An adversary.
On your side.

Authorized adversarial testing for your next anti-cheat update.

Hire a cooperative adversary to build AI-assisted prototypes that reproduce player-level threats, test them using the same retail client as your players, and show your engineers exactly what happened.

Retail client. No studio source.Studio-authorized scope.

RED-TEAM INSTINCTS.
PURPLE-TEAM OUTCOMES.

A new idea for fairer games Concept / 0.1

Why is this necessary?

The next cheat can be built before the next player report.

We want players to win on skill. Community reports are valuable, but they start with what someone notices. They rarely come with the cheat’s code, intended behavior, failed attempts or a repeatable test.

Your next defense doesn’t have to wait for that report. BlindSpot puts a cooperative adversary to work after your anti-cheat update, while outside cheat developers are figuring out their next move.

Who are the threats?

A player can buy a cheat, build one, or exploit the game without extra software. Our focus is the private, AI-assisted cheat developer who keeps changing their own tools.

Open a profile to explore the behavior and the coverage question.

00Fair playerPlays within the rulesClean baseline

Uses permitted controls and tools without deliberately exploiting the game. Skilled or unusual play can still look suspicious to someone watching.

The coverage question

Can the test distinguish unfair assistance from legitimate play? Clean control sessions give the studio a comparison point.

01Mechanics exploiterAbuses a bug or an unintended interactionIn-game abuse

Finds an advantage inside the game’s own systems without needing an external program. A widely shared exploit may surface through community reports.

The coverage question

How much damage can the behavior cause, and can it be reproduced? A simple exploit can still have serious competitive or economy consequences.

02Automation userUses macros, scripts or input devicesRules and context matter

Automates an action or a sequence of inputs. Some tools support legitimate accessibility; other uses provide a prohibited advantage. The game’s rules and actual behavior matter.

The coverage question

Can you identify the unfair behavior without misclassifying permitted use? Repetition alone does not make every automation case trivial to detect.

03Commercial cheat customerBuys access to somebody else’s toolingDistribution at scale

Needs little development skill to use a sophisticated product. Some users are blatant; others are restrained. Purchases give suppliers a reason to maintain their tools.

The coverage question

How does a distributed tool affect matches across its users and settings? Low effort for the buyer can still mean substantial harm for the game.

04Vibe hackerAI-assisted cheat developerBlindSpot’s focus

A player uses AI coding tools to prototype bespoke cheats, then revises them around their own play style. The tool may stay private, with no widely distributed version for your team to inspect.

Test this threat with a cooperative adversary

Hire a cooperative adversary who reveals their code, intent and test sessions as they work. Private does not mean undetectable; it means your coverage needs testing against that specific behavior.

05Commercial cheat developerBuilds, sells and maintains cheat productsA persistent supply chain

Has an incentive to restore a product after defenses change and keep paying customers. Teams may combine specialist engineering with distribution, support and ongoing maintenance.

The coverage question

How do you keep pressure on a supplier that keeps adapting? BlindSpot’s initial pilot targets player-level experiments; deeper specialist research needs its own scope.

A working model of access and behavior, not a universal danger score. Profiles overlap. Impact, reach and detectability depend on the game; the share of players building private AI-assisted cheats is not established here.

Research behind the profiles

How does it work?

I’m Tim, your cooperative adversary.

My background is web and software development, with very little game-development experience before this work. That outside perspective is useful: the pilot tests what a technically capable player without a game-development background can attempt with generative tools. Your engineers get documented results from that player-level starting point.

01 / AGREE

Choose the question
and the rules.

We choose the threat surface, such as information access, aim assistance or input automation, and the coverage question to test. Then we agree on the build, accounts, environment, permitted actions and stop conditions. You authorize the scope before work begins.

02 / BUILD

Vibe-code
a test prototype.

I use the same publicly available AI coding tools a vibe hacker can use, such as ChatGPT and Claude, to build scoped, player-level prototypes. I document what each version is meant to do, then test it on the agreed retail build.

03 / WORK TOGETHER

See the work
as it happens.

My telemetry and working dossier update in near real time, so your engineers can watch results arrive, compare their logs and redirect the next test. You can also watch game sessions live through an optional private stream. Code changes, attempted behavior and session times stay in the record.

What do we do?

Build and test the small, private tools a player could make. Choose a focused subset of these examples around the behaviors your team wants to investigate.

