Pakistani Password Wordlist

A Pakistani password wordlist, like any specialized wordlist, can be a valuable tool in the right hands, particularly for cybersecurity professionals conducting authorized security assessments. However, its creation and use must be approached with caution, responsibility, and a deep understanding of ethical hacking practices. Encouraging good password hygiene and implementing robust security measures are crucial steps in protecting digital information.

A Pakistani password wordlist is a specialized collection of strings used by cybersecurity researchers to test the strength of accounts in Pakistan

. These lists differ from generic global wordlists because they incorporate local linguistic, cultural, and geographic nuances that are common in Pakistani password choices. Core Components of a Pakistani Wordlist

A robust wordlist for this region typically combines several categories of local data: Common Personal Names pakistani password wordlist

: Many users incorporate their own names or those of family members. Masculine Names

: Muhammad (the most popular), Ali, Usman, Malik, Imran, and Bilal. Feminine Names : Rana, Ayesha, Raja, Sana, Fatima, and Maryam. Surnames & Tribes

: Surnames like Khan (27% of users), Ahmed, Ahmad, Malik, and Hussain are extremely common. Regional tribal names such as Baloch, Qureshi, and Shah are also frequently used. Geographic Markers If you are integrating this into a larger

: Names of major cities like Lahore, Karachi, Islamabad, and Peshawar, or even specific local landmarks like "Mazar-e-Quaid" or "Minar-e-Pakistan". Cultural & Religious Terms

: Phrases like "bismillah" are ranked among the most popular non-pattern passwords in the region. Localized Patterns

: Combinations often include a name followed by digits (e.g., ), special characters, or local suffixes like "pk". Tools and Resources Passwords often reflect the user's native language and

Researchers use various specialized tools to generate or download these lists:

If you are integrating this into a larger tool (like a security audit suite or a custom cracking tool), consider these specific features:

This script is modular. It takes base keywords and applies "mutation rules" specific to Pakistani user behavior.

import itertools
import datetime
class PakistaniWordlistGenerator:
    def __init__(self):
        # Core pillars of Pakistani passwords
        self.base_keywords = [
            # National Identity
            "pakistan", "pak", "paki", "islam", "islamabad", "karachi", "lahore", 
            "rawalpindi", "pindi", "multan", "quetta", "peshawar", "kashmir",
            "green", "flag", "jinnah", "quaideazam",
            # Religion & Spirituality
            "allah", "muhammad", "bismillah", "rehman", "rahim", "malik",
            # Cricket & Pop Culture
            "cricket", "afridi", "babar", "rizwan", "shaheen", "wasim", 
            "ramiz", "shahid", "boom", "greenflag",
            # Roman Urdu / Common Words
            "jaanu", "jaan", "pyar", "mohabbat", "dil", "yaar", "zindagi",
            "apna", "ghar", "dosti", "khush", "mehtab", "sher", "bacha",
            # Tech / Generic
            "password", "admin", "login", "user", "wifi", "ptcl", "jazz"
        ]
# Special numbers in Pakistani culture
        self.sacred_numbers = ["786", "110", "92", "14"] # 92 is country code, 14 is Aug 14
# Common appendices
        self.years = self.generate_years()
        self.special_chars = ["!", "@", "#", "$", "."]
        self.network_prefixes = ["0300", "0301", "0321", "0331", "0345"] # Common mobile prefixes
def generate_years(self):
        current_year = datetime.datetime.now().year
        return [str(y) for y in range(1970, current_year + 1)]
def mutate_case(self, word):
        """Generate variations of capitalization"""
        return [word, word.upper(), word.capitalize(), word.lower()]
def append_numbers(self, word):
        """Append culturally relevant numbers"""
        mutations = set()
# Simple numbers 0-9, 00-99
        for i in range(100):
            mutations.add(f"wordi")
            mutations.add(f"wordi:02d") # leading zero (e.g., 01)
# Sacred Numbers
        for num in self.sacred_numbers:
            mutations.add(f"wordnum")
# Years
        for year in self.years:
            mutations.add(f"wordyear")
return mutations
def leet_speak_pak_style(self, word):
        """
        Minimal leet speak (a=4, e=3) but focused on styles seen locally.
        Example: pakistan -> p@kistan, pak1stan
        """
        replacements = 
            'a': ['4', '@'],
            'e': ['3'],
            'i': ['1', '!'],
            'o': ['0'],
            's': ['$', '5'],
            'h': ['#']
# Just doing simple first-level replacement for performance
        leet_words = set()
        for char, replacements_list in replacements.items():
            if char in word:
                for r in replacements_list:
                    leet_words.add(word.replace(char, r, 1)) # Replace first occurrence
# Common specific Pakistani l33t: P@kistan, P4kistan
        if "pak" in word:
            leet_words.add(word.replace("a", "@", 1))
            leet_words.add(word.replace("a", "4", 1))
return leet_words
def generate_wordlist(self, output_file="pak_wordlist.txt"):
        final_wordlist = set()
print(f"[*] Starting generation with len(self.base_keywords) base keywords...")
for keyword in self.base_keywords:
            # 1. Case Mutations
            case_variations = self.mutate_case(keyword)
for variant in case_variations:
                # Add plain word
                final_wordlist.add(variant)
# 2. Number Appending
                num_variations = self.append_numbers(variant)
                final_wordlist.update(num_variations)
# 3. Leet Speak
                leet_variations = self.leet_speak_pak_style(variant)
                final_wordlist.update(leet_variations)
# 4. Special Char Suffix (Common: pakistan!, pak@123)
                for char in self.special_chars:
                    final_wordlist.add(f"variantchar")
                    # Combine with sacred number
                    final_wordlist.add(f"variantchar786")
# 5. Combinations (Two-word combos)
        # Examples: "jaanu786", "pakcricket", "lovepakistan"
        common_combo_keys = ["jaanu", "pyar", "dil", "pak", "love", "cricket"]
        for word1 in common_combo_keys:
            for word2 in self.base_keywords:
                if word1 != word2:
                    combo = f"word1word2"
                    final_wordlist.add(combo)
                    final_wordlist.add(f"combo786") # High probability combo
# Save to file
        print(f"[*] Generated len(final_wordlist) unique passwords.")
        with open(output_file, "w", encoding="utf-8") as f:
            for pwd in sorted(final_wordlist):
                f.write(pwd + "\n")
        print(f"[*] Wordlist saved to output_file")
# Run the generator
if __name__ == "__main__":
    gen = PakistaniWordlistGenerator()
    gen.generate_wordlist()

Passwords often reflect the user's native language and culture. When auditing systems in Pakistan, a security researcher might anticipate the use of: