--- title: "Sekura vs traditional vulnerability scanners — Sekura" url: https://sekura.ai/vs/scanners/ description: "How Sekura differs from SAST/SCA/DAST scanners: scanners output ranked potential issues; Sekura reports only what it has actually exploited. Side-by-side comparison across output, false positives, scope, cadence, and triage burden." updated: 2026-10-09 generator: sekura build, scripts/build-markdown.mjs --- Comparison # Sekura vs traditional vulnerability scanners How Sekura differs from SAST/SCA/DAST scanners: scanners output ranked potential issues; Sekura reports only what it has actually exploited. Side-by-side comparison across output, false positives, scope, cadence, and triage burden. [All guides →](https://sekura.ai/learn/) ![Sekura — owl-in-shield mark](https://sekura.ai/branding/sekura-owl-v3.png) ## TL;DR | | Traditional scanner | Sekura | | ------------------------ | ---------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------- | | **Output** | List of _potential_ issues, ranked by severity score | List of _exploited_ issues, each with a proof-of-exploit | | **False-positive model** | Inherent — scanners flag potential issues that may or may not be exploitable | Eliminated by design — Sekura only reports findings it has actually exploited | | **Scope** | Single surface per tool (SAST, or SCA, or DAST) | SAST + DAST + exploit chain + LLM security + post-quantum crypto in one scan | | **Cadence** | On-demand or scheduled scans | Continuous — runs every push, every PR, optionally every hour | | **Triage burden** | Engineering teams chase ranked alerts, manually validate each | Each finding ships with a reproducible payload; no validation step | | **Deployment** | SaaS, usually on vendor infrastructure | Cloud distribution: runs in your own GitHub Actions runner. Enterprise: runs behind your firewall | | **Pricing model** | Per-seat or per-application annual contracts | Public: free first scan, $199 Scan Once, $20–$300/mo plans, enterprise contact-us | ## What traditional vulnerability scanners do A traditional vulnerability scanner — SAST (Snyk, Veracode, Checkmarx, Semgrep), SCA (Dependabot, Snyk Open Source), or DAST (Burp Suite, Invicti, Tenable) — analyses a target and emits a ranked list of vulnerabilities. The ranking is typically based on a CVSS severity score: a hypothetical worst-case impact, computed without reference to your environment. The scanner does not attempt to verify the vulnerability is exploitable in your specific deployment. It cannot tell whether a tainted SQL query is reachable from an unauthenticated route, whether a path-traversal flaw is mitigated by a downstream WAF rule, or whether a hardcoded secret has been rotated. These determinations require human triage — and on a typical mid-size codebase, scanners emit thousands of findings that the security team must work through. The dominant cost of running a scanner is not the licence; it is the triage time. ## What Sekura does differently Sekura runs a 7-phase multi-agent pipeline against the target: 1. **White-box SAST** — seven SAST engines plus an LLM reviewer read the source and emit ranked _hypotheses_. 2. **Recon** — agents enumerate the running attack surface (subdomains, endpoints, headers, exposed services). 3. **Dynamic probing** — agents send crafted requests, observe responses, and confirm or refute each hypothesis. 4. **Exploit synthesis** — agents construct working exploits for confirmed hypotheses (e.g. a payload that actually reads `/etc/passwd`, not just a CVSS score). 5. **Exploit-chain analysis** — agents stitch single-issue exploits into multi-step attack chains, finding paths a scanner cannot. 6. **Post-quantum cryptography review** — agents audit crypto usage and flag quantum-vulnerable algorithms. 7. **Reporting** — each confirmed finding is exported with the exact request, payload, response, and remediation. Sekura reports a finding only if it can produce a deterministic proof-of-exploit. If the agents cannot exploit a hypothesis in the target's actual environment, the hypothesis is dropped. The reported list is short, ranked by demonstrated impact, and contains zero false positives by construction. ## Where scanners still win - **Coverage breadth at zero exploit cost.** A scanner runs cheaply over thousands of repositories and surfaces everything _potentially_ wrong. That breadth is useful for inventory, compliance reporting, and dependency hygiene where exploitation is not required. - **Speed on extremely simple changes.** A linter-style scanner emits results in seconds. Sekura's pipeline takes minutes per scan because exploit synthesis is dynamic. - **Familiarity in existing workflows.** SARIF / GitHub Security tab integration is standard; security teams already know how to work scanner output. Sekura is not trying to replace dependency scanners — its findings _also_ flow into SARIF and the GitHub Security tab. It replaces the manual-triage burden that scanners impose. ## When to use which - **You need a CVE inventory.** Run an SCA scanner (Dependabot, Snyk Open Source). Sekura uses SCA findings as inputs to its exploit synthesis but does not duplicate the inventory. - **You need to know what is actually exploitable in your production environment.** Run Sekura. - **You need both.** Run both. Sekura's pipeline ingests scanner output as Phase-1 hypotheses, then proves or refutes each one in Phase 3. [All guides](https://sekura.ai/learn/)