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Chair of Network Architectures and Services Department of Informatics Technical University of Munich Evaluating Network Security Using Internet-wide Measurements Oliver Gasser Ph. D. Defense, Friday 24 th May, 2019 Chairman: Prof. Dr. Jrg

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Chair of Network Architectures and Services Department of Informatics Technical University of Munich

Evaluating Network Security Using Internet-wide Measurements

Oliver Gasser

  • Ph. D. Defense, Friday 24th May, 2019

Chairman: Prof. Dr. Jörg Ott Examiners: Prof. Dr.-Ing. Georg Carle

  • Prof. Anja Feldmann, Ph. D.
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Motivation

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Motivation

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Motivation

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Motivation

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Motivation

The Internet

  • Internet measurements can be leveraged to empirically assess security of
  • protocols,
  • devices,
  • implementations, and
  • configurations
  • Vast IPv6 address space poses big challenge for Internet measurements

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Motivation

The Internet

  • Internet measurements can be leveraged to empirically assess security of
  • protocols,
  • devices,
  • implementations, and
  • configurations
  • Vast IPv6 address space poses big challenge for Internet measurements

Goals

  • Improve measurement methodology for Internet-wide security measurements
  • IPv4 and IPv6
  • Empirically assess security of three different protocols
  • HTTPS
  • BACnet
  • IPMI

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Research questions

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Research questions

RQ I RQ II RQ III RQ IV RQ V

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Research questions

RQ I: How can we perform Internet-scale IPv6 measurements? ZMapv6 goscanner RQ II RQ III RQ IV RQ V

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Research questions

RQ I: How can we perform Internet-scale IPv6 measurements? ZMapv6 goscanner RQ II: How biased are address sources for IPv6 hitlists? Passive sources Active sources Biases in sources IPv6 Hitlist Service RQ III RQ IV RQ V

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Research questions

RQ I: How can we perform Internet-scale IPv6 measurements? ZMapv6 goscanner RQ II: How biased are address sources for IPv6 hitlists? Passive sources Active sources Biases in sources IPv6 Hitlist Service RQ III: Are HTTPS servers still vulnerable to MitM attacks? Certificate security HTTPS security RQ IV RQ V

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Research questions

RQ I: How can we perform Internet-scale IPv6 measurements? ZMapv6 goscanner RQ II: How biased are address sources for IPv6 hitlists? Passive sources Active sources Biases in sources IPv6 Hitlist Service RQ III: Are HTTPS servers still vulnerable to MitM attacks? Certificate security HTTPS security RQ IV: Are BACnet devices vulnerable to amplification attacks? Deployment Amplification Notification RQ V

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Research questions

RQ I: How can we perform Internet-scale IPv6 measurements? ZMapv6 goscanner RQ II: How biased are address sources for IPv6 hitlists? Passive sources Active sources Biases in sources IPv6 Hitlist Service RQ III: Are HTTPS servers still vulnerable to MitM attacks? Certificate security HTTPS security RQ IV: Are BACnet devices vulnerable to amplification attacks? Deployment Amplification Notification RQ V: Are IPMI devices vulnerable to MitM attacks? Deployment TLS security

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Research questions

RQ I: How can we perform Internet-scale IPv6 measurements? Chapter 3 ZMapv6 goscanner RQ II: How biased are address sources for IPv6 hitlists? Chapter 4 Passive sources Active sources Biases in sources IPv6 Hitlist Service RQ III: Are HTTPS servers still vulnerable to MitM attacks? Chapter 5 Certificate security HTTPS security RQ IV: Are BACnet devices vulnerable to amplification attacks? Chapter 6 Deployment Amplification Notification RQ V: Are IPMI devices vulnerable to MitM attacks? Chapter 7 Deployment TLS security

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Research questions

RQ I: How can we perform Internet-scale IPv6 measurements? Chapter 3 ZMapv6 goscanner RQ II: How biased are address sources for IPv6 hitlists? Chapter 4 Passive sources Active sources Biases in sources IPv6 Hitlist Service RQ III: Are HTTPS servers still vulnerable to MitM attacks? Chapter 5 Certificate security HTTPS security RQ IV: Are BACnet devices vulnerable to amplification attacks? Chapter 6 Deployment Amplification Notification RQ V: Are IPMI devices vulnerable to MitM attacks? Chapter 7 Deployment TLS security

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RQ II: How biased are address sources for IPv6 hitlists?

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RQ II: How biased are address sources for IPv6 hitlists?

Motivation

  • IPv6 address space too large to perform brute-force measurements
  • Assemble lists of IPv6 target addresses: IPv6 hitlists

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RQ II: How biased are address sources for IPv6 hitlists?

Motivation

  • IPv6 address space too large to perform brute-force measurements
  • Assemble lists of IPv6 target addresses: IPv6 hitlists

Measurements & analyses

  • Passive and active measurements
  • Empirical analysis of different types of biases
  • Weekly patterns
  • Different host populations
  • Different number of addresses
  • Over-representation of certain prefixes

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RQ II: How biased are address sources for IPv6 hitlists?

IPv6 hitlist passive sources: new IPv6 addresses per day

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6 Date 10 20 30 40 50 60 70 80 90 100 % of unique IPs per day that are new Weekend Weekend Weekend Weekend 10 20 30 40 50 60 70 80 90 100

IXP MWN

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RQ II: How biased are address sources for IPv6 hitlists?

IPv6 hitlist passive sources: new IPv6 addresses per day

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6 Date 10 20 30 40 50 60 70 80 90 100 % of unique IPs per day that are new Weekend Weekend Weekend Weekend 10 20 30 40 50 60 70 80 90 100

IXP MWN

  • Large share of new addresses each day hints at privacy extensions

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RQ II: How biased are address sources for IPv6 hitlists?

IPv6 hitlist passive vs. active sources: Hamming weight distribution

2 4 6 8 10 40 42

N (31.5, 15.75)

Frequency [%] 10 20 30 40 50 60 Number of IID bits set to '1' (IXP)

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RQ II: How biased are address sources for IPv6 hitlists?

IPv6 hitlist passive vs. active sources: Hamming weight distribution

2 4 6 8 10 40 42

N (31.5, 15.75)

Frequency [%] 10 20 30 40 50 60 Number of IID bits set to '1' (IXP)

N (31.5, 15.75)

Number of IID bits set to '1' (Traceroute) 2 4 6 8 10 40 42 Frequency [%] 10 20 30 40 50 60

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RQ II: How biased are address sources for IPv6 hitlists?

IPv6 hitlist passive vs. active sources: Hamming weight distribution

2 4 6 8 10 40 42

N (31.5, 15.75)

Frequency [%] 10 20 30 40 50 60 Number of IID bits set to '1' (IXP)

N (31.5, 15.75)

Number of IID bits set to '1' (Traceroute) 2 4 6 8 10 40 42 Frequency [%] 10 20 30 40 50 60

  • Different host populations: clients at IXP (privacy extensions) vs. routers (manually as-

signed addresses)

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RQ II: How biased are address sources for IPv6 hitlists?

IPv6 hitlist active sources: Cumulative address runup

Domainlists DNS ANY CT AXFR Bitnodes RIPE Atlas Traceroute 60 M 50 M 40 M 30 M 10 M 20 M 2 1 7

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RQ II: How biased are address sources for IPv6 hitlists?

IPv6 hitlist active sources: Cumulative address runup

Domainlists DNS ANY CT AXFR Bitnodes RIPE Atlas Traceroute 60 M 50 M 40 M 30 M 10 M 20 M 2 1 7

  • 8

2 1 7

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  • Many addresses from domainlists, CT, and traceroutes
  • Rapid increase of traceroute addresses due to CPE routers

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RQ II: How biased are address sources for IPv6 hitlists?

Taxonomy

  • Alias: another address of the same host
  • Aliased prefix: whole prefix bound to the same host
  • Bias: some hosts overrepresented due to aliased prefixes

2001:0db8:0407:8000::/64

2001:0db8:0407:8000: 0 151:2900:77e9:03a8 2001:0db8:0407:8000: 1 5ab:3855:92a0:2341 2001:0db8:0407:8000: e aae:cb10:9321:ba76 2001:0db8:0407:8000: f 693:2443:915e:1d2e 16 branches (random IPs)

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RQ II: How biased are address sources for IPv6 hitlists?

Taxonomy

  • Alias: another address of the same host
  • Aliased prefix: whole prefix bound to the same host
  • Bias: some hosts overrepresented due to aliased prefixes

Aliased prefix detection

2001:0db8:0407:8000::/64

2001:0db8:0407:8000: 0 151:2900:77e9:03a8 2001:0db8:0407:8000: 1 5ab:3855:92a0:2341 2001:0db8:0407:8000: e aae:cb10:9321:ba76 2001:0db8:0407:8000: f 693:2443:915e:1d2e 16 branches (random IPs)

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RQ II: How biased are address sources for IPv6 hitlists?

Detected aliased prefixes

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RQ II: How biased are address sources for IPv6 hitlists?

Detected aliased prefixes

  • Only 3.2 % of prefixes are aliased
  • But 46.6 % of addresses are in aliased prefixes → bias

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RQ II: How biased are address sources for IPv6 hitlists?

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RQ II: How biased are address sources for IPv6 hitlists?

  • Daily publication
  • Responsive IPv6 addresses for 5 protocol-port combinations
  • Aliased and non-aliased IPv6 prefixes
  • Dozens of fellow researchers have access

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RQ II: How biased are address sources for IPv6 hitlists?

Summary

  • Identified different types of biases in IPv6 hitlist sources
  • Distort targets by almost 50 %
  • Biases can be detected
  • IPv6 Hitlist Service provides fellow researchers with access to daily IPv6 address data

Publications (this research question)

  • Oliver Gasser, Quirin Scheitle, Pawel Foremski, Qasim Lone, Maciej Korczynski, Stephen D. Strowes, Luuk Hendriks, and Georg Carle, “Clusters

in the Expanse: Understanding and Unbiasing IPv6 Hitlists”, IMC’18.

  • Oliver Gasser, Quirin Scheitle, Sebastian Gebhard, and Georg Carle, “Scanning the IPv6 Internet: Towards a Comprehensive Hitlist”, TMA’16.

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Research questions

RQ I: How can we perform Internet-scale IPv6 measurements? Chapter 3 ZMapv6 goscanner RQ II: How biased are address sources for IPv6 hitlists? Chapter 4 Passive sources Active sources Biases in sources IPv6 Hitlist Service RQ III: Are HTTPS servers still vulnerable to MitM attacks? Chapter 5 Certificate security HTTPS security RQ IV: Are BACnet devices vulnerable to amplification attacks? Chapter 6 Deployment Amplification Notification RQ V: Are IPMI devices vulnerable to MitM attacks? Chapter 7 Deployment TLS security

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

Motivation

  • HTTPS ecosystem experienced many security issues which allow for MitM attacks (e.g.,

misissued certificates, weak keys, CA breaches)

  • A number of HTTPS security extensions have been proposed to make the HTTPS ecosys-

tem more secure

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

Motivation

  • HTTPS ecosystem experienced many security issues which allow for MitM attacks (e.g.,

misissued certificates, weak keys, CA breaches)

  • A number of HTTPS security extensions have been proposed to make the HTTPS ecosys-

tem more secure Measurements & analyses

  • Active measurements
  • Empirical analysis of different HTTPS ecosystem weaknesses
  • Insecure certificates
  • Downgrade from HTTPS to HTTP
  • Misissued certificates

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

Baseline Requirements (BRs)

  • Rules regarding certificates and issuing processes which CAs adhere to
  • Devised within the CA/Browser Forum
  • Each requirement has an enforcement date

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

Baseline Requirements (BRs)

