# Password Structure Analysis & Behavioral Patterns Passwords encode behavioral signals. They are not random strings, they are **structured artifacts of human choice**. By decomposing passwords into layers, we can infer tendencies, constraints, and reuse behavior. This analysis aligns with **text analytics**, but focuses specifically on **authentication secrets**. We break structure into three analytical layers: - **Basic Pattern** - visibly obvious components - **Macro-Pattern** - statistical and structural characteristics - **Micro-Pattern** - subtle, contextual, and behavioral signals Each layer provides leverage for understanding _why_ passwords fail and _how_ failure scales. --- ## Text Analytics Applied to Passwords ### 1. Basic Pattern **Definition:** Visually obvious structure when comparing passwords across a small set. Examples: ``` R0b3rt2017! Jennifer1981! ``` Observed traits: - Base word is a personal name - Leetspeak substitution (`o → 0`, `e → 3`) - Four-digit year - Common terminal symbol (`!`) **Interpretation:** - Memorability prioritized over randomness - Compliance-driven modification - Strong reuse potential across systems **Analytical leverage:** This pattern maps cleanly to: - Dictionary + leetspeak rules - Hybrid attacks (`Dict + ?d?d?d?d?s`) > **Insight:** Basic patterns compress large search spaces into a small number of predictable constructions. --- ### 2. Macro-Pattern **Definition:** Statistical structure describing _how_ a password is built rather than _what_ it contains. Examples: ``` 7482Sacrifice Solitaire7482 ``` Observed traits: - Fixed numeric constant (`7482`) - Word placement varies, constant preserved - Length consistency (≈12 characters) - Charset limited to letters and digits **Structural summary:** - `?d?d?d?d + ?l?l?l?l?l?l?l` - `?l?l?l?l?l?l?l + ?d?d?d?d` **Interpretation:** - User prefers a fixed-length “safe zone” - Numeric anchor reused - Capitalization pattern is consistent **Analytical leverage:** - Hybrid attacks with static numeric suffix/prefix - Reduced effective entropy (constant collapses variability) > **Insight:** Macro-patterns define _bounds_. Once identified, they sharply reduce uncertainty. --- ### 3. Micro-Pattern **Definition:** Subtle, contextual signals expressing personal preference, themes, and habits. Examples: ``` BlueParrot345 RedFerret789 ``` Observed traits: - Color + animal construction - Title-case capitalization - Sequential numeric endings - Consistent semantic theme **Interpretation:** - Thematic reuse across passwords - Predictable evolution over time - Strong clustering potential **Analytical leverage:** - Custom combo dictionaries - Sequential digit masks (`?d?d?d`) - Theme-based expansion > **Insight:** Micro-patterns are where passwords leak _identity_, not just structure. --- ## Regional Password Trend Analysis ### US / EU / CA **Length distribution (English-language datasets):** - 7–9 characters dominate (~57%) - Sharp drop beyond 12 characters **Character frequency shift:** - Text: `etaoinshrdlcumwfgypbvkjxqz` - Passwords: `aeionrlstmcdyhubkgpjvfwzxq` **Top observed masks:** - `?l{6–10}` - `?l{6–8}?d{2}` - `?d{6–8}` **Key takeaway:** Lowercase dominance + short length = high probability mass early in guessing. --- ### CN (Chinese datasets) **Length distribution:** - Shorter on average - Digits heavily favored **Top observed masks:** - `?d{6–12}` - Mixed but digit-centric constructions **Key takeaway:** Numeric preference reshapes attack economics but does not eliminate predictability. --- ## Password Manager Output Patterns Password managers produce **high entropy**, but still leave **identifiable fingerprints**: |Manager|Length|Charset|Structural Signature| |---|---|---|---| |Safari|15|u/l/d|Grouped w/ hyphens| |Dashlane|12|u/l/d|Flat random| |KeePass|20|u/l/d/s|High entropy| |LastPass|12|u/l/d|Balanced| |RoboForm|15|u/l/d/s|Digit-heavy| |1Password|24|u/l/d/s|Long, uniform| **Insight:** Manager-generated passwords shift failure from _guessability_ to _exposure pathways_ (reuse, sync, endpoint compromise). --- ## Impact Assessment ### 1. Security Impact - Structural predictability dominates compromise outcomes - Complexity rules influence _shape_, not _strength_ - Reuse magnifies minor weaknesses into systemic failure ### 2. Analytical Impact - Pattern-based analysis explains early success rates - Cracking efficiency is driven by **structure recognition** - Entropy alone is a misleading metric ### 3. Organizational Impact - Passwords cluster by culture, role, and policy - Breaches reveal behavioral intelligence, not just secrets - Weakest system defines enterprise-wide risk ceiling --- ## Thinking in Graphs... UNDER CONSTRUCTION The below are notes that I am currently thinking with for concept tie ins across the site. This analysis maps directly to **attack path thinking**: | Password Analysis | Graph Analog | | ----------------- | ------------------------------ | | Structural reuse | Credential reuse edges | | Macro-patterns | Privilege boundary constraints | | Micro-patterns | Behavioral shortcuts | | Probability mass | High-value attack paths | | Scale effects | Path explosion | Passwords are **nodes**. Reuse and structure are **edges**. #graph --- ## Key Takeaways - Passwords are structured behavioral artifacts - Structure matters more than entropy - Scale converts predictability into inevitability - Analysis should focus on **patterns**, not strings - Defense improves when behavior is modeled, not assumed random [[Home]]