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The bug no black-box test would find

Source Code Review

We review critical code and business logic to uncover vulnerabilities and edge cases that external testing can miss.

Why this matters for iGaming

The Costliest Bugs Don't Look Like Bugs

Some vulnerabilities live inside perfectly valid code. They emerge only when specific functions, permissions, transactions, or dependencies interact in ways the system was never designed to handle.

Source review exposes those hidden paths by tracing how critical logic actually behaves. We find flaws that external testing can miss and show exactly where the code creates exploitable risk.

What we assess

Read in the Context of the Whole System

A source code review is scoped around how your iGaming platform actually fits together, not audited function by function, so findings reflect real data flows rather than isolated code smells.

Business logic

Wallet and ledger operations, bonus and promotion state machines, bet placement and settlement, and how wagering requirements are enforced end to end.

Access control

Authorization checks across roles, object ownership, and any operation sensitive enough to need one, checked for the gaps a black-box scan can't see.

Concurrency

Race conditions in balance updates, payout processing, and any transaction path where parallel requests can be made to interfere with each other.

Cryptography

Key handling, source of randomness, hashing, and whether cryptographic primitives are implemented the way they're supposed to be, not just present.

Input handling and injection

Where trust boundaries sit, what validation actually enforces, and which sinks are dangerous once an assumption about "safe" input turns out to be wrong.

Data flows

How player, payment, and identity data move across modules, and where along that path something sensitive can end up somewhere it shouldn't.

Third-party and dependency risk

Unsafe use of libraries and integration points that quietly widen the attack surface without a line of your own code changing.

In practice

Five Flaws Scanners Structurally Miss.

Every engagement is built around a specific, business-critical question rather than an open-ended hunt for bugs. Each one is answered by reading the code itself, the only way to get a definitive yes or no.

/01

Can a bonus be claimed, converted, or cleared along a path it was never meant to take?

Researchers trace the promotion state machine end to end, looking for a sequence that lets a player exit wagering requirements they were supposed to meet.

/02

Can a wallet balance be pushed below zero?

Testing targets concurrency in balance and payout handling, checking whether parallel requests against the same wallet can extract more than exists.

/03

Is every sensitive operation actually gated by an authorization check?

Researchers work through access control across roles and object ownership, surfacing gaps that are reachable in code but invisible to anything probing from outside it.

/04

Does the randomness behind outcomes hold up?

RNG and cryptographic implementations in outcome-sensitive code are reviewed for weak or misused primitives, not just their presence.

/05

Where does sensitive data end up that it shouldn't?

Data flows are traced across modules to find player, payment, and identity fields leaking into logs, responses, or third-party calls through paths no external test would exercise.

Our methodology

Manual-Led, Senior-Only, Framework-Aligned

A methodology built to hold up under scrutiny from the people who own the codebase, not just the people who commissioned the report. Your code is treated as the sensitive asset it is: reviews run from a read-only copy of the source under agreed handling terms, with scope boundaries and data handling locked in before work begins.

Read in architecture context

Code is reviewed against how your system actually fits together, tracing data flows across modules instead of auditing functions in isolation.

AI-directed reasoning at scale

Researchers direct frontier AI to reason about code in context: following data flows, surfacing interaction patterns that aren't obvious at a glance, and generating adversarial inputs that probe boundary conditions a rule-based scanner has no rules for.

Beyond the scanner set

Business-logic flaws, race conditions, cryptographic misuse, and access-control gaps, the categories automated tooling is structurally unable to reach.

Senior researchers, every engagement

The same experienced offensive researchers own the review start to finish.

Results your team can benchmark

Typical focus areas include authentication and session logic, authorization and multi-tenancy, financial and ledger correctness, bonus and game logic, cryptographic implementation, unsafe deserialization and injection sinks, error handling and information exposure, and dependency risk.

Scope

The Logic That Actually Moves Money

Each area of coverage is discussed with your team before the review starts, focused on the modules where a flaw would matter most.

What the engagement covers

Core platform services — the modules handling money, players, and game outcomes
Authentication and authorization — identity, sessions, and access-control logic
Wallet and payment logic — deposits, withdrawals, balances, and reconciliation
Bonus and promotion engine — issuance, wagering, conversion, and expiry logic
Integrations — provider, aggregator, payment, and KYC touchpoints in code
Cryptographic components — key management, randomness, and data protection

What you receive

Findings tied to the exact location in code, with business impact
Code-level evidence showing the path to the flaw, not just a line number
Remediation guidance written for the engineers who'll implement the fix
Executive summary on code-level risk
Retesting against the fixed code, included in the engagement

Why GameGuardz

The Value Is Knowing Which Function Settles a Real-Money Bet

Static analysis can surface endless findings. The harder part is knowing which code actually matters: where ledger logic lives, what controls the bonus engine, and which functions govern real-money transactions.
GameGuardz reviews your code with iGaming context already in hand, linking vulnerabilities to the functions they affect and giving your team clear evidence of what matters, why it matters, and what needs fixing.

Faq

Questions we get asked.

A penetration test probes your platform from the outside and finds what's reachable without seeing the code behind it. A source code review reads the logic directly, which is the only way to reliably catch business-logic flaws, race conditions, and cryptographic misuse that never surface as an external symptom.

Yes, a source code review requires access to the code itself. Engagements run from a read-only copy under agreed handling terms, with scope, access, and data-handling boundaries locked in before the review starts.

No. Automated tools flag pattern matches and produce a high volume of noise. This is a manual review led by senior researchers, directing AI to reason about data flows and boundary conditions in context, then judging what actually matters, the categories automated tooling structurally can't reach.

Engagements are scoped to your platform's actual stack. Get in touch with the languages and frameworks in play and we'll confirm fit during scoping.

Either works. Most engagements focus on the modules that handle money, identity, and game outcomes, since that's where a review pays for itself fastest, but scope is agreed with your team based on where the risk actually sits.

Take us where the risk lives in your codebase.

A call is enough for us to scope the repositories and modules worth reviewing first.

Request a Code Review