HOTP 6-Digit Window Lookup
Ideal independent uniform six-digit HOTP acceptance probability per blind attempt over caller accepted counter window; does not generate/verify HOTP or model throttling.
Description
Estimate an ideal random-guess match probability across accepted six-digit counter codes.
A six-digit one-time code has one million possible values under the ideal uniform model. Accepting several counter positions creates multiple candidate matches for one random guess.
When to use this tool
Estimate an ideal random-guess match probability across accepted six-digit counter codes. Use it when the input measurements and conventions below match the operation you need.
- Prepare acceptedCounters, respecting the measurement basis and boundaries below.
- Compare the worked example with your intended operation before reusing its result.
How to use the tool and how it works
- Enter every field in the input table using the stated units and exact supported selector spelling where applicable.
- Run the tool. Correct input errors before interpreting an output.
- Read the result fields below; use accompanying flags and the stated sign, boundary or model convention when interpreting a number.
acceptedCounters must be an integer from 1 to one million. The tool returns 1 minus (1 minus 1e-6) raised to acceptedCounters, using an independent-code model for the chance of at least one match.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| acceptedCounters | Accepted counters. | Integer; from 1 to 1000000 inclusive |
| Output field | Interpretation |
|---|---|
| result | Object containing the following named result fields. |
| result.idealBlindGuessProbability | Ideal blind guess probability; use the stated units and sign convention. |
{
"input": {
"acceptedCounters": 1
},
"output": {
"result": {
"idealBlindGuessProbability": 0.000001
}
}
}Limitations and assumptions
- No HOTP value, key, time window or real verifier is inspected. Correlations, duplicate codes, throttling, repeated guesses and implementation policy are not modeled.
- Every declared field is required and unexpected fields are rejected. Numeric inputs must be finite; input errors are distinct from a valid false result or an explicitly qualified output.
- Extremely large inputs and nonfinite or excessively large outputs are rejected. List positions reported by the tool use zero-based indices unless stated otherwise.
Alternative or Complementary methods
Use the applicable protocol specification and a reviewed implementation for real verification, hashing or key management. A format label, probability model or tentative text mapping does not replace that operation. Compare the scope of the nearby tools below before substituting one.
References
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