At AWS, we have begun using automated mathematical proof search methods to automate compliance certification. Our approach uses automated mathematical proof tools to find arguments that express, in a repeatable precise way, what controls are used, and why and how they are correctly implemented. In this chalk talk, learn how auditors can independently validate design and operating effectiveness using open-source and community-validated tools. This validation approach provides evidence of the operating effectiveness of a control at all times, for all operations. This approach can reduce costs and takes the time spent achieving compliance certification from months to seconds. This approach can also remove ambiguity from what it means to be compliant with a particular control.

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Automating Compliance Certification
With Automated Mathematical Proof
Chad Woolf
Vice President,
AWS Security
S E C 3 3 0
Byron Cook
Director,
AWS Automated Reasoning
Tom McAndrew
CEO
Coalfire

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The auditor’s challenge
Complexity Evidence reliance
Efficiency Increasing assurance

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Today: Assuring characteristics of a system
Narrowed to describing the “control environment”
Narrative based
Automated controls – preventative and detective
Population sampling
Manual controls, written policies, culture

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Intro to automated reasoning
• Mathematic proofs
• Proving a system condition

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Automated reasoning
Applied to security controls
• Method of generation – system versus manual –
Mathematically-based proof
• Completeness of coverage and scope –Evaluation of all
behaviors of system enables more accurate inference of
compliance than assessments of snippets of code.
• Frequency of generation – Handle greater evaluation
frequency that is closer to real-time.
• Source of evidence – Objectivity of the evidence.
• Type of evidence – reliability of evidence increases
depending upon the type of evidence.

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New assurance methods
Semantics-based reasoning about different aspects of AWS services,
such as AWS Identity and Access Management (IAM) policies, can infer
new insight about the compliance of those services using Zelkova, Tiros,
and the Checker Framework.

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Case studies
Encryption of data at rest
Use Checker Framework during build process to generate
proof that services integrated with KMS use 256-bit
length keys to meet the audit objective:
“Is this AWS service using strong encryption at all times?”

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Case studies
Data privacy compliance
Use Zelkova as a method to reason about
policies that govern access to resources and
generate evidence

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Case studies
Network access compliance
Use Tiros as a method of generating evidence by
evaluation of all possible network connections

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More Information about Provable Security
https://aws.amazon.com/security/provable-security/

14. Thank you!
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