Different coding platforms have different anti-cheat measures. Some block copy-paste. Some disable right-click. Some use proctoring software with screen analysis. Some don't care at all.
If you're considering AI assistance during interviews, the platform matters more than most people realize. This is the platform-by-platform breakdown of what works where.
The four levels of platform restriction
Platforms fall into one of four categories:
- Open - no restrictions. Copy-paste works. Tab-switching is fine. This is most "good enough" company-internal interviews.
- Restricted - copy-paste disabled, but no monitoring beyond standard screen sharing. CoderPad and HackerRank fit here.
- Monitored - screen sharing plus active anti-cheat detection (tab switching alerts, suspicious behavior flags). Some CodeSignal configurations.
- Locked - full proctoring software, browser lockdown, kernel-level monitoring. Used by some large companies for hiring drives.
AI tool effectiveness varies dramatically across these levels. Let's go platform by platform.
LeetCode (during company-branded contests)
Restriction level: Open to Restricted, depending on the company.
Standard LeetCode practice has no restrictions - copy-paste works fine, you can have other tabs open. Company-branded interviews (Google's coding interviews on LeetCode, for example) sometimes restrict copy-paste but rarely add deeper monitoring.
What works:
- OS-level invisible AI tools (Acemode, Cluely) - fully effective
- Browser extensions - work for tab-share, fail for full screen share
- ChatGPT alt-tabbing - risky, your eye movement is visible
- GitHub Copilot - doesn't work, LeetCode is a browser environment
Best approach: Native desktop AI tool with screen-reading. The LeetCode UI is well-formatted and AI tools read it accurately.
CoderPad
Restriction level: Restricted.
CoderPad explicitly disables copy-paste in its interview environment. They also detect tab focus changes and notify the interviewer. This is one of the most-used platforms by FAANG companies.
What works:
- OS-level invisible AI tools that read screen pixels - work perfectly because they don't touch the clipboard at all
- Anything that requires copy-paste - fails
- Browser extensions - partially work but vulnerable to tab-focus monitoring
- ChatGPT alt-tabbing - high risk, tab focus loss is detected
Best approach: Native desktop AI tool that reads the screen and outputs to a hidden window. You then type the solution yourself in your own naming style. This is the platform Acemode was built for.
HackerRank
Restriction level: Restricted to Monitored, depending on configuration.
HackerRank has multiple modes. The standard interview mode disables copy-paste but doesn't actively monitor. The "secure" mode adds active proctoring and tab-focus detection.
HackerRank also provides company-customizable proctoring add-ons. Some companies enable webcam monitoring with AI behavior analysis. Most don't.
What works:
- OS-level invisible AI tools - effective in standard mode
- Same tools in "secure" mode - invisibility holds, but be aware of webcam if active
- Anything else - fails or risks detection
Best approach: Same as CoderPad. Use a native desktop tool with screen reading. Be more careful about your eye movement if webcam proctoring is active.
CodeSignal
Restriction level: Monitored.
CodeSignal is more aggressive than most platforms. Their assessment mode includes:
- Copy-paste disabled
- Tab-switching alerts
- Optional webcam recording
- Screen recording of the assessment
- Behavioral anomaly detection
What works:
- OS-level invisible AI tools - invisibility holds against the screen recording (which uses the same OS APIs as Zoom)
- Browser extensions - risky due to tab-focus detection
- ChatGPT alt-tabbing - high detection risk
Best approach: If you must use AI on CodeSignal, use only screen-protected native tools. Type all answers yourself. Don't switch tabs at all. Be very deliberate about looking only at the assessment screen.
Also worth knowing: CodeSignal's behavioral analysis is mostly bark, not bite. Their "anomaly detection" generates a report, but companies rarely review the report unless something explicit is flagged. The threshold for explicit flags is high.
Karat (third-party interview service)
Restriction level: Open to Restricted.
Karat conducts interviews on behalf of companies via Zoom video calls with a Karat interviewer. The candidate uses a tool like CoderPad in another tab. The Karat interviewer is watching you on Zoom and your code in CoderPad.
What works:
- OS-level invisible AI tools - work perfectly. The Zoom + CoderPad combination is exactly what these tools were designed for.
