feat: add LLM Markov Attack (menu option 15)

Add a new attack mode that uses a local LLM via Ollama to generate
password candidates, converts them into hashcat .hcstat2 Markov
statistics via hcstat2gen, and runs a Markov-enhanced mask attack.

Two generation sub-modes:
- Wordlist-based: feeds sample from an existing wordlist to the LLM
  as pattern context (config-selectable default with Y/N override)
- Target-based: prompts for company name, industry, and location
  for contextual password generation

Pipeline: Ollama API -> candidate file -> hcstat2gen -> LZMA compress
-> hashcat -a 3 --markov-hcstat2

Config additions: ollamaUrl, ollamaModel, markovCandidateCount,
markovWordlist. No new pip dependencies (uses stdlib urllib/lzma).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

config.json.example

@@ -22,5 +22,9 @@
   "bandrel_common_basedwords": "welcome,password,p@ssword,p@$$word,changeme,letmein,summer,winter,spring,springtime,fall,autumn,monday,tuesday,wednesday,thursday,friday,saturday,sunday,january,february,march,april,may,june,july,august,september,october,november,december,christmas,easter,covid19",
   "hashview_url": "http://localhost:8443",
   "hashview_api_key": "",
-  "hashmob_api_key": ""
+  "hashmob_api_key": "",
+  "ollamaUrl": "http://localhost:11434",
+  "ollamaModel": "llama3.2",
+  "markovCandidateCount": 5000,
+  "markovWordlist": "rockyou.txt"
 }