  • Rules regarding certificates and issuing processes which CAs adhere to
  • Devised within the CA/Browser Forum
  • Each requirement has an enforcement date

Analyze BR adherence of all certificates in Certificate Transparency (CT) logs

  • Must not use 1024 bit keys
  • Must not use SHA-1 signature algorithm
  • Must contain SAN in addition to CN

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

BR violations of certificates in CT logs

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Time 101 102 103 104 105 106 107 108 Valid CT certificates at time 1024-bit RSA keys SHA-1 sig. alg. Only CN, no SAN

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

BR violations of certificates in CT logs

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Time 101 102 103 104 105 106 107 108 Valid CT certificates at time 1024-bit RSA keys SHA-1 sig. alg. Only CN, no SAN

  • Enforcement of stricter rules helps curb the number of insecure certificates
  • But: Many valid insecure certificates are found in CT logs

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

HTTP Strict Transport Security (HSTS) deployment

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

HTTP Strict Transport Security (HSTS) deployment

  • Significant usage among top domains
  • Preloading highly used among top domains, smaller usage among general population

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

HTTP Public Key Pinning (HPKP) deployment

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

HTTP Public Key Pinning (HPKP) deployment

  • Low usage among general population
  • High usage through preloading among top domains

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RQ III: Are HTTPS servers still vulnerable to MitM attacks?

Summary

  • Thousands of insecure certificates are still valid
  • High usage of HSTS and HPKP among top domains, mostly due to preloading
  • Insecure certificates and lack of HTTPS security techniques make hosts vulnerable to

Man-in-the-Middle attacks

Publications (this research question)

  • Oliver Gasser, Benjamin Hof, Max Helm, Maciej Korczynski, Ralph Holz, and Georg Carle, “In Log We Trust: Revealing

Poor Security Practices with Certificate Transparency Logs and Internet Measurements”, PAM’18.

  • Quirin Scheitle, Oliver Gasser, Theodor Nolte, Johanna Amann, Lexi Brent, Georg Carle, Ralph Holz, Thomas C.

Schmidt, and Matthias Wählisch, “The Rise of Certificate Transparency and Its Implications on the Internet Ecosystem”, IMC’18.

  • Johanna Amann, Oliver Gasser, Quirin Scheitle, Lexi Brent, Georg Carle, and Ralph Holz, “Mission Accomplished?

HTTPS Security after DigiNotar”, IMC’17.

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Comparison to related work

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Comparison to related work

Holz (2014) [8] Durumeric (2017) [2] Fiebig (2017) [3] Hendriks (2019) [7] IPv6 measurements ✗ ✗ ✓ ✓ Bias analyses ✗ ✗ ✓ ✗ HTTPS security analyses ✓ ✓ ✗ ✗ Reproducibility efforts ✗ ✗ ✓ ✗ Measurement service ✗ ✓ ✗ ✗

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Comparison to related work

Holz (2014) [8] Durumeric (2017) [2] Fiebig (2017) [3] Hendriks (2019) [7] This dissertation IPv6 measurements ✗ ✗ ✓ ✓ ✓ Bias analyses ✗ ✗ ✓ ✗ ✓ HTTPS security analyses ✓ ✓ ✗ ✗ ✓ Reproducibility efforts ✗ ✗ ✓ ✗ ✓ Measurement service ✗ ✓ ✗ ✗ ✓

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Key contributions

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Key contributions

  • Internet measurement methodology
  • Largest IPv6 hitlist to date
  • Extensive bias analyses in hitlist sources
  • IPv6 Hitlist Service
  • HTTPS security
  • Thousands of insecure certificates
  • Millions of domains lacking HTTPS security extensions
  • Man-in-the-Middle attacks still possible

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Key contributions

  • Internet measurement methodology
  • Largest IPv6 hitlist to date
  • Extensive bias analyses in hitlist sources
  • IPv6 Hitlist Service
  • HTTPS security
  • Thousands of insecure certificates
  • Millions of domains lacking HTTPS security extensions
  • Man-in-the-Middle attacks still possible

Publications (this talk)

  • Oliver Gasser, Benjamin Hof, Max Helm, Maciej Korczynski, Ralph Holz, and Georg Carle, “In Log We Trust: Revealing Poor Security Practices

with Certificate Transparency Logs and Internet Measurements”, PAM’18. Best Paper Award.