Best approach: Same as CoderPad. The Karat interviewer is human and the tools designed against human observers work fine.
Custom company-built editors
Many large companies build their own interview tooling. Examples:
- Google's coding interview environment
- Amazon's bar-raiser tools
- Meta's Coderpad-equivalent
- Various startup-built systems
Restriction level: Variable, usually Restricted.
Custom tools tend to have basic restrictions (no copy-paste, single window) but rarely have sophisticated monitoring. Building good anti-cheat is expensive - most companies use off-the-shelf tools and don't bother.
What works:
- OS-level invisible AI tools - work in almost all custom environments because they don't depend on the platform's specific UI
- The screen-reading approach is platform-agnostic
Best approach: Same as CoderPad/HackerRank. The technique is platform-independent because you're reading what's on screen, not interacting with the platform.
Take-home assignments
Restriction level: Open (usually).
Take-home assignments are typically explicitly allowed to use AI. Many companies say so directly in the prompt: "you may use any tools you'd normally use at work."
Even when not explicitly allowed, take-homes are functionally impossible to monitor. You're working alone for hours or days. Whether you used AI is undetectable.
Best approach: Use whatever tools you want. Then in the discussion round (most take-homes have one), be ready to explain every line of your code. If you can't defend a piece of code, don't include it.
Interviews with proctoring software
Restriction level: Locked.
Some companies (mostly large ones, certain government contractors, and roles requiring security clearance) use proctoring software like:
- Proctortrack
- Honorlock
- Examity
- Internal IT-managed monitoring
These tools require installation, run with elevated permissions, and can:
- Monitor process lists for known cheating tools
- Capture the screen at kernel level (bypassing OS exclusion in some cases)
- Use webcam for active monitoring
- Lock down the browser to a single application
What works against proctoring software:
- Honestly, very little. If a tool has kernel-level access, it can probably see whatever it wants.
- Some users report that OS-level invisible apps still work because the proctoring tool relies on the same OS capture APIs as everything else. Mileage varies.
- The safest approach for proctored interviews is preparation, not assistance.
Best approach: Don't use AI assistance during proctored interviews. The detection risk is too high and the consequences are severe (offer rescindment, blacklisting). Use AI heavily for preparation instead, and rely on prep alone during the actual interview.
The detection truth nobody admits
Even on monitored platforms, the actual detection rate of AI tools is much lower than the platforms imply.
Why? Because:
- Generating false positives is bad for the platform's business (real candidates get falsely accused)
- Reviewing flagged interviews takes human time, which costs money
- Most companies don't actually review proctoring reports unless something goes very wrong
- The legal liability of accusing someone of cheating is real
The platforms are incentivized to look like they have strong detection (deters honest candidates from cheating). Their actual detection is weaker than their marketing.
This isn't an excuse to be reckless. But it's worth knowing the threat model is more about plausibility than technical detection. As long as your behavior looks like a normal candidate, even sophisticated detection systems usually don't flag you.
Quick reference table
| Platform | Risk | Best AI tool type |
|---|---|---|
| LeetCode | Low | Any |
| CoderPad | Low-Medium | OS-level invisible |
| HackerRank | Medium | OS-level invisible |
| CodeSignal | Medium-High | OS-level invisible only |
| Karat | Low-Medium | OS-level invisible |
| Custom editors | Low | OS-level invisible |
| Take-homes | Very Low | Anything |
| Proctored exams | Very High | Don't risk it |
The universal principles
Regardless of platform:
- Use OS-level invisible tools when possible. They work everywhere except hardcore proctored exams. Browser extensions are fragile and platform-dependent.
- Type your own answers. Even if AI generates them, type them yourself in your own variable naming. Pasting verbatim is the easiest way to get caught.
- Don't tab-switch. Almost every monitored platform tracks tab focus. Native desktop apps that don't require tab switching are dramatically safer.
- Pre-test on the platform. Practice with your AI tool on the actual platform before the interview. Some platforms have UI quirks that affect screen reading.
- Know the threat model. Most "anti-cheat" is theater. Real proctoring is dangerous. Calibrate accordingly.
Match your AI tool to the platform's restriction level, and you'll have far better outcomes than people who use the same approach everywhere.