You can make the outcome unpredictable before the trigger fires, but you cannot make it unknown to every part of the program. Once the game generates the random value, the code holds it at that moment. The promise you can defend is narrower: players and ordinary game logic cannot compute, see, or practically predict the result before the trigger, provided the number is drawn at the trigger from a cryptographically secure source and kept out of every code path that runs before then.
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The phrase bundles several different parties, and each needs its own answer. Before the trigger, the outcome should be unavailable to:
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- the player’s client, including its UI, animations, and any cached state the browser or app keeps;
- other players, spectators, or anyone watching a network message stream;
- the game’s state object, save files, and any data structure that exists before the trigger;
- logs, analytics events, crash reports, and debugging output.
What you cannot promise is that the outcome is unknown to the process that generates it at the instant of generation. The accurate claim is about timing and information flow: the result is produced when the trigger fires and does not exist anywhere readable before that moment. Describing the goal as “unpredictability before the draw” keeps the claim true even though the code eventually holds the value.
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Architecture: draw at the trigger, not at the start
The most common mistake is to shuffle the chamber at game start, store the result, and simply hide it from the screen. That design does not meet the promise, because game logic can read the stored value at any time. The sequence below keeps the draw out of pre-trigger state.
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- Keep pre-trigger state free of the outcome. At game start, store only public facts such as the number of chambers (six for a standard revolver model), the round identifier, and the trigger status. Do not create an outcome field, even an empty one that is filled later.
- Move the draw to the trigger handler. When the trigger request arrives, call the platform’s secure random function once for that round. Do not reuse a value generated for an earlier round.
- Map the random bytes to the outcome space using the unbiased method described in the next section.
- Write the result only to the reveal path. The result should leave the handler in the same message or response that announces the reveal, and it should not be written to the shared state object beforehand.
- Discard intermediate values. Clear the raw bytes and any temporary variables, and make sure the logging layer never receives them.
Expected result: a client inspecting its own memory, its network traffic, or the server’s pre-trigger state finds no outcome. The only point where the result appears is the reveal event.
Where the draw runs: client, server, or both
Where the handler lives determines who can see the outcome early. In a single-player offline game, the trigger handler runs on the player’s device, so the player controls the environment and can inspect or modify it. That is acceptable for a casual solo game, but it means the promise is only against accidental leakage, not against the player.
In a multiplayer or online game, run the trigger handler on the server. The client sends a trigger request, receives only the reveal, and never receives the random bytes or the pre-trigger value. Operators with access to the server can still see the outcome, so the promise in that setting is “not visible to players or ordinary game code,” not “unknown to the operator.”
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Choosing a random source
Use the operating system’s cryptographically secure generator, exposed through the language’s secure-random API. Common examples include the secrets module in Python, crypto.randomBytes in Node.js, crypto.getRandomValues in browsers, and SecureRandom in Java. Do not use general-purpose generators such as Math.random, C’s rand(), or ordinary Random classes; they are designed for simulations and games where speed matters more than unpredictability.
A seeded pseudorandom generator is deterministic once its internal state is known. If you use one, protect its state as carefully as the outcome itself and seed it from a secure source. NIST’s SP 800-90 series separates deterministic random-bit generation from the entropy sources that seed it, so check which component your platform’s generator relies on.
Mapping the bytes to six chambers without bias
Six outcomes do not divide evenly into the 256 values of one byte, so a simple modulo introduces bias. Since 256 = 42 × 6 + 4, the remainders 0 through 3 occur one more time than 4 and 5 across the 256 possible byte values. A player comparing many rounds could in principle notice that difference, and a careful audit would flag it.
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Rejection sampling removes the bias:
- Draw one random byte (0 to 255).
- If the value is 252 or higher, discard it and draw again. (252 is the largest multiple of 6 that fits in a byte, and 252 = 42 × 6.)
- Otherwise, return the value modulo 6. Each chamber position 0 to 5 then has exactly 42 accepted byte values.
The rejection rate is 4 in 256, about 1.6 percent, so the expected number of draws per round is close to one. Assign the bullet to one chamber index and treat the result as a comparison against that index.
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Why passing statistical tests is not enough
It is tempting to generate a long sequence of outcomes, run frequency tests, and conclude the game is fair. That shows only that the sequence looks random in aggregate. RFC 4086 draws the distinction directly: “Statistically tested randomness in the traditional sense is NOT the same as the unpredictability required for security use.” The same document warns that a small seed space, such as a clock value, can be searched regardless of how complex the algorithm that follows is. For this game, the question is not whether the outcomes look uniform across thousands of rounds, but whether an attacker can predict one specific round before the trigger.
Verifying the result afterward: commit-then-reveal
Players or auditors sometimes want proof that the operator did not change the result after the trigger. Commit-then-reveal offers one approach. The server draws the outcome, publishes a cryptographic commitment to it (a hash of the outcome combined with a random nonce), and later reveals the outcome and nonce so anyone can check the commitment.
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This protocol answers a different question from the one in the title. The committed value exists before the trigger, and the party holding it knows it. Commit-then-reveal therefore suits a promise of “the operator cannot change the result,” not “no code knows the result before the trigger.” Choose the one that matches your promise, and do not present a commitment scheme as a way to hide the draw from the operator.
The protocol also introduces failure modes. A participant can withhold a reveal or trigger a reset after seeing an unfavorable outcome, and a NIST publication on commit-then-reveal protocols discusses this risk. Write the rules before launch:
- a deadline for the reveal, and what happens if it passes;
- whether a round can be reset, and who is allowed to request a reset;
- whether an aborted round counts as a result, a loss, or a void;
- whether the outcome of a reset round can be reused or must be redrawn.
Comparing the three designs
| Design | When the outcome is drawn | Who can access it before the trigger | Predictable before the trigger? | Verifiable afterward? | Abort or reset handling |
|---|---|---|---|---|---|
| Draw at game start, hide in the UI | At game start | Any code that can read the game state | Yes, to that code | Not stated; depends on logging design | Not stated; depends on rules you define |
| Draw at trigger, server-side only | At the trigger request | The server process and anyone with operator access | No, provided the generator is secure and nothing leaks | Not stated; requires a separate audit log design | Defined by your round rules |
| Commit at start, reveal at trigger | At game start (commitment published), revealed at the trigger | The party holding the committed value, which knows it before the trigger | Not hidden from the committer; the commitment reveals nothing to others | Yes, against the published commitment | Reveal can be withheld or a reset requested unless you write rules for it |
The table shows that the second design fits the title’s promise most closely. The third adds verifiability at the cost of an early-knowing party.
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Terminology and standards to get right
Avoid the phrase “truly random” in marketing or documentation. A cryptographic generator produces output that is computationally unpredictable under its stated assumptions, not a value guaranteed to be physically random. Where a physical entropy source is involved, the relevant NIST framework treats it as a separate component with its own assumptions. In NIST IR 8427 (2023), the SP 800-90 series uses a full-entropy assumption of at least 1−ε entropy per bit, with ε at most 2^-32. That is a framework assumption about entropy sources, not a probability of any game outcome and not a guarantee for your implementation.
Standards also change. NIST has stated that SP 800-90A is being revised to align with SP 800-90C. Check the current publication version, and the requirements of your jurisdiction or platform, before claiming standards compliance. If the game involves money or prizes, gambling regulations apply separately, and the randomness design does not settle them.
Quick Recap
Pre-release checks
- Search the pre-trigger state, save data, and network messages for any outcome field, hash, or seed that would reveal the result.
- Confirm the trigger handler is the only function that calls the random source for each round.
- Confirm the mapping uses rejection sampling, not a plain modulo.
- Check that logs, analytics, and crash reports exclude raw bytes and outcomes before the reveal.
- If you use commit-then-reveal, test the timeout, reset, and missing-reveal paths and confirm the written rules match the behavior.
- Describe the result as “unpredictable before the trigger” and avoid “certified,” “provably fair,” or “true random” unless you have evidence for your runtime, entropy source, and threat model.
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