  • Oliver Gasser, Quirin Scheitle, Pawel Foremski, Qasim Lone, Maciej Korczynski, Stephen D. Strowes, Luuk Hendriks, and Georg Carle, “Clusters

in the Expanse: Understanding and Unbiasing IPv6 Hitlists”, IMC’18.

  • Quirin Scheitle, Oliver Gasser, Theodor Nolte, Johanna Amann, Lexi Brent, Georg Carle, Ralph Holz, Thomas C. Schmidt, and Matthias Wäh-

lisch, “The Rise of Certificate Transparency and Its Implications on the Internet Ecosystem”, IMC’18.

  • Johanna Amann, Oliver Gasser, Quirin Scheitle, Lexi Brent, Georg Carle, and Ralph Holz, “Mission Accomplished? HTTPS Security after

DigiNotar”, IMC’17. Community Contribution Award, IRTF Applied Networking Research Prize.

  • Oliver Gasser, Quirin Scheitle, Sebastian Gebhard, and Georg Carle, “Scanning the IPv6 Internet: Towards a Comprehensive Hitlist”, TMA’16.

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Bibliography

[1] Johanna Amann, Oliver Gasser, Quirin Scheitle, Lexi Brent, Georg Carle, and Ralph Holz. “Mission Accomplished? HTTPS Security after DigiNotar”. In: IMC’17. Community Contribution Award, IRTF Applied Networking Research Prize. ACM. London, United Kingdom, Nov. 2017, pp. 325–340. [2] Zakir Durumeric. “Fast Internet-Wide Scanning: A New Security Perspective”. PhD thesis. University

  • f Michigan, 2017.

[3] Tobias Fiebig. “An Empirical Evaluation of Misconfiguration in Internet Services”. PhD thesis. Technische Universität Berlin, 2017. [4] Oliver Gasser, Benjamin Hof, Max Helm, Maciej Korczynski, Ralph Holz, and Georg Carle. “In Log We Trust: Revealing Poor Security Practices with Certificate Transparency Logs and Internet Measurements”. In: PAM’18. Best Paper Award. Springer. Berlin, Germany, Mar. 2018, pp. 173–185. [5] Oliver Gasser, Quirin Scheitle, Pawel Foremski, Qasim Lone, Maciej Korczynski, Stephen D. Strowes, Luuk Hendriks, and Georg Carle. “Clusters in the Expanse: Understanding and Unbiasing IPv6 Hitlists”. In: IMC’18. ACM. Boston, MA, USA, Nov. 2018. DOI: 10.1145/3278532.3278564. [6] Oliver Gasser, Quirin Scheitle, Sebastian Gebhard, and Georg Carle. “Scanning the IPv6 Internet: Towards a Comprehensive Hitlist”. In: TMA’16. IFIP. Louvain-la-Neuve, Belgium, Apr. 2016. [7] Luuk Hendriks. “Measuring IPv6 Resilience and Security”. PhD thesis. University of Twente, 2019. [8] Ralph-Günther Holz. “Empirical Analysis of Public Key Infrastructures and Investigation of Improvements”. PhD thesis. Technical University of Munich, 2014.

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Bibliography

[9] IMC’18. ACM. Boston, MA, USA, Nov. 2018. [10] Quirin Scheitle, Oliver Gasser, Theodor Nolte, Johanna Amann, Lexi Brent, Georg Carle, Ralph Holz, Thomas C. Schmidt, and Matthias Wählisch. “The Rise of Certificate Transparency and Its Implications on the Internet Ecosystem”. In: IMC’18. ACM. Boston, MA, USA, Nov. 2018,

  • pp. 343–349. ISBN: 978-1-4503-5619-0. DOI: 10.1145/3278532.3278562.

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