What is Entropy Analysis?
Detecting secrets by how random they look.
Short answer
Entropy analysis measures the randomness of a string to spot secrets that do not match a known format. High entropy strings, like generated API keys, stand out from normal language, and that signal is how LeakSnitch catches obfuscated or custom credentials.
In depth
Format based patterns catch known structures, but custom internal secrets may not match any template. Entropy gives a second layer: a token with very high character randomness inside a prompt is a strong signal it is a machine credential, even without a known prefix.
LeakSnitch uses Shannon entropy as a fallback that activates when other signals are weak, so unusual secrets do not slip through just because no format matched. Like everything else, the threshold is published and tunable by enterprise teams.
Frequently asked questions
Does entropy analysis cause false positives on normal text?
LeakSnitch only leans on entropy when context is missing, and random code tokens are common enough that entropy alone rarely triggers a block. It is a fallback signal, not a standalone tripwire.
Related terms
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