This document discusses using formal specification techniques like UML, Alloy, and Prolog to discover design flaws related to application and website security. It provides examples of how these techniques can be used to find issues with input validation, data flow, and access control by modeling the system and its requirements. Formal modeling allows exploring complex behaviors and edge cases that may lead to security vulnerabilities. The document advocates applying a "cocktail" of different modeling approaches to more thoroughly test for flaws during design.
This document provides an overview of dependability and dependable systems. It defines dependability as an umbrella term that includes reliability, availability, maintainability, and other attributes that allow systems to be trusted. Dependability addresses how systems can continue operating correctly even when faults occur. Key topics covered include fault tolerance techniques, error processing, failure modes, and modeling approaches for analyzing dependability. The goal of the course is to understand how to design systems that can be relied upon to deliver their services as specified, even in the presence of faults or unexpected events.
This document provides information about fault tolerance and discusses different approaches to building fault tolerant systems from unreliable components. It begins with an overview of fault tolerance principles like error detection, correction and stopping propagation. It then covers hardware fault tolerance using redundancy, as well as early software approaches like Tandem's nonstop systems. The document discusses the challenges of building reliable software and strategies like defensive programming, process supervision and restarting processes on error. It emphasizes that failure assumptions must be specified and provides a demonstration of error detection in Erlang.
Fault-tolerant computer systems are designed to continue operating properly even when some components fail. They achieve this through techniques like redundancy, where backup components take over if primary components fail. The document discusses the goals of fault tolerance like ensuring no single point of failure. It provides examples of how fault tolerance is implemented in areas like data storage and outlines techniques used to design and evaluate fault-tolerant systems.
This document discusses fault tolerance in computing systems. It defines fault tolerance as building systems that can continue operating satisfactorily even in the presence of faults. It describes different types of faults like transient, intermittent, and permanent hardware faults. It also discusses concepts like errors, failures, fault taxonomy, attributes of fault tolerance like availability and reliability. It explains various techniques used for fault tolerance like error detection, system recovery, fault masking, and redundancy.
The document discusses faults, errors, and failures in systems. A fault is a defect, an error is unexpected behavior, and a failure occurs when specifications are not met. Fault tolerance allows a system to continue operating despite errors. Fault tolerant systems are gracefully degradable and aim to ensure small failure probabilities. Faults can be hardware or software issues. Various failure types and objectives of fault tolerance like availability and reliability are also described.
The document discusses various types of faults in distributed systems including transient, intermittent, and permanent faults. It describes approaches to achieving fault tolerance through redundancy of information, time, and physical components. The document also discusses active replication using triple modular redundancy and the primary backup approach. It introduces the two army problem and Byzantine Generals problem regarding reaching agreement in faulty systems and solutions requiring multiple participants and message rounds.
Distributed Middleware Reliability & Fault Tolerance Support in System SHarini Sirisena
The document discusses techniques for building reliable large-scale distributed systems. It describes how System S achieves reliability through two key building blocks - an inter-component communication infrastructure that handles failures and remote procedure calls, and a data storage mechanism. System S uses CORBA for communication and IBM DB2 for data storage. It also discusses how System S handles component failures through retrying operations, managing component state, and ensuring idempotent and non-idempotent operations are executed correctly.
This document provides an overview of dependability and dependable systems. It defines dependability as an umbrella term that includes reliability, availability, maintainability, and other attributes that allow systems to be trusted. Dependability addresses how systems can continue operating correctly even when faults occur. Key topics covered include fault tolerance techniques, error processing, failure modes, and modeling approaches for analyzing dependability. The goal of the course is to understand how to design systems that can be relied upon to deliver their services as specified, even in the presence of faults or unexpected events.
This document provides information about fault tolerance and discusses different approaches to building fault tolerant systems from unreliable components. It begins with an overview of fault tolerance principles like error detection, correction and stopping propagation. It then covers hardware fault tolerance using redundancy, as well as early software approaches like Tandem's nonstop systems. The document discusses the challenges of building reliable software and strategies like defensive programming, process supervision and restarting processes on error. It emphasizes that failure assumptions must be specified and provides a demonstration of error detection in Erlang.
Fault-tolerant computer systems are designed to continue operating properly even when some components fail. They achieve this through techniques like redundancy, where backup components take over if primary components fail. The document discusses the goals of fault tolerance like ensuring no single point of failure. It provides examples of how fault tolerance is implemented in areas like data storage and outlines techniques used to design and evaluate fault-tolerant systems.
This document discusses fault tolerance in computing systems. It defines fault tolerance as building systems that can continue operating satisfactorily even in the presence of faults. It describes different types of faults like transient, intermittent, and permanent hardware faults. It also discusses concepts like errors, failures, fault taxonomy, attributes of fault tolerance like availability and reliability. It explains various techniques used for fault tolerance like error detection, system recovery, fault masking, and redundancy.
The document discusses faults, errors, and failures in systems. A fault is a defect, an error is unexpected behavior, and a failure occurs when specifications are not met. Fault tolerance allows a system to continue operating despite errors. Fault tolerant systems are gracefully degradable and aim to ensure small failure probabilities. Faults can be hardware or software issues. Various failure types and objectives of fault tolerance like availability and reliability are also described.
The document discusses various types of faults in distributed systems including transient, intermittent, and permanent faults. It describes approaches to achieving fault tolerance through redundancy of information, time, and physical components. The document also discusses active replication using triple modular redundancy and the primary backup approach. It introduces the two army problem and Byzantine Generals problem regarding reaching agreement in faulty systems and solutions requiring multiple participants and message rounds.
Distributed Middleware Reliability & Fault Tolerance Support in System SHarini Sirisena
The document discusses techniques for building reliable large-scale distributed systems. It describes how System S achieves reliability through two key building blocks - an inter-component communication infrastructure that handles failures and remote procedure calls, and a data storage mechanism. System S uses CORBA for communication and IBM DB2 for data storage. It also discusses how System S handles component failures through retrying operations, managing component state, and ensuring idempotent and non-idempotent operations are executed correctly.
Software Security (Vulnerabilities) And Physical SecurityNicholas Davis
The document discusses various types of software vulnerabilities including:
1. Vulnerabilities can result from weak passwords, software bugs, viruses, or insecure user input.
2. Common causes of vulnerabilities are password management flaws, operating system design flaws, software bugs, and unchecked user input.
3. There is debate around how vulnerabilities should be disclosed, with options including full disclosure, responsible disclosure, and limited disclosure.
This document introduces a simplified model for software reliability engineering (SRE). It outlines three phases: error introduction during development, defect identification during testing, and failure manifestation during operation. For each phase, it identifies key influencing factors and proposes potential measures and metrics to assess those factors, such as design complexity, code coverage, and how thoroughly contexts of use are considered. The goal is to provide a standardized yet practical approach to SRE.
Distributed Systems: scalability and high availabilityRenato Lucindo
Distributed systems use multiple computers that interact over a network to achieve common goals like scalability and high availability. They work to handle increasing loads by either scaling up individual nodes or scaling out by adding more nodes. However, distributed systems face challenges in maintaining consistency, availability, and partition tolerance as defined by the CAP theorem. Techniques like caching, queues, logging, and understanding failure modes can help address these challenges.
Architecting for the cloud storage build testLen Bass
This document discusses best practices for deploying applications to the cloud, including:
- Using a deployment pipeline with continuous integration, integration testing, and staging environments to minimize errors and delays.
- Managing versions and branches to prevent errors from multiple teams working simultaneously.
- Performing integration testing after each commit to catch errors early.
- Maintaining separate databases for different environments like test vs production.
- Using feature toggles to allow uncompleted code to be checked in without breaking builds.
- Performing staging tests using production data and load to thoroughly test before deployment.
This document provides an overview of an Operating Systems I course, including course details, textbooks, prerequisites, grading, and an overview of computer system concepts. The computer system concepts section covers processors, memory, I/O devices, registers, instruction execution, interrupts, and the interrupt cycle. It describes the basic components and functions of an operating system at a high level.
Socio-technical systems include technical components like hardware and software as well as human users and operational processes. They are purposefully designed to achieve organizational goals. Emergent properties are characteristics of the whole system that cannot be predicted from its parts alone, such as reliability, safety, and security. Legacy systems are old socio-technical systems still in use that rely on obsolete technologies and constrain modern business processes.
The document discusses the top 10 vulnerabilities of databases. The most common is deployment failures where databases are not properly secured when deployed. Other vulnerabilities include broken authentication that allows worms like SQL Slammer to spread rapidly; data leaks through unencrypted network traffic; stolen backups; abuse of standard database features; lack of access controls; SQL injections; weak key management; and inconsistent security practices. Proper configuration such as encrypted connections, access control, and regular patching can help address many of these issues.
