Securie vs GitHub Copilot Autofix
Last fact-checked against competitor public docs: 2026-05-25
Copilot Autofix (powered by CodeQL) suggests fixes for findings the GitHub Advanced Security pipeline produced. Securie is the AI codebase maintenance engineer — opens tested repair PRs for approval, with test-verified repair and DSSE-signed attestation. Different layer, different blast radius.
Copilot Autofix and Securie sit at different layers of the codebase assurance stack. Copilot Autofix is a suggestion layer that takes a CodeQL finding and proposes a patch the developer applies. Securie is the AI codebase maintenance engineer — detect risk, repair, verify, and attest evidence end-to-end. Both have a legitimate role, and which one you pick depends on whether you want to keep the human triage layer in the loop (Copilot Autofix) or replace it (Securie).
Copilot Autofix is a suggestion layer on top of CodeQL findings — the human still triages, applies, and tests. Securie is end-to-end: detect risk, draft the repair, verify against the codebase and tests, and attest the evidence. For teams already paying for GitHub Enterprise + GHAS, Copilot Autofix is a workflow improvement; Securie concentrates the maintenance and assurance triage layer into tested repair PRs.
Feature comparison
| Securie | GitHub Copilot Autofix | |
|---|---|---|
| Finding source | Frontier-LLM finder (Opus 4.7) + 9 supplementary specialists across 14 languages — on-demand sandbox replay reserved for Business+ disputed findings | CodeQL queries (GitHub Advanced Security) |
| Finding verification | Frontier-LLM finder + fix-verification against your test suite — PASS-only ships as Suggested Change | Pattern-match via CodeQL; no runtime proof per finding |
| Fix-PR shape | Tested repair PR with regression test, verification output, and DSSE-signed attestation | AI-suggested patch inline on the alert — human applies + tests |
| Weakness coverage | 8 axes: security, correctness, reliability, intent-drift, tests, hallucinations, inert-surfaces, style/consistency (ADR-073) | Security only (CodeQL detection categories) |
| Attestation chain | DSSE Ed25519 + in-toto + Sigstore rekor + OpenTimestamps anchor — auditor-verifiable | GitHub audit log; no per-fix attestation envelope |
| Deploy-time gate | Vercel / Netlify / Cloudflare — fan-out via deploy-gate-core | GitHub branch protection (no hosting-layer block) |
| Runtime evidence | runtime signal validator on customer-app containers (Scale+) + daily log digest (Business) | None — Copilot is dev-time only |
| Continuous offensive verification | Continuous frontier-LLM finder chains primitives across endpoints (ADR-064) | None — single-finding suggestions only |
| On-demand sandbox replay (Business+) | On-demand signed posture artifact (Business+ self-serve) | None |
| Trust Page | Auto-generated /trust/[slug] with PRR badge + validation matrix | None |
| Sovereign deployment | On-prem + air-gapped + customer-VPC (Enterprise) | GitHub Enterprise Server (GHES) only |
| Languages | 14 LSP-IR-backed: TypeScript, JavaScript, Python, Go, Rust, Java, Kotlin, Scala, Swift, C#, Ruby, PHP, C/C++, Solidity, Dart | CodeQL supported set: C/C++, C#, Go, Java, JavaScript/TypeScript, Python, Ruby, Swift |
| Cost | Free → Starter $39 → Pro $99 → Team $799 → Business $2,999+ → Scale from $90K/year → Enterprise from $180K/year | GitHub Enterprise + GHAS Advanced Security — typically $20-50 per active committer per month bundled |
Where the difference shows up in practice
generated or rushed Server Action with permissive Zod schema (Next.js)
GitHub Copilot Autofix: CodeQL may not flag — the static pattern (Zod validation + Server Action) looks correct. Copilot Autofix doesn't see a finding to fix.
Securie: Authorization specialist + sandbox replay: synthesize an input that the permissive Zod accepts but the downstream handler shouldn't trust. Replay confirms exploit. Fix PR tightens the schema + adds regression test that re-checks the original exploit input fails after the patch.
Supabase RLS policy with auth.uid() in USING but missing WITH CHECK on INSERT
GitHub Copilot Autofix: CodeQL has community queries for SQL injection but limited Supabase-RLS semantic coverage. Copilot Autofix's suggestion quality on Supabase-specific bugs varies — the LLM may write a plausible policy that doesn't match the customer's actual auth model.
Securie: Supabase RLS specialist runs cross-tenant test in sandbox: signs in as user-A in tenant-1, INSERTs row, signs in as user-B in tenant-2, confirms row is visible (cross-tenant leak). Fix PR adds WITH CHECK clause + regression test that re-runs the cross-tenant assertion.
Unhandled fetch timeout on outbound API call
GitHub Copilot Autofix: Not in scope — CodeQL focuses on security; reliability bugs (axis #3) are out of the Copilot Autofix surface.
Securie: Reliability specialist + chaos-test sandbox: inject upstream latency, confirm the handler hangs. Fix PR wraps the fetch with AbortController + timeout + regression test that asserts the handler returns within 5s under a 30s upstream delay.
AI-fabricated import of a non-existent package
GitHub Copilot Autofix: Out of scope — CodeQL detects vulnerabilities in real packages; it doesn't resolve every import against the installed package tree at PR time.
Securie: Hallucinations specialist: every import is resolved against the actual installed package tree (LSP-IR). Imports from packages that don't exist fail the gate and the slopsquat-watcher pipeline cross-checks the registry for typosquat patterns matching the fabricated name.
The deeper tradeoff
The architectural pivot between Copilot Autofix and Securie is autonomy depth.
Copilot Autofix is bounded by the CodeQL finding it receives. CodeQL is a pattern-matching engine over a code-property graph; it produces high-quality static findings, and Copilot Autofix uses the LLM to write a patch suggestion inline on the alert. The developer sees the alert, reads the suggested patch, decides whether to apply it, runs the test suite themselves, and merges. The human is the verification primitive.
Securie's sandbox is the verification primitive. Every finding ships only after a Firecracker microVM has replayed a working exploit against a shadow copy of the customer's app. Every fix ships only after the same sandbox has re-run the exploit against the patched code and confirmed it now fails. Every shipped PR carries a regression test in-tree that locks the fix against future refactor. The human approves or rejects the PR; they do not have to be the verification primitive.
The two layers compose. A team can run CodeQL/Copilot Autofix on PR for inline suggestions AND run Securie for tested repair PRs. The CodeQL/Copilot output goes to the developer's inbox; Securie's output goes to the PR-review queue. Where they overlap is exactly where Securie's sandbox-verification gate fires — findings that CodeQL surfaces but Securie's sandbox can't replay get dropped (they were false positives); findings Securie surfaces that CodeQL missed expose CodeQL's pattern blind spots.
The attestation chain is a step-function difference. Copilot Autofix produces a GitHub audit log entry. Securie produces a DSSE-signed in-toto envelope per fix, anchored in Sigstore rekor + OpenTimestamps. For enterprise prospects asking 'how do you know this fix actually fixed the bug?' the customer can hand them the cryptographic envelope; for compliance-adjacent buyers asking for evidence, the envelope is auditor-verifiable. Copilot Autofix's audit log is GitHub-verifiable, which is a different trust property.
The weakness-axis coverage is the second step-function difference. Copilot Autofix covers what CodeQL detects, which is security only. Securie covers 8 axes including correctness (logic bugs), reliability (timeouts / retries / leaks), intent-drift (code-spec divergence), tests (auto-generated regression + property tests), hallucinations (AI-fabricated APIs / slopsquats), inert-surfaces (ADR-044 wired-but-no-op detection), and style/consistency (per-tenant Ring 0 pattern learning). For a team using AI coding tools at high velocity, the 7 non-security axes are where the bug volume is — security is the most-policed surface and therefore not the dominant source of new bugs anymore.
Pricing
$39-$99 self-serve for solo founders; $799-$2,999 for the engineering org; Scale starts from $90K/year for the Series-B+ deployment. Each tier includes all 26 specialists across all 8 maintenance axes — pricing splits on PR volume + committer expansion + retention + deployment topology, never on which axis you get.
Bundled with GitHub Advanced Security. Per-committer pricing inside GitHub Enterprise. Suggestion-quality varies by language + finding type. The autofix layer is free once GHAS is paid for; the cost is therefore the underlying GHAS subscription.
Migration playbook
Step 1: Audit your current GHAS + Copilot Autofix usage
What: Run `gh code-scanning alert list` for the past 90 days. Count: (a) total alerts surfaced, (b) alerts marked 'fixed' via Copilot Autofix, (c) alerts marked 'dismissed-false-positive', (d) alerts still open.
Why: Establishes the baseline. Securie's sandbox-verification gate eliminates the false-positive cohort by construction, and the autonomous fix-PR shape closes the 'still open' cohort without human triage time. Quantifying both inputs sets up the labor-replacement math.
Gotchas: Some 'dismissed-false-positive' alerts are real bugs the team didn't have time to triage — don't assume the dismiss bucket is genuinely false-positive. Securie's sandbox is the truth-teller; re-scanning with Securie's maintenance loop typically promotes 10-30% of the dismiss bucket back to confirmed-exploitable.
Step 2: Install Securie on the same repo as a parallel reviewer
What: GitHub App install on the same repo. Securie will start reviewing PRs in parallel with CodeQL + Copilot Autofix. Run both for 30 days.
Why: Lets the team observe Securie's verdicts side-by-side with the existing pipeline. Disagreements (Securie flags what CodeQL missed; CodeQL flags what Securie dropped) are the most informative signal.
Gotchas: Two PR comment bots on the same PR can be noisy — turn off Copilot Autofix's inline suggestions on PRs where Securie has surfaced findings, or coexist by funneling Copilot Autofix's CodeQL alerts to the Security tab and Securie's verdicts to the PR review thread.
Step 3: Compare attestation chains side-by-side
What: Pick 5 representative recent fix-PRs from each pipeline. Verify Securie's DSSE envelope using the Securie public key. Pull GitHub's audit log entry for the Copilot Autofix-applied PRs. Compare the two evidentiary artifacts.
Why: For enterprise prospects asking 'show me how you know this fix is real' the DSSE envelope answers cryptographically. For compliance-adjacent buyers, the auditor-verifiable envelope shortens the maintenance and assurance cycle.
Gotchas: The auditor probably doesn't know what DSSE is — provide a 1-page explanation that maps in-toto attestations to their existing SOC 2 / ISO 27001 / pen-test-report mental model. Securie ships an example explanation in the auditor-onboarding doc.
Step 4: Decide on coexistence vs. cutover
What: After 60 days of parallel running, decide: (a) keep Copilot Autofix as the inline-suggestion layer + Securie as the autonomous fix-PR layer (coexistence), or (b) downgrade from GHAS Advanced Security (Copilot Autofix included) to GHAS base (Dependabot + secret-scanning only) and let Securie cover the SAST + tested repair surface entirely (cutover).
Why: Coexistence costs GHAS Advanced Security subscription + Securie subscription; cutover saves the GHAS Advanced Security delta. The decision depends on whether the team has CodeQL custom queries in flight as audit controls — if yes, keep GHAS; if no, the SAST surface fully moves to Securie.
Gotchas: If your SOC 2 control description mentions 'GHAS CodeQL pattern detection' as a security control, update the control description before downgrading. Auditors catch stale control descriptions and it creates friction at the next audit. Securie's DSSE attestation chain is the substitute control; the description must reference it instead.
When to pick GitHub Copilot Autofix
You already pay for GitHub Enterprise + GHAS and want improved triage suggestions inline on existing CodeQL findings. The autofix is essentially free at that point and improves developer ergonomics. You don't need autonomous PR-opening, sandbox verification, or signed attestation chains.
When to pick Securie
You want to concentrate senior evidence work — not augment it. You need findings that come with test-verified repair (not pattern-match flags), tested repair PRs with regression tests (not suggestions for a human to apply), DSSE-signed attestation chains (for auditors / insurers / enterprise prospects), and coverage across 8 maintenance axes including correctness, reliability, intent-drift, tests, hallucinations, inert-surfaces, and style — not just security. Or you need sovereign / air-gapped / customer-VPC deployment, which GitHub's hosted offering structurally cannot provide.
Bottom line
Pick Copilot Autofix if you're already on GitHub Advanced Security and want better triage suggestions inline. Pick Securie if you want the maintenance and assurance function replaced — test-verified repairs only, tested repair PRs with regression tests, signed attestations for auditors and insurers, and coverage across 8 maintenance axes (not just security).
FAQ
Does Securie replace GitHub Advanced Security entirely?
It can — Securie covers the SAST + tested repair surface end-to-end with test-verified repair + DSSE attestations + autonomous PR-opening across 8 maintenance axes. Dependabot + secret-scanning remain useful as GHAS base features, but the Advanced Security tier (which Copilot Autofix sits inside) is the lever that's most directly replaceable.
Can I run Securie and Copilot Autofix together?
Yes — they sit at different layers. Copilot Autofix suggests inline patches; Securie drafts tested repair PRs with regression tests + signed attestations. The disagreement signal (Securie flags ≠ CodeQL flags) is informative.
Does Copilot Autofix produce signed attestations?
No. Copilot Autofix updates the GitHub audit log when an applied fix lands. Securie's DSSE-signed in-toto envelope per fix is cryptographically auditor-verifiable — a step-function difference for compliance-adjacent buyers and insurer-evidence flows.
Which is better at non-security maintenance axes?
Copilot Autofix covers security only (the CodeQL surface). Securie covers all 8 axes per ADR-073: security, correctness, reliability, intent-drift, tests, hallucinations, inert-surfaces, style/consistency. For teams using AI coding tools at high velocity, the 7 non-security axes are where the bug volume is.
Does Securie work on GitHub Enterprise Server (sovereign deployment)?
Yes. Securie's Enterprise tier ships sovereign deployment (on-prem / air-gapped / customer-VPC) where the customer owns the host and holds the attestation signing keys. The GitHub App runs against GHES; the verification sandbox and the attestation chain stay inside the customer's infrastructure.