Adds a third LLM Attack generation mode ("cracked") that samples the
plaintexts already recovered this session from <hashfile>.out and asks the
model to infer the target organization's password conventions and emit new
candidates in the same style.
- llm.py: new _CRACKED_PROMPT (offensive candidate generation, explicitly
not the denylist-oriented _WORDLIST_PROMPT), a _PROMPTS mode->prompt map,
and a "cracked" branch in _build_request that tells the model not to
repeat already-cracked passwords.
- main.py: extract the wordlist sampling logic into the shared module-level
helper _sample_plaintext_file(path, cap, source_label) and call it from
both the wordlist and cracked branches of hcatOllama; guard missing and
empty .out files.
- attacks.py: offer mode 3 only when <hashfile>.out exists and is non-empty
(matching _markov_pick_training_source), with a clear message otherwise.
- README: document the three modes and the widened ollamaMaxSampleLines
scope.
Co-Authored-By: Claude <noreply@anthropic.com>
