Reasoning Analytically About Password-Cracking Software Enze Alex - - PowerPoint PPT Presentation

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Reasoning Analytically About Password-Cracking Software Enze Alex - - PowerPoint PPT Presentation

Nov 12, 2022 12 likes •827 views

Reasoning Analytically About Password-Cracking Software Enze Alex Liu , Amanda Nakanishi, Maximilian Golla, David Cash, Blase Ur Chic4go 2 Attack Model 80d561388725fa74f2d03cd16e1d687c 3 Attack Model 80d561388725fa74f2d03cd16e1d687c

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Reasoning Analytically About Password-Cracking Software

Enze “Alex” Liu, Amanda Nakanishi, Maximilian Golla, David Cash, Blase Ur

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Chic4go

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Attack Model

80d561388725fa74f2d03cd16e1d687c

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Attack Model

80d561388725fa74f2d03cd16e1d687c

  • 1. h(“123456”) = e10adc3949ba59abbe56e057f20f883e

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Attack Model

80d561388725fa74f2d03cd16e1d687c

  • 1. h(“123456”) = e10adc3949ba59abbe56e057f20f883e
  • 2. h(“password”) = 5f4dcc3b5aa765d61d8327deb882cf99

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Attack Model

80d561388725fa74f2d03cd16e1d687c

  • 1. h(“123456”) = e10adc3949ba59abbe56e057f20f883e
  • 2. h(“password”) = 5f4dcc3b5aa765d61d8327deb882cf99
  • 3. h(“monkey”) = d0763edaa9d9bd2a9516280e9044d885

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Attack Model

80d561388725fa74f2d03cd16e1d687c

  • 1. h(“123456”) = e10adc3949ba59abbe56e057f20f883e
  • 2. h(“password”) = 5f4dcc3b5aa765d61d8327deb882cf99
  • 3. h(“monkey”) = d0763edaa9d9bd2a9516280e9044d885
  • 4. h(“letmein”) = 0d107d09f5bbe40cade3de5c71e9e9b7

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Attack Model

80d561388725fa74f2d03cd16e1d687c

  • 1. h(“123456”) = e10adc3949ba59abbe56e057f20f883e
  • 2. h(“password”) = 5f4dcc3b5aa765d61d8327deb882cf99
  • 3. h(“monkey”) = d0763edaa9d9bd2a9516280e9044d885
  • 4. h(“letmein”) = 0d107d09f5bbe40cade3de5c71e9e9b7
  • 5. h(“p@ssw0rd”) = 0f359740bd1cda994f8b55330c86d845

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Attack Model

80d561388725fa74f2d03cd16e1d687c

  • 1. h(“123456”) = e10adc3949ba59abbe56e057f20f883e
  • 2. h(“password”) = 5f4dcc3b5aa765d61d8327deb882cf99
  • 3. h(“monkey”) = d0763edaa9d9bd2a9516280e9044d885
  • 4. h(“letmein”) = 0d107d09f5bbe40cade3de5c71e9e9b7
  • 5. h(“p@ssw0rd”) = 0f359740bd1cda994f8b55330c86d845
  • 6. h(“Chic4go”) = 80d561388725fa74f2d03cd16e1d687c

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Chic4go

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Guess # 6

Chic4go

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Guess # 6 Guess # 13,545,239,432

Chic4go

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SLIDE 13

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Password-Cracking Methods

Probabilistic Models Software Tools

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Password-Cracking Methods

Probabilistic Models Software Tools

Chic4go

Guess #

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Password-Cracking Methods

Probabilistic Models Software Tools

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Chic4go

Guess #

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Guess Number by Enumeration

  • 1. 123456
  • 2. password
  • 3. monkey
  • 4. letmein
  • 5. p@ssw0rd
  • 6. Chic4go

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Does Not Scale !!!

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Our Analysis Goals

  • 1. Compute guess numbers efficiently
  • 2. Configure guessing method systematically

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Outline

  • State of the art
  • How software password-cracking tools work
  • Our efficient techniques for guess numbers
  • Our techniques for systematic configuration

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Probabilistic Models

Markov Models [Narayanan and Shmatikov, CCS 2005] Probabilistic Context-Free Grammars [Weir et al., S&P 2009] Neural Networks [Melicher et al., Usenix Security 2016]

Guess # Configuration

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Probabilistic Models

Markov Models [Narayanan and Shmatikov, CCS 2005] Probabilistic Context-Free Grammars [Weir et al., S&P 2009] Neural Networks [Melicher et al., Usenix Security 2016]

Guess # Configuration

[CCS 2015]

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Probabilistic Models

Markov Models [Narayanan and Shmatikov, CCS 2005] Probabilistic Context-Free Grammars [Weir et al., S&P 2009] Neural Networks [Melicher et al., Usenix Security 2016]

Guess # Configuration

[CCS 2015]

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Probabilistic Models

Markov Models [Narayanan and Shmatikov, CCS 2005] Probabilistic Context-Free Grammars [Weir et al., S&P 2009] Neural Networks [Melicher et al., Usenix Security 2016]

Guess # Configuration

[CCS 2015]

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Probabilistic Models

Markov Models [Narayanan and Shmatikov, CCS 2005] Probabilistic Context-Free Grammars [Weir et al., S&P 2009] Neural Networks [Melicher et al., Usenix Security 2016]

Guess-Efficient

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Guess-Efficient Wall-Clock Time Slow

Probabilistic Models

Markov Models [Narayanan and Shmatikov, CCS 2005] Probabilistic Context-Free Grammars [Weir et al., S&P 2009] Neural Networks [Melicher et al., Usenix Security 2016]

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Software Tools

John the Ripper Hashcat

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chicago

chicago1 chicago2 chicago3 chicago6 chicago9 chicdog chicagos CHICAG chicaga Chicago CHICAGO CHIcago

Software Tools

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Guess-Inefficient Wall-Clock Time Fast

Software Tools

John the Ripper Hashcat

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Guess-Inefficient Wall-Clock Time Fast

Software Tools

John the Ripper Hashcat

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Software Tools

John the Ripper Hashcat

Guess # Configuration

[S&P 2019]

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Outline

  • State of the art
  • How software password-cracking tools work
  • Our efficient techniques for guess numbers
  • Our techniques for systematic configuration

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Mangled Wordlist Attack

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Mangled Wordlist Attack

Wordlist

Super Password Chicago

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Mangled Wordlist Attack

Wordlist

Super Password Chicago

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

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Rulelist

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Mangled Wordlist Attack

Wordlist

Super Password Chicago

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

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Super1

Rulelist Guesses

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Mangled Wordlist Attack

Wordlist Rulelist

Super Password Chicago

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Guesses

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Super1 Password1

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Mangled Wordlist Attack

Wordlist

Super Password Chicago

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Super1 Password1 Chicago1

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Rulelist Guesses

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Mangled Wordlist Attack

Wordlist

Super Password Chicago

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Super1 Password1 Chicago1 Super P4ssword Chic4go

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Rulelist Guesses

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Mangled Wordlist Attack

Wordlist

Super Password Chicago

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Super1 Password1 Chicago1 Super P4ssword Chic4go super password chicago

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Rulelist Guesses

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Example Wordlists and Rulelists

Wordlist

PGS (≈ 20,000,000) Linkedin (≈ 60,000,000) HIBP (≈ 500,000,000)

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Example Wordlists and Rulelists

Wordlist Rulelist

PGS (≈ 20,000,000) Linkedin (≈ 60,000,000) HIBP (≈ 500,000,000) Korelogic (≈ 5,000) Megatron (≈ 15,000) Generated2 (≈ 65,000)

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Example Wordlists and Rulelists

Wordlist Rulelist

PGS (≈ 20,000,000) Linkedin (≈ 60,000,000) HIBP (≈ 500,000,000) Korelogic (≈ 5,000) Megatron (≈ 15,000) Generated2 (≈ 65,000)

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109 - 1015 guesses

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Example Wordlists and Rulelists

Wordlist Rulelist

PGS (≈ 20,000,000) Linkedin (≈ 60,000,000) HIBP (≈ 500,000,000) Korelogic (≈ 5,000) Megatron (≈ 15,000) Generated2 (≈ 65,000)

109 - 1015 guesses

+ Hackers’ private word/rule lists

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Outline

  • State of the art
  • How software password-cracking tools work
  • Our efficient techniques for guess numbers
  • Our techniques for systematic configuration

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Guesses

Super1 Password1 Chicago1 Super P4ssword Chic4go super password chicago

Is This Password in the Guesses?

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Chic4go

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Is This Password in the Guesses?

Wordlist Rulelist

Super Password Chicago

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Guesses

Super1 Password1 Chicago1 Super P4ssword Chic4go super password chicago

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We can work backwards!

Insight

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Insight: Invert Rules

Password

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Chic4go

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Insight: Invert Rules

Rulelist

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Password

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Chic4go

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Insight: Invert Rules

Rulelist

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Password

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Chic4go

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Preimages

Chicago Chic4go

Insight: Invert Rules

Rulelist

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Password

Chic4go

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*05 O03 d '7

Switch the first and the sixth char; Delete the first three chars; Duplicate the whole word; Truncate the word to length 7;

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Chic4go

Preimages? Preimages?

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Where in the Stream?

Wordlist Rulelist

Super Password Chicago

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Guesses

Super1 Password1 Chicago1 Super P4ssword Chic4go

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Where in the Stream?

Wordlist Rulelist

Super Password Chicago

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Guesses

Super1 Password1 Chicago1 Super P4ssword Chic4go

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Counting Guesses For Each Rule

Super Password Chicago

Wordlist Rule Guesses

Reject if no “a”; Replace a→ 4 2

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  • Fast Guess Number Estimation

Our First Contribution

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Fast Guess Number Estimation

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Linkedin + SpiderLab

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Fast Guess Number Estimation

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Linkedin + SpiderLab Guesses

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Fast Guess Number Estimation

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Enumeration Our Approach Size ~ 3 PB ~ 10 GB Linkedin + SpiderLab Guesses

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Fast Guess Number Estimation

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Enumeration Our Approach Size ~ 3 PB ~ 10 GB Preprocessing > 2 years < 1 day Linkedin + SpiderLab Guesses

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Fast Guess Number Estimation

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Enumeration Our Approach Size ~ 3 PB ~ 10 GB Preprocessing > 2 years < 1 day Mean Lookup ??? < 1 second Linkedin + SpiderLab Guesses

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Outline

  • State of the art
  • How software password-cracking tools work
  • Our efficient techniques for guess numbers
  • Our techniques for systematic configuration

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Software Tools Depend On

  • Order of rules
  • Contents of the rulelist
  • Order of words
  • Contents of the wordlist

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Wordlist Rulelist

Insight: Data-Driven Configuration

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Password Set

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Wordlist Rulelist New configuration

Insight: Data-Driven Configuration

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Password Set

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Data-Driven Configuration

  • Order of rules
  • Contents of the rulelist
  • Order of words
  • Contents of the wordlist

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  • Should the rules be in a different order?

Rule Ordering

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all
  • 1. Replace “a” → “4”
  • 2. Lowercase all
  • 3. Append “1”

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  • Should the rules be in a different order?
  • Key idea: Order by # cracks per guess

Rule Ordering

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all
  • 1. Replace “a” → “4”
  • 2. Lowercase all
  • 3. Append “1”

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Rule Ordering Results

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Ideal Data-driven Original

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Rule Ordering Results

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Ideal Data-driven Original

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Rule Ordering Results

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Ideal Data-driven Original

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  • Should other words be in the wordlist?
  • Key idea: Add frequent preimage “misses”

Word Completeness

Preimages Rulelist

  • 1. Append “1”
  • 2. Replace “a” → “4”
  • 3. Lowercase all

Oakland1 O@kl@nd

  • akland

Oakland

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Word Completeness (Sample Results)

Category Examples Set-specific bfheros; ilovmyneopets”””

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Word Completeness (Sample Results)

Category Examples Set-specific bfheros; ilovmyneopets””” Meaningful MaSterBrain; la la la

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Word Completeness (Sample Results)

Category Examples Set-specific bfheros; ilovmyneopets””” Meaningful MaSterBrain; la la la Short strings a2; a23; 7a; b2; q2

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Takeaway

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Analytical Tools

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Analytical Tools Guess Number

Takeaway

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Analytical Tools Guess Number

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Takeaway

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Analytical Tools Guess Number Configuration Tools

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Takeaway

https://github.com/UChicagoSUPERgroup/

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Analytical Tools Guess Number Configuration Tools

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Analytical Tools Guess Number Configuration Tools

https://github.com/UChicagoSUPERgroup/

Takeaway

Reasoning Analytically About Password-Cracking Software

Enze “Alex” Liu, Amanda Nakanishi, Maximilian Golla, David Cash, Blase Ur

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