See the evidence this produces
Information advantage
Investigate whether a player can obtain an unfair view of the match through the retail client. Document what was attempted and what was actually observable.
Aim and input assistance
Test approved forms of assisted behavior beside clean sessions, giving your team known actions to compare with its detection signals.
Repeated-input automation
Test scoped actions such as repeated clicks or input sequences. Compare their effects and signals with manual play and studio-permitted accessibility use.
Movement and action rules
Examine whether the retail client allows actions outside the game’s intended movement or timing rules. Record attempted violations alongside legitimate edge cases.
Variations in assisted play
Compare agreed levels of assistance and different play styles. Give your engineers labeled sessions to investigate, including sessions where no visible enforcement occurs.
Post-patch regression checks
Rerun an agreed prototype after a defense changes. Document what now fails, what still works and which results need studio-side confirmation.
Custom player-level experiments
Bring a specific concern about what a player could build with public AI tools. We scope a prototype and a repeatable test around that question.

You get the prototype’s code, intended behavior and session evidence privately. Failed builds and blocked attempts stay in the record. A working bypass is never promised.

Keep testing
while they rebuild.

Outside cheat developers keep their work private. Your cooperative adversary shares the attempt, so your team can improve during the same post-patch blind spot.

THE POST-PATCH WINDOW
YOUR UPDATETHE BLIND SPOTTHEIR NEXT MOVE
Studio defenseAttacker adaptationHover a point to inspect both sides.

Illustrative sequence, not a prediction of attacker timing or measured performance.

THE OPPORTUNITY

Don’t leave the next test to them.

Switch on BlindSpot to see how your team can use the same window.

AUTO CYCLE · 4 SECONDS
PATCH DAYNEXT ITERATION

Drag the handle or tap a step to take control.

They reverse-engineer your update.
You get our debrief.

Less “we found something.”
More “here’s the evidence.”

Inspect the kind of handover your engineers would receive.

Download the sample data
POST-PATCH DOSSIERProject Vanguard / v1.4.2
FICTIONAL SAMPLE
ENGAGEMENT SUMMARY

Match these sessions to your detection logs.

The sample covers information advantage and aim assistance. Session observations show what the tester saw; your telemetry establishes what your defenses detected.

18sample matches
11.4hsample playtime
2test vectors
PRIORITY 01

Visibility into assisted behavior

No enforcement was observed in selected sample sessions. Detection status remains unconfirmed until the studio correlates its logs.

Needs correlation
No kick ≠ no detection. Enforcement and detection are different outcomes.
All names, numbers and outcomes here are fictional demonstration data.NO CUSTOMER RESULTS IMPLIED

Founding studios:
raise your anti-cheat bar
in 30 days.

The Post-Patch Pilot.

Hire a cooperative adversary to test your agreed retail build using AI-assisted prototypes. The work produces a private dossier your engineers can use throughout the engagement.

$7,500proposed fixed pilot fee
no ongoing commitment

Concept offer for discussion. Pricing, delivery and guarantee terms would be agreed before any engagement.

THE 30-DAY PILOTDESIGNED TO PROVE VALUE
  • 20 scoped hours of prototyping and test sessions
  • Two studio-approved retail accounts
  • Labeled logs + reproducible private artifacts
  • Prioritized dossier + 60-minute engineering readout
  • One focused retest after your team’s adjustment

The evidence guarantee

Proposed guarantee: deliver the agreed dossier or waive the final 50%. Blocked attempts count as evidence. A successful bypass is never promised.

Choose your testing environment

Creates a discussion brief with your selection. No booking or payment.

Your studio controls
the engagement.

Controlled testing needs clear boundaries. The studio chooses the scope and can stop a session at any time.

The conversation that sparked the ideaBULKHEAD · THE HOTZONE, EP2
Does this replace our anti-cheat?

No. It adds scoped adversarial testing and documented feedback to the systems and engineers you already have. No provider can promise that cheating disappears.

Why focus on private, AI-assisted cheats?

AI coding tools make custom development more accessible. A private tool may lack a known public signature, but behavioral and other detection layers can still catch it. We test a specific coverage question; we do not claim to know how many of your players build private cheats.

Why pay for this when players already report cheats?

Keep listening to your players. This engagement adds a cooperative adversary you can direct: known test actions, private prototype code, controlled comparisons and planned retests. The studio can investigate an agreed threat without waiting for a player to encounter it and submit a report.

Is this only useful before launch?

The proposed model fits an authorized beta or a released game’s update cycle. After launch, changes can create new questions about coverage. The pilot tests whether this approach produces useful evidence for your team; value is not assumed just because a game is live.

Will you test in live player matches?

Only if the studio explicitly authorizes that environment and its rules. Controlled sessions are an alternative. Any approved live scope is unranked, capped and stoppable. No ranked ladders, economy abuse, server disruption or uncontrolled testing.

Do you need our code or detection thresholds?

The proposed model starts with a retail client and no studio source access. Your team correlates our activity with its own telemetry. Account registration and enforcement settings are documented so results can be interpreted accurately.

Is BlindSpot Ops operating yet?

This is Tim’s business concept, shared to gather feedback and potential collaborators. The pilot is a proposed offer. The sample report is fictional. No studio affiliation, customer result or available job is implied.