Source Code Review

Read the code, by hand.

Line-by-line manual review plus modern SAST across your stack. Every vulnerability is verified by hand by an operator who has shipped production code in that language, and shipped back as a PR-ready fix, never a raw tool dump.

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Manual, not just SASTVerified by handPR-ready fixesUnder NDA
routes/report.js · reviewed by hand
86 export async function getReports(req, res) {
88- const q = `SELECT * FROM reports
89- WHERE owner = '${req.query.user}'` // tainted
90- const rows = await db.query(q)
88+ const rows = await db.query( // parameterised
89+ 'SELECT * FROM reports WHERE owner = $1',
90+ [req.query.user])
91 res.json(rows)
CRITICALSQL injection, unparameterised query

How it works

SAST is the floor, not the report.

Tooling finds candidates fast. A human decides what is real, what matters, and how to fix it, then packages it to fit the way your team already ships.

schema

Threat modeling first

We map trust boundaries, data flows, and an asset taxonomy with your engineering lead, STRIDE and DFDs, so the review is aimed at real risk, not a generic checklist.

manage_search

SAST across the stack

Semgrep, CodeQL, and language-native scanners (gosec, bandit, njsscan, brakeman), plus a custom rule pack tuned to your codebase in the first day.

fact_check

Manual triage on every hit

Every finding is reviewed by hand by an operator fluent in that language. No false positives shipped, no scanner output rebadged as a report.

integration_instructions

Fits your SDLC

Findings arrive PR-ready with fix snippets and a JIRA-importable CSV, and the custom Semgrep rules drop straight into your CI to keep catching regressions.

What we review

Your language, where it matters most.

We review production code in the languages and frameworks below, and look hardest at the components where a single mistake becomes a breach.

Languages & frameworks

Python

Django · Flask · FastAPI

JS / TS

Node · Express · NestJS · Next.js

Java

Spring · Quarkus

Go

Gin · Echo · Fiber

Ruby

Rails · Sinatra

PHP

Laravel · Symfony

C# / .NET

ASP.NET Core · MAUI

Rust

Actix · Axum · async-std

Where we look hardest

Authentication

Login, password reset, MFA, SSO.

Authorization

Role checks, ownership, tenant boundary.

Session & token

JWT signing, refresh rotation, logout.

Crypto use

Encrypt-at-rest, KMS, key rotation.

Input validation

Every untrusted boundary, every parser.

Persistence layer

SQL builders, ORM trust, raw queries.

3rd-party integrations

Webhook validation, OAuth client behavior.

Background workers

Queue trust, deserialization, replay.

Build & deploy

CI/CD secrets, signing, artefact provenance.

What you get

Evidence your team can act on.

schema

Threat model doc

DFDs, STRIDE analysis, and an asset taxonomy for the reviewed system.

description

Findings report

Every finding with file, line, CWE, CVSS, and a suggested fix.

table_rows

JIRA-ready CSV

Import straight into your tracker, one issue per finding.

rule

Custom Semgrep rules

A stack-specific rule pack ready to run in your CI.

inventory_2

SBOM bundle

CycloneDX SBOM with a dependency-risk delta versus your previous release.

groups

Engineering walk-through

A live session with the team that wrote the code, walking every finding.

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FAQ

Questions, answered.

Which languages and frameworks do you cover?
Python (Django, Flask, FastAPI), JavaScript/TypeScript (Node, Express, NestJS, Next.js), Java (Spring, Quarkus), Go, Ruby on Rails, PHP (Laravel, Symfony), C#/.NET, and Rust. Every review is led by an operator who has shipped production code in that language, if your stack isn't listed, tell us and we'll be honest about whether we're the right fit.
What access do you need?
Read-only access to the repository, a scoped deploy key or a read-only collaborator seat is enough. We don't need write access, production credentials, or your infrastructure. Everything is scoped in the letter of engagement and covered by a mutual NDA before a single line is read.
How is this different from a penetration test?
A pentest attacks the running application from the outside and proves what an adversary can reach. A code review reads the source from the inside and finds flaws that never surface at runtime, logic only reachable in edge cases, dormant paths, weak crypto, unsafe deserialization. They catch different classes of bug, so serious teams do both: the review finds the root cause, the pentest confirms the blast radius.
How do you avoid drowning us in false positives?
Scanners are the floor, not the report. Every SAST hit is triaged by hand by an operator fluent in the language before it reaches you, we confirm the code path is actually reachable and exploitable, discard the noise, and only ship findings we can stand behind. You never get a raw tool dump with our name on it.
What are the deliverables?
A threat-model document (DFDs, STRIDE, asset taxonomy), a findings report with file, line, CWE, CVSS and a suggested fix per issue, a JIRA-importable CSV, a custom Semgrep rule pack for your CI, a CycloneDX SBOM, and a live engineering walk-through with the team that wrote the code.
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Brief us on the codebase.

Tell us what you need reviewed. An operator replies within one business day.

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