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 | Per LLM-token (Free / Pro $49/user-month / Enterprise) |
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:
- White-box SAST — seven SAST engines plus an LLM reviewer read the source and emit ranked hypotheses.
- Recon — agents enumerate the running attack surface (subdomains, endpoints, headers, exposed services).
- Dynamic probing — agents send crafted requests, observe responses, and confirm or refute each hypothesis.
- Exploit synthesis — agents construct working exploits for confirmed hypotheses (e.g. a payload that actually reads
/etc/passwd, not just a CVSS score). - Exploit-chain analysis — agents stitch single-issue exploits into multi-step attack chains, finding paths a scanner cannot.
- Post-quantum cryptography review — agents audit crypto usage and flag quantum-vulnerable algorithms.
- 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.