ASPM Showdown: Legit Security vs. Cycode vs. Apiiro vs. OX Security

Before getting into architecture, here is a compact side-by-side of the core positioning differences, based on each vendor's own published materials and the comparison pages cited in this guide.

All four require a sales conversation for pricing. Treat any specific dollar figure you see quoted online for these platforms as unverified unless it comes directly from your own quote.

The marketing language across this category converges on similar words (graph, correlation, code-to-cloud), so the real differentiation is in what each platform uses as its primary data source and reconciliation method.

Legit Security builds what it calls an AppSec knowledge graph. It combines its own deep code analysis with pipeline analysis to produce an SDLC inventory (sometimes described as a pipeline bill of materials) and a visual graph of build assets. The pitch is broad SDLC visibility rather than depth in any single area, backed by a claim of reducing secrets-scanning false positives through contextual and active validation.

Cycode's correlation model centers on change impact analysis (CIA), which builds material change logs to understand what actually shipped and where. It layers a pipeline bill of materials on top, tracking CI/CD steps, runners, dependencies, and credentials, and traces findings from source through deployment to runtime infrastructure. Cycode ships proprietary SAST and SCA scanners alongside its correlation layer.

Apiiro's architecture is the most code-centric of the four. Its Deep Code Analysis (DCA) engine maps software architecture and traces components (APIs, open source packages, containers) back to code owners, enriching each with business impact. The Risk Graph it produces is how Apiiro implements cross-scanner correlation: findings from your existing SAST, DAST, SCA, container, IaC, secrets, and CSPM tools land in one queryable graph, and duplicate findings are reconciled through code-behavior fingerprinting rather than relying on CVE IDs matching exactly. Apiiro's SCM and runtime integration is agentless and API-based, which reduces the manual tagging typically required by asset-inventory-style ASPM tools.

OX Security's model is built around a Pipeline Bill of Materials (PBOM) that tracks every artifact, dependency, build step, and credential through the build lifecycle, oriented primarily at software supply chain posture. More recently OX has shifted its narrative toward prevention rather than detection, adding an in-IDE agent (branded VibeSec) that aims to catch insecure code before it is committed rather than surfacing it after a scan. That is a meaningfully different philosophy from the other three, which are fundamentally post-scan correlation layers.

Every ASPM platform is only as useful as what it can actually see, so integration breadth and depth matter more here than in almost any other security tool category.

Legit Security publishes the broadest integration count of the four, listing more than 100 connectors across AppSec tools, source code management, CI, artifact registries, cloud, cloud security, identity management, and ticketing. It also ships an MCP server that exposes its security intelligence directly to AI coding assistants such as Cursor, GitHub Copilot, Claude Code, and Windsurf, plus an open-source misconfiguration scanner (legitify) for GitHub and GitLab.

Cycode's documented integration strength is concentrated on source control (GitHub, GitLab, Bitbucket, Azure DevOps) and CI/CD pipeline security, which lines up with its change-impact-analysis architecture. If your primary risk surface is pipeline tampering or CI/CD misconfiguration rather than broad SDLC asset sprawl, this is a narrower but more targeted fit.

Apiiro's integration model is explicitly agentless and API-based for SCM and runtime environments, which lowers onboarding friction because there is no manual tagging or labeling step to maintain. Its 2026 CLI extension targets AI coding agents specifically, exposing skills to query risk, scan code, validate changes, apply policy, fetch threat models, and surface prompt context directly inside CI pipelines.

OX Security lists integrations with GitHub Actions, GitLab CI/CD, Azure DevOps, Jenkins, Jira, and Slack, plus IDE plugins for its in-editor VibeSec agent. Its integration depth is oriented around build-pipeline visibility and developer-tool presence rather than the broad third-party AppSec tool ingestion Legit Security emphasizes.

Vendor comparison pages rarely spell out ongoing operational load, but a few structural signals are visible from the architecture differences above.

Platforms with proprietary scanners built in (Legit Security, Cycode, and to a lesser extent Apiiro and OX) reduce the number of separate scanner licenses you manage, but they also mean you are now trusting that vendor's detection engine for at least part of your coverage, not just its correlation layer. If you already have SAST and SCA tools you are happy with and only want a correlation layer on top, ask each vendor directly how much of their built-in scanning you can disable versus how much is mandatory for the risk graph to function.

Agentless, API-based integration (Apiiro's stated approach for SCM and runtime) generally means lower ongoing maintenance than integrations that require agents deployed into build runners or manual asset tagging, because there are fewer moving parts that can drift out of sync with your actual infrastructure.

Any platform built around a pipeline bill of materials (Cycode and OX Security both use this term) requires your CI/CD environment to expose enough metadata for that BOM to stay accurate. Highly customized or self-hosted CI/CD setups may need more onboarding effort to get full BOM fidelity than a team running entirely on GitHub Actions or GitLab CI/CD out of the box.

For any of the four, budget real engineering time, not just security team time, for the first integration pass. Correlating cloud runtime context specifically tends to require cloud account read access and IAM configuration that platform teams, not AppSec teams, usually own.

None of the four vendors publishes list pricing or tiered plans on their public sites as of this writing. All four require a sales conversation and a scoped quote, typically based on factors like number of repositories, developer seats, or applications under management, though the exact metering model varies by vendor and is worth confirming directly rather than assuming.

We are not going to fabricate per-seat or per-repo figures here because no public source confirms them for any of these four platforms. If a search result, blog post, or comparison site quotes you a specific dollar amount for Legit Security, Cycode, Apiiro, or OX Security, treat it as unverified until your own sales conversation confirms it. What you can compare without a quote is scope: ask each vendor explicitly whether their quote includes their own built-in scanners (SAST, SCA, secrets, IaC) or only the correlation and graph layer on top of scanners you already own, since that materially changes what you are actually paying to replace versus supplement.

Summarizing the architecture and integration details above into practical strengths and limits for each vendor, based strictly on what each vendor and the comparison sources cited in this guide document publicly.

None of these four platforms is a universal winner. The right choice depends on what you are trying to fix and what you already run.

If your AppSec toolchain already includes multiple third-party SAST, SCA, and container scanners that you are satisfied with and your core pain is duplicate alert triage and missing business context, Legit Security's broad third-party ingestion and compliance mapping is worth prioritizing in your evaluation, particularly if you also need audit-ready evidence for frameworks like SSDF or ISO 27001.

If your organization's biggest unresolved risk is in the CI/CD pipeline itself (exposed credentials in build logs, unauthorized pipeline changes, unclear ownership of build infrastructure) rather than in application code volume, Cycode's change-impact-analysis and pipeline BOM approach is a more targeted match than a broader SDLC inventory platform.

If you run a large, security-mature engineering organization with many repositories and want the deepest code-level correlation, including reconciling findings across SAST, DAST, SCA, container, IaC, secrets, and CSPM tools without relying on exact CVE-ID matches, Apiiro's Deep Code Analysis and agentless integration model is worth a closer look, especially if your teams are already adopting AI coding assistants that Apiiro's CLI is built to work alongside.

If your team has already standardized on GitHub Copilot, Cursor, or another AI coding assistant and wants to catch insecure code before it is committed rather than after a scan runs, OX Security's prevention-first VibeSec positioning is the outlier worth piloting, but validate the false-positive rate carefully since in-IDE blocking tools that annoy developers get disabled quickly regardless of their detection accuracy.

If you are still running mostly point scanners without any correlation layer at all and are deciding between upgrading your SAST tool versus adding an ASPM layer on top of what you have, read our Checkmarx vs Veracode SAST comparison first. A better point scanner and an ASPM correlation layer solve different problems, and teams sometimes need to fix scanner accuracy before a correlation layer has good enough underlying data to be useful.

ASPM platforms assume you already have multiple scanners producing enough volume that correlation and prioritization are the bottleneck, not scanner coverage itself. If your organization runs a single SAST tool and no SCA, DAST, or container scanning at all, an ASPM platform will have very little to correlate and you are better off closing basic scanner coverage gaps first.

Similarly, if your engineering organization is under roughly 50 developers with a handful of repositories, the enterprise sales cycle and onboarding effort these four platforms require may cost more in engineering time than the alert-fatigue problem they solve. A smaller team can often get most of the practical benefit by consolidating scanner output into a shared ticketing queue with clear deduplication rules, without an additional platform and its associated cost and integration overhead.

Finally, if your primary unmet need is compliance evidence generation rather than developer-facing risk prioritization, confirm during the sales process that the platform's compliance mapping (where offered) actually produces auditor-ready artifacts for your specific framework, rather than assuming general ASPM coverage implies compliance coverage.

Before signing an enterprise contract with any of these four vendors, run a scoped proof of concept against your actual repositories and pipelines, not a vendor demo environment. Use this checklist to keep the evaluation consistent across vendors.