One platform from code to SOC.
Cantina finds the exploit in your code, pushes the fix to your engineers, and catches the adversary who tries to use it in production, all in one product. Everyone else sells you half the stack.
Request a demoModern security teams run dozens of tools across AppSec and SecOps. Findings slip between products, the code-to-production handoff becomes someone's second job, and the pain compounds as you scale. Cantina collapses the sprawl into one platform: find it in the code, fix it in the PR, catch it when it tries to happen again.
| Capability | Cantina | AI code scanners | Legacy SOC stack | AI SOC analyst tools |
|---|---|---|---|---|
| Unified AppSec + SecOps in one platform | Yes. Code to SOC in one product | AppSec only | SecOps only | SecOps only |
| Proof of exploitability | Verifiable evidence of real exploitation | Rare. Potential issues only | Not in scope | Not in scope |
| Chained attack paths | End-to-end attack narratives, not isolated findings | No. Isolated issues | Not in scope | Not in scope |
| Business-logic coverage | Yes. Authorization and logic flaws, not pattern-matched bugs | Limited. Pattern-based | Not in scope | Not in scope |
| Low false-positive rate | 83%+ validity, adapts via threat-model quiz and learns from feedback | High FP rate. Analyst time sink | Heavy alert fatigue | Yes. Core pitch |
| Multi-layer coverage in one engagement | Yes. Single scope | Code only | Not in scope | Not in scope |
| One-click retest of fixes | Built in. No new SOW | Re-scan required; no proof of fix | Not in scope | Not in scope |
| Severity tied to real business impact | Yes. Scored on business / protocol impact, not CVSS | Generic CVSS | Generic severity | Generic severity |
| Adversary / threat modeling | Included top-down with every engagement | No. Bottom-up only | Not in scope | Not in scope |
| Autonomous SOC triage | Yes. End-to-end, no analyst needed to start | Not in scope | Analyst-driven or pre-built playbooks | Yes. Their core lane |
| Autonomous investigation | Yes. Pivots, enriches, concludes | Not in scope | Manual, analyst-driven | Yes |
| Autonomous response | Yes. With guardrails | Not in scope | Scripted playbooks (human-authored) | Rare. Most hand off to SOAR |
| Native multi-source ingestion | Yes. No separate pipeline product | Not in scope | Yes, but heavy config | Typically read-from-SIEM only |
| Natural-language / agentic interface | Fully agentic chat across code and SOC | Limited copilots | Proprietary query languages + some AI copilots | Partial. Mostly back-end AI |
| Built-in case management | Full case lifecycle in-platform | Not in scope | Needs external ticketing systems | Typically hand off to SOAR / ticketing |
| Identity-layer detection | Yes | Not in scope | Depends on log sources + rules you write | Only what the SIEM feeds them |
| Cloud prevention + runtime detection unified | CSPM + runtime in one | Not in scope | Detection only; prevention is a separate product | Detection-triage only |
| Rapid deployment | Days. Ingesting and finding | Weeks | Months. Notoriously long cycles | Fast if SIEM is already in place |
| Unified workflow | Findings flow from Apex into Clarion, then into engineer and security workflows | CI/CD hooks only | Alerts to SIEM / ITSM | Alerts to SOAR |
Comparisons are against product categories, not specific vendors. For vendor-level detail, talk to our team.