Securie vs Mobb
Mobb is the auto-fix specialist — it ingests SAST findings (from your existing scanner) and produces a fix PR. Securie is a full PR-to-attestation platform that also produces fix PRs but with a structurally different commitment: every fix is regression-tested in a sandbox against the reproduced exploit. This page is the honest comparison for teams choosing between auto-fix tools.
Teams comparing Securie and Mobb are usually evaluating one specific question: how much can we automate the fix step without compromising correctness? Mobb is purpose-built for that question — it sits on top of whatever SAST scanner you already have and produces fix PRs from the findings. The integration is broad and the patches are high-quality. The honest tradeoff is that the fix is pattern-derived from the finding shape; there is no exploit to regression-test the fix against.
Securie answers the same question with a different architectural commitment. The fix is generated, then regression-tested in the sandbox against the reproduced exploit. A fix that does not cause the exploit to fail is rejected and re-generated. The commitment is stronger — auditor-verifiable, attestation-signed — but it requires Securie to produce the finding in the first place, so the integration with your existing SAST stack is different.
The procurement question is whether you want auto-fix as a layer on top of your existing scanner (Mobb) or as one stage of a sandbox-verified pipeline (Securie). Both answers are defensible, and the right one depends on what you have today and what your stack looks like.
Mobb is a fix-only specialist that sits on top of an existing SAST scanner — its differentiator is fix quality + multi-scanner integration. Securie is a full platform whose fix output is one stage of a sandbox-verified pipeline — every fix must cause the reproduced exploit to fail or it is rejected. Pick Mobb if you have a SAST scanner you trust and want to add auto-fix on top of it. Pick Securie if you want one tool from finding-detection through sandbox-verification through fix-regression-testing through attestation.
Feature comparison
| Securie | Mobb | |
|---|---|---|
| Auto-fix PR generation | Yes — sandbox-regression-tested against the reproduced exploit | Yes — Mobb's flagship capability; multi-scanner input integration |
| Fix regression-test commitment | Patch must cause the reproduced exploit to fail in the sandbox or it is rejected | Pattern-driven fix; no exploit-regression test (no exploit to test against) |
| Finding source | Securie's own specialists (Day-1 Supabase RLS / secrets / broken auth + ~20 code-complete) | Ingests findings from existing SAST tools (Snyk, Checkmarx, Semgrep, GitHub Advanced Security, more) |
| Multi-scanner integration | Standalone — Securie produces its own findings end-to-end | Strong — Mobb's primary value is integrating with whatever SAST your team already has |
| Sandbox verification | Yes — Firecracker microVM with replayer-per-class + ProofArtifact persistence | No — Mobb does not run a sandbox; fixes are pattern-derived |
| Audit attestation | Signed in-toto + DSSE + Sigstore-rekor (Ed25519, KMS-backed in production) | Fix PR + audit log; not cryptographically attested |
| Language coverage | TypeScript + JavaScript at launch; Python + Go on Series-A roadmap | Java, JavaScript/TypeScript, Python, C#, more — broader by design (downstream of multi-scanner ingestion) // TODO: verify current language matrix |
| Supabase RLS specialist | Day-1 production-validated specialist with full CREATE POLICY semantics | Inherits whatever the upstream SAST scanner detects; no Supabase-specific specialist |
| AI-feature coverage | llm-safety + multimodal-guard + rag-guard + mcp-guard + prompt-inj CI gate | Inherits whatever upstream scanner detects; not Mobb's focus |
| Pricing | Free / $12 / $49 / $299 / Enterprise | Per-developer subscription; Enterprise tier // TODO: verify mobb.ai pricing |
Where the difference shows up in practice
A SQL injection in a parameterized-looking but actually-string-concatenated query
Mobb: Mobb ingests the finding from the upstream SAST. The finding pattern is canonical SQL injection at line N with input X. Mobb generates the fix: parametrize the query. The fix is typically correct because the bug pattern is canonical. PR ships in minutes.
Securie: Securie's specialist detects the SQL-injection candidate. The sandbox seeds a Postgres instance and replays the attack — confirms exploit succeeds. The fix is generated (parametrize the query) and the sandbox re-runs the same attack — confirms exploit now fails. Patch ships as a PR with the exploit-pre + exploit-post evidence. For canonical bugs, both tools produce equivalent patches; Securie's adds the sandbox-verified evidence.
A Supabase RLS policy with USING but missing WITH CHECK on INSERT
Mobb: If the upstream SAST detects the missing WITH CHECK (most do not have Supabase-specific semantics), Mobb attempts a pattern-derived fix. Without Supabase-specific knowledge, the fix may not match the framework's expected shape — it may add WITH CHECK but with the wrong predicate, or it may not fire at all because the upstream SAST did not produce the finding.
Securie: Securie's Supabase RLS specialist detects the bug with full Supabase semantics. The sandbox confirms a cross-user INSERT succeeds. The fix is generated with the canonical Supabase pattern (`WITH CHECK (auth.uid() = owner_id)`) and the sandbox re-runs — confirms the cross-user INSERT now fails. The framework-specific fix is the sandbox-verified one.
A logic vulnerability in a Server Action — auth check exists but does not protect the actual mutation
Mobb: The bug is a logic vulnerability — a getUser() call exists, but its return is never compared against the FormData user_id used in the mutation. The pattern engine in the upstream SAST may flag the Server Action as 'possible authz issue,' but the canonical fix pattern does not exist (the right fix is a comparison that depends on the specific Server Action's intent). Mobb's pattern-derived fix may add a generic authz check that does not match the function's actual access model.
Securie: Securie's BOLA/BFLA specialist + intent-graph reasoning identifies that getUser().id is not compared against the FormData user_id. The sandbox seeds two users and confirms the cross-user mutation succeeds. The fix is generated with the specific comparison required (`if (getUser().id !== formData.userId) return forbidden()`) and the sandbox re-runs — confirms the cross-user mutation now fails. The intent-graph context produces a logic-fix that pattern-matching cannot.
A leaked OpenAI API key in source
Mobb: Mobb generates a fix that moves the key to an environment variable + adds the env-var read at the call site. The pattern is canonical and the fix is correct. Mobb does not validate whether the key is currently active or rotate it.
Securie: Securie's secret_scanner specialist detects the key + live-validates against OpenAI. The fix moves the key to an environment variable AND mints a new key via the OpenAI management API AND revokes the old key. The PR ships with the rotated key already in place; the developer just merges. Mobb does not have the rotation step (it is not in scope).
The deeper tradeoff
The architectural pivot between Mobb and Securie is fix-derivation strategy. Mobb derives the fix from the finding pattern + surrounding code context — a sophisticated patch generator that takes 'this is a SQL injection at this line with this input' and produces 'parametrize the query like this.' The patch quality is typically high; the commitment is that the pattern of the bug matches the pattern of the patch. For well-specified bug classes (canonical SQL injection, canonical XSS, canonical command injection), this works well.
For framework-specific or logic vulnerabilities, the pattern-derivation approach has structural limits. A Server Action with a Zod schema too permissive to catch the actual attack does not have a canonical 'fix' pattern — the right fix depends on what the surrounding code expects. A Supabase RLS policy missing WITH CHECK on INSERT has a fix shape, but pattern-matching the bug to its fix requires Supabase-specific semantic knowledge the pattern engine does not always have. A Next.js middleware matcher that misses a path prefix has a fix shape that is correct for the specific app's routing, not derivable from the finding pattern alone.
Securie's sandbox-regression-test commitment cuts through this by changing the question. Instead of 'does the fix pattern-match the bug,' the question becomes 'does running the fix make the exploit fail.' The sandbox replays the exploit against the patched code; if the exploit succeeds, the patch is rejected and the patch loop iterates. The output is a fix that is verified to break the specific exploit that was reproduced.
The consequences cascade. Audit trails are stronger because each fix carries the exploit-success-pre-patch + exploit-failure-post-patch evidence. Compliance evidence is stronger because the verification is auditor-replicable. The cost is integration shape — Securie produces its own findings end-to-end, so layering on top of an existing SAST is a different mental model than Mobb's.
The market segments differently along this seam. Teams with mature AppSec and an existing SAST they trust pick Mobb to add auto-fix on top. Teams without an existing SAST or who want one tool covering the full pipeline pick Securie. Teams with regulated audit requirements (SOC 2, FedRAMP-pathway) typically prefer the cryptographic attestation chain Securie produces over Mobb's audit log + PR shape, but that is a downstream consequence of the fix-derivation choice, not the central decision.
Pricing
Free ($0) · Indie ($12) · Solo Founder ($49) · Startup ($299). Capped-envelope monthly.
Per-developer subscription; Enterprise annual; free trial. // TODO: verify mobb.ai/pricing.
Migration playbook
Step 1: Identify whether your bottleneck is fix-generation or finding-detection
What: Inventory: for the last 90 days, where did your security workflow stall — was it 'we have findings but no time to fix them' (fix-generation bottleneck) or 'we are not seeing the bugs that actually matter' (finding-detection bottleneck)?
Why: Mobb solves the first bottleneck; Securie solves both. The decision starts with which one you actually have.
Gotchas: Common conflation: 'we have noise' is a triage bottleneck, not a fix-generation one. Mobb does not reduce noise (it inherits whatever the upstream scanner produces); Securie does reduce noise (sandbox verification drops unreproducible findings).
Step 2: If fix-generation bottleneck and you trust your SAST: pick Mobb
What: Install Mobb on top of your existing SAST. Configure the integration. Run for two weeks; measure fix-PR-shipped-per-week and PR-merge-rate.
Why: Mobb is purpose-built for this. The integration with your existing scanner is its differentiator.
Gotchas: Watch fix-PR merge rate — patches that the developer rejects are signal that the auto-fix quality is not yet matched to your codebase's idioms. Tune Mobb's settings or manually classify rejected fixes.
Step 3: If finding-detection bottleneck OR you ship AI-built apps on Next.js + Supabase: pick Securie
What: Install Securie's GitHub App. Run for two weeks. Measure: real bugs caught (especially Supabase RLS, leaked secrets, broken auth, AI-feature bugs), auto-fix PR merge rate, sandbox-verified-finding-count.
Why: Securie produces its own findings end-to-end with sandbox verification, including AI-app-specific specialists your existing SAST may not have. The fix layer is regression-tested.
Gotchas: If you already have Mobb on your existing SAST, the Securie evaluation should treat Mobb's PRs separately — running both tools' auto-fix on the same finding can produce two PRs touching the same code.
Step 4: If both bottlenecks: run both tools in parallel for two weeks, then decide
What: Run Securie + Mobb together for two weeks. Measure: real bugs caught (Securie's specialists vs Mobb's upstream-SAST findings), fix-PR quality, fix-merge rate, audit-evidence shape per tool.
Why: The combination is unusual but not unreasonable — Mobb augments the existing SAST, Securie covers the AI-app surface that SAST does not. The parallel run shows the overlap and the gap.
Gotchas: Two auto-fix PRs on the same finding (one from Mobb, one from Securie) is the failure mode. Configure precedence — one tool for canonical bugs, the other for framework-specific.
Step 5: Decide based on real-bug-precision + audit-shape requirements
What: After two weeks, compare: real-bug-precision per tool, fix-quality per tool, audit-shape per tool. If audit requires cryptographic attestation per scan (SOC 2 Type II, FedRAMP-pathway), Securie's chain is the structurally relevant evidence. If audit requires fix-PR records, both tools produce them.
Why: The audit-shape requirement is often the deciding factor for regulated teams. Get clarity on what your auditor wants to see before committing.
Gotchas: Auditors increasingly expect cryptographic evidence for high-trust controls. Mobb's audit log is sufficient for many SOC 2 controls but may not satisfy FedRAMP-pathway high-trust requirements; Securie's attestation chain is built for that case.
When to pick Mobb
You have a SAST scanner you trust (Snyk, Semgrep, Checkmarx, GitHub Advanced Security) and you want to add auto-fix on top of it without changing the scanner. Mobb's value proposition is exactly that integration — it does not replace your SAST, it augments it.
When to pick Securie
You want one tool that produces the finding, proves it with a sandbox exploit, generates the fix, regression-tests the fix against the same exploit, and emits a signed attestation — end-to-end without separate SAST + fix-tool integration. Or: you ship AI-built apps where AI-app-specific specialists matter and your existing SAST does not cover them.
Bottom line
Mobb wins on integration breadth — it ingests findings from many SAST scanners (Snyk, Checkmarx, GitHub Advanced Security, Semgrep, more) and produces fix PRs across that input. Securie wins on the fix-correctness commitment: the patch is regression-tested against the exploit before it ships, so a fix that does not actually fix the bug cannot pass. The procurement question is whether you want auto-fix as a layer on your existing stack (Mobb) or as one stage of a sandbox-verified pipeline (Securie).
FAQ
Mobb's auto-fix already produces high-quality patches. What does sandbox regression-testing add?
Mobb's patches are derived from the finding pattern + the surrounding context. The patches are typically high-quality, but the commitment is structurally weaker than sandbox regression-testing — there is no exploit to test the patch against. A patch that pattern-matches as 'fixed' may still leave the underlying vulnerability exploitable under different input. Securie's commitment is structurally stronger: the patch must cause the same reproduced exploit to fail, or the patch is rejected. The difference matters most for non-trivial bugs (logic vulnerabilities, framework-specific bypasses) where pattern-derived patches can miss the real fix.
Can I run Mobb on top of Securie's findings?
In principle yes — Securie produces SARIF-compatible finding output. In practice the wires are not currently integrated, and the value is unclear because Securie produces auto-fix PRs natively. The Mobb-on-Securie combination would be redundant on the auto-fix axis. If you are already a Mobb customer with an existing SAST integration, evaluate Securie as a replacement for both rather than adding it as a third tool.
Does Securie's auto-fix work for languages outside its launch scope?
No. Launch auto-fix coverage tracks the specialist surface — TypeScript + JavaScript on Next.js + Supabase + Vercel. Python and Go are on the Series-A roadmap. If your stack is Java, C#, or other languages, Mobb's broader language matrix (inherited from the upstream SAST it integrates with) is the more practical choice today.
What about manual fix-quality review?
Both tools produce PRs the developer reviews before merging. The review burden differs in shape: Mobb's PRs are pattern-derived patches you review for correctness against the original finding. Securie's PRs are sandbox-regression-tested against the original exploit, so review focuses on style + maintainability rather than 'does this actually fix the bug' — the sandbox already answered that.
How does the audit story compare?
Mobb produces a fix PR + an audit log of the patch operation. Securie produces a fix PR + a signed in-toto + DSSE + Sigstore-rekor attestation per scan + per-finding ProofArtifact persistence (the reproduced-exploit trace + the regression-tested patch). For SOC 2 / FedRAMP-pathway audits where cryptographically signed evidence per scan is the requirement, Securie's attestation chain is structurally different from a fix-PR audit log.