Software security (vulnerabilities) and physical securityNicholas Davis
The document discusses various types of software vulnerabilities including:
1. Vulnerabilities can result from weak passwords, software bugs, viruses, or insecure user input.
2. Common causes of vulnerabilities are password management flaws, operating system design flaws, software bugs, and unchecked user input.
3. There is debate around how vulnerabilities should be disclosed, with options including full disclosure, responsible disclosure, and limited disclosure.
CNIT 123: 8: Desktop and Server OS VulnerabilitesSam Bowne
Slides for a college course based on "Hands-On Ethical Hacking and Network Defense, Second Edition by Michael T. Simpson, Kent Backman, and James Corley -- ISBN: 1133935613
Teacher: Sam Bowne
Twitter: @sambowne
Website: https://samsclass.info/123/123_F16.shtml
For a college class in Ethical Hacking and Network Defense at CCSF, by Sam Bowne. More info at https://samsclass.info/123/123_F17.shtml
Based on this book
Hands-On Ethical Hacking and Network Defense, Third Edition by Michael T. Simpson, Kent Backman, and James Corley -- ISBN: 9781285454610
A distributed system is a collection of independent computers that appears as a single coherent system to users. Key properties include concurrency across multiple cores and hosts, lack of a global clock, and independent failures of nodes. There are many challenges in building distributed systems including performance, concurrency, failures, scalability, and transparency. Common approaches to address these include virtual clocks, group communication, failure detection, transaction protocols, redundancy, and middleware. Distributed systems must be carefully engineered to balance competing design tradeoffs.
CNIT 123 8: Desktop and Server OS VulnerabilitiesSam Bowne
For a college class in Ethical Hacking and Network Defense at CCSF, by Sam Bowne. More info at https://samsclass.info/123/123_S18.shtml
Based on this book
Hands-On Ethical Hacking and Network Defense, Third Edition by Michael T. Simpson, Kent Backman, and James Corley -- ISBN: 9781285454610
Ch 8: Desktop and Server OS VulnerabilitesSam Bowne
Slides for a college course at City College San Francisco. Based on "Hands-On Ethical Hacking and Network Defense, Third Edition" by Michael T. Simpson, Kent Backman, and James Corley -- ISBN: 9781285454610.
Instructor: Sam Bowne
Class website: https://samsclass.info/123/123_S17.shtml
The document discusses fuzzing techniques for finding software vulnerabilities. It defines fuzzing as automatically feeding malformed data to a program to trigger flaws. It describes generating fuzzed test cases, delivering them to targets, and monitoring for crashes. The document outlines dumb and smart fuzzing approaches, and steps for basic fuzzing like generating test cases, monitoring targets, and determining exploitability of found issues.
How we breach small and medium enterprises (SMEs)NCC Group
This document summarizes common techniques used to breach small and medium enterprises. It discusses how networks are typically assessed through discovery, vulnerability assessment, exploitation, and post-exploitation. It then outlines several weaknesses that are commonly leveraged, including lack of security patches, default credentials, excessive network footprint, lack of network segregation, exceptions in configurations, and failure to implement whitelisting over blacklisting. Specific scenarios are provided for each to illustrate how access can be gained and privilege escalated within a network. The document stresses the importance of security fundamentals like patching, access control, and network segmentation.
This webcast's agenda is:
1. Introduction to the OWASP Top TEN.
2. How to integrate the OWASP Top Ten in your SDLC.
3. How the OWASP Top Ten maps to compliance, standards and other drivers.
An Eirtight internal presentation by our chief solution architect Leointin Birsan (Lusu the ghost). It is designed to help our team refocus on the importance of bearing in mind security when writing code.
This document discusses data intensive applications and some of the challenges, tools, and best practices related to them. The key challenges with data intensive applications include large quantities of data, complex data structures, and rapidly changing data. Common tools mentioned include NoSQL databases, message queues, caches, search indexes, and batch/stream processing frameworks. The document also discusses concepts like distributed systems architectures, outage case studies, and strategies for improving reliability, scalability, and maintainability in data systems. Engineers working in this field need an accurate understanding of various tools and how to apply the right tools for different use cases while avoiding common pitfalls.
Unit 2 - Chapter 7 (Database Security).pptxSakshiGawde6
This document discusses database security concepts. It explains that databases store sensitive organizational data so security is important. It describes database security layers including server, network, operating system, data encryption, and database levels. Database security involves balancing access for users' jobs with restricting sensitive data. Permissions at each level control what users can access.
Software Security (Vulnerabilities) And Physical SecurityNicholas Davis
The document discusses various types of software vulnerabilities including:
1. Vulnerabilities can result from weak passwords, software bugs, viruses, or insecure user input.
2. Common causes of vulnerabilities are password management flaws, operating system design flaws, software bugs, and unchecked user input.
3. There is debate around how vulnerabilities should be disclosed, with options including full disclosure, responsible disclosure, and limited disclosure.
This document introduces a simplified model for software reliability engineering (SRE). It outlines three phases: error introduction during development, defect identification during testing, and failure manifestation during operation. For each phase, it identifies key influencing factors and proposes potential measures and metrics to assess those factors, such as design complexity, code coverage, and how thoroughly contexts of use are considered. The goal is to provide a standardized yet practical approach to SRE.
Distributed Systems: scalability and high availabilityRenato Lucindo
Distributed systems use multiple computers that interact over a network to achieve common goals like scalability and high availability. They work to handle increasing loads by either scaling up individual nodes or scaling out by adding more nodes. However, distributed systems face challenges in maintaining consistency, availability, and partition tolerance as defined by the CAP theorem. Techniques like caching, queues, logging, and understanding failure modes can help address these challenges.
Architecting for the cloud storage build testLen Bass
This document discusses best practices for deploying applications to the cloud, including:
- Using a deployment pipeline with continuous integration, integration testing, and staging environments to minimize errors and delays.
- Managing versions and branches to prevent errors from multiple teams working simultaneously.
- Performing integration testing after each commit to catch errors early.
- Maintaining separate databases for different environments like test vs production.
- Using feature toggles to allow uncompleted code to be checked in without breaking builds.
- Performing staging tests using production data and load to thoroughly test before deployment.
This document provides an overview of an Operating Systems I course, including course details, textbooks, prerequisites, grading, and an overview of computer system concepts. The computer system concepts section covers processors, memory, I/O devices, registers, instruction execution, interrupts, and the interrupt cycle. It describes the basic components and functions of an operating system at a high level.
Socio-technical systems include technical components like hardware and software as well as human users and operational processes. They are purposefully designed to achieve organizational goals. Emergent properties are characteristics of the whole system that cannot be predicted from its parts alone, such as reliability, safety, and security. Legacy systems are old socio-technical systems still in use that rely on obsolete technologies and constrain modern business processes.
The document discusses the top 10 vulnerabilities of databases. The most common is deployment failures where databases are not properly secured when deployed. Other vulnerabilities include broken authentication that allows worms like SQL Slammer to spread rapidly; data leaks through unencrypted network traffic; stolen backups; abuse of standard database features; lack of access controls; SQL injections; weak key management; and inconsistent security practices. Proper configuration such as encrypted connections, access control, and regular patching can help address many of these issues.
Software security (vulnerabilities) and physical securityNicholas Davis
The document discusses various types of software vulnerabilities including:
1. Vulnerabilities can result from weak passwords, software bugs, viruses, or insecure user input.
2. Common causes of vulnerabilities are password management flaws, operating system design flaws, software bugs, and unchecked user input.
3. There is debate around how vulnerabilities should be disclosed, with options including full disclosure, responsible disclosure, and limited disclosure.
CNIT 123: 8: Desktop and Server OS VulnerabilitesSam Bowne
Slides for a college course based on "Hands-On Ethical Hacking and Network Defense, Second Edition by Michael T. Simpson, Kent Backman, and James Corley -- ISBN: 1133935613
Teacher: Sam Bowne
Twitter: @sambowne
Website: https://samsclass.info/123/123_F16.shtml
For a college class in Ethical Hacking and Network Defense at CCSF, by Sam Bowne. More info at https://samsclass.info/123/123_F17.shtml
Based on this book
Hands-On Ethical Hacking and Network Defense, Third Edition by Michael T. Simpson, Kent Backman, and James Corley -- ISBN: 9781285454610
A distributed system is a collection of independent computers that appears as a single coherent system to users. Key properties include concurrency across multiple cores and hosts, lack of a global clock, and independent failures of nodes. There are many challenges in building distributed systems including performance, concurrency, failures, scalability, and transparency. Common approaches to address these include virtual clocks, group communication, failure detection, transaction protocols, redundancy, and middleware. Distributed systems must be carefully engineered to balance competing design tradeoffs.
CNIT 123 8: Desktop and Server OS VulnerabilitiesSam Bowne
For a college class in Ethical Hacking and Network Defense at CCSF, by Sam Bowne. More info at https://samsclass.info/123/123_S18.shtml
Based on this book
Hands-On Ethical Hacking and Network Defense, Third Edition by Michael T. Simpson, Kent Backman, and James Corley -- ISBN: 9781285454610
Ch 8: Desktop and Server OS VulnerabilitesSam Bowne
Slides for a college course at City College San Francisco. Based on "Hands-On Ethical Hacking and Network Defense, Third Edition" by Michael T. Simpson, Kent Backman, and James Corley -- ISBN: 9781285454610.
Instructor: Sam Bowne
Class website: https://samsclass.info/123/123_S17.shtml
The document discusses fuzzing techniques for finding software vulnerabilities. It defines fuzzing as automatically feeding malformed data to a program to trigger flaws. It describes generating fuzzed test cases, delivering them to targets, and monitoring for crashes. The document outlines dumb and smart fuzzing approaches, and steps for basic fuzzing like generating test cases, monitoring targets, and determining exploitability of found issues.
How we breach small and medium enterprises (SMEs)NCC Group
This document summarizes common techniques used to breach small and medium enterprises. It discusses how networks are typically assessed through discovery, vulnerability assessment, exploitation, and post-exploitation. It then outlines several weaknesses that are commonly leveraged, including lack of security patches, default credentials, excessive network footprint, lack of network segregation, exceptions in configurations, and failure to implement whitelisting over blacklisting. Specific scenarios are provided for each to illustrate how access can be gained and privilege escalated within a network. The document stresses the importance of security fundamentals like patching, access control, and network segmentation.
This webcast's agenda is:
1. Introduction to the OWASP Top TEN.
2. How to integrate the OWASP Top Ten in your SDLC.
3. How the OWASP Top Ten maps to compliance, standards and other drivers.
An Eirtight internal presentation by our chief solution architect Leointin Birsan (Lusu the ghost). It is designed to help our team refocus on the importance of bearing in mind security when writing code.
This document discusses data intensive applications and some of the challenges, tools, and best practices related to them. The key challenges with data intensive applications include large quantities of data, complex data structures, and rapidly changing data. Common tools mentioned include NoSQL databases, message queues, caches, search indexes, and batch/stream processing frameworks. The document also discusses concepts like distributed systems architectures, outage case studies, and strategies for improving reliability, scalability, and maintainability in data systems. Engineers working in this field need an accurate understanding of various tools and how to apply the right tools for different use cases while avoiding common pitfalls.
Unit 2 - Chapter 7 (Database Security).pptxSakshiGawde6
This document discusses database security concepts. It explains that databases store sensitive organizational data so security is important. It describes database security layers including server, network, operating system, data encryption, and database levels. Database security involves balancing access for users' jobs with restricting sensitive data. Permissions at each level control what users can access.
Describes a model to analyze software systems and determine areas of risk. Discusses limitations of typical test design methods and provides an example of how to use the model to create high volume automated testing framework.
Test Strategies for Conventional Software, Unit Testing, Targets for Unit Test Cases, Common Computational Errors in Execution Paths, Other Errors to Uncover, Problems to uncover in Error Handling, Drivers and Stubs for Unit Testing, Fundamentals of Software Engineering
This document provides a guide for testing the back end of SQL databases. It discusses why back end testing is important, different testing phases and methods. It outlines tests for various structural aspects like database schema, stored procedures, triggers, and integration. Functional testing is also described, including checking data integrity, security, performance, and interfaces. Nightly processes, tools, and other test issues are covered as well. The goal is to provide testers a comprehensive approach to thoroughly testing the back end.
This lecture discusses principles of secure coding and lessons learned from past security incidents. It covers topics like:
- Design principles like least privilege and complete mediation.
- Common coding errors that led to vulnerabilities like buffer overflows.
- The importance of input validation, logging, and avoiding risky functions.
- Lessons from fuzz testing programs and the need for secure development practices.
- Authentication techniques like hashing passwords and limiting privileges.
- The role of policy, usability, and social aspects in security.
Illuminate - Performance Analystics driven by Machine LearningjClarity
illuminate is a machