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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.

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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.