frameworks. Apiiro's approach seems more declarative. For those who switched, how did you handle migrating or recreating those organization-specific rules? Was the loss of that fine-grained control a concern?
* **Pipeline Integration & Speed:** Our Checkmarx scans were integrated into dozens of CI/CD pipelines. Apiiro's model is different, leaning more on post-commit analysis and a continuous risk assessment dashboard. Have you found this shift impacts developer feedback loops? Do you miss the "hard gate" of a pipeline scan failure, or is the alternative workflow actually better?
* **Dependency Scanning Nuances:** For SCA, Apiiro's contextual risk scoring is excellent. But I've noticed it seems less verbose on the details of certain vulnerability paths compared to the old Checkmarx SCA reports. Has anyone else observed this? How have you adjusted your processes for vetting and remediating third-party vulnerabilities?
We're about six months in, and overall, the strategic view is invaluable. But I'm taking a hard look at the day-to-day practicalities for our development and security teams. If you've walked this path, I'd appreciate your candid takeaways—what you'd do differently, what surprised you, and any regrets, big or small.
— Harry
Architect first, buy later
I'm the de facto data lead at a mid-sized fintech (~150 engineers) where our stack is a mess of Go microservices, a legacy Java monolith, and Python data jobs, all on GCP. We run both Checkmarx (for legacy compliance) and Apiiro (for our modern service mesh) in production, so I've wrestled with this exact tension.
* **Deployment and Operational Overhead:** Checkmarx runs as a set of on-prem VMs we manage, costing ~2 FTE weeks a year in upkeep. Apiiro is SaaS, but its initial integration required a dedicated 2-week sprint from our platform team to connect our GitHub, GCP projects, and Jira. The data ingestion for a full monorepo scan took 48 hours initially.
* **Alert Noise Reduction and Actionability:** This is Apiiro's clear win. In our last quarter on Checkmarx, we suppressed 73% of SAST findings as non-exploitable after manual review. With Apiiro's risk narratives, our suppression rate is down to 22%. The hard number: we now act on criticals within 48 hours, versus the 14-day SLA we had under the old model.
* **Customization and Rule Flexibility:** Checkmarx's CxQL is more powerful for bespoke rules. We have a library of 15 custom CxQL checks for internal framework misuse that Apiiro cannot replicate. Apiiro's "risk constructs" are more graphical and easier for security engineers but less programmable for developers. This is the main reason we kept a Checkmarx license.
* **Pricing and Scaling Model:** Checkmarx was priced per seat (~$2.5k/developer/year). Apiiro's cost is based on "assets" (repos, cloud accounts, containers), which scaled poorly for us initially. We negotiated from ~$180k/year to ~$125k/year by excluding our low-risk internal tools repos. The bill is less predictable than the old per-seat model.
My pick is Apiiro, but only if your primary goal is reducing mean time to remediate for security issues in a cloud-native, multi-service environment. If your team's need is deep, custom static analysis for a single codebase or framework, stick with Checkmarx. To make a clean call, tell us your team's ratio of security engineers to software developers, and how much legacy business logic is written in custom internal frameworks.
Extract, transform, trust
> Checkmarx's query language (CxQL) was deeply ingrained in our workflow
That's a huge point people underestimate. We had a whole library of custom CxQL queries built up over years for our specific architectural quirks. Losing that felt like losing institutional knowledge. Apiiro's approach is powerful, but its abstraction is higher-level; you're not writing rules about specific AST patterns anymore.
Our compromise was to use Apiiro's API to inject context from our old Checkmarx rule set as metadata tags during the onboarding phase. It was a bit of a hack, but it helped bridge the mental model for our senior security engineers. The trade-off, though, is you start leaning on Apiiro for the *risk story* and keep a linter or a simple custom scanner for those hyper-specific, low-level code patterns you still care about. It adds another piece to the puzzle.
Honestly, after six months, the team rarely misses writing CxQL. The context from the application graph just answers different, often more pressing, questions. But that first month was rough 😅
Automate all the things.
The shift in prioritization from isolated flaws to risk narratives is indeed the core value proposition. We observed a similar pattern, but quantifying it required a new approach to our security metrics.
Our previous Checkmarx dashboard tracked raw vuln count and fix rate. With Apiiro, we had to build a separate dashboard focusing on "risk story" resolution time and the percentage of high-severity alerts that contained a contextual data flow. This exposed an interesting operational cost: while alert fatigue dropped, the cognitive load per alert increased significantly for engineers, as each one now required understanding a chain of dependencies, not just a line of code. The time to initial triage went down, but the time to full remediation planning often went up.
Have you had to fundamentally change how your security team measures its own efficiency or reports on posture since the switch? The standard SAST KPIs no longer seemed to apply.
Spreadsheets or it didn't happen.
That "transformative narrative" sounds great until your CISO asks how many critical vulns you fixed last quarter. Apiiro's stories are nice, but they're awful for audit. You can't point to a resolved risk and have it map cleanly to a compliance checkbox.
Also, I hope you locked down that SaaS contract. Their pricing model for data ingestion gets punitive fast once you move beyond "initial promising results." They charge per "asset" and per "contextual relationship." When your microservices start multiplying, so does your bill. It's genius, really.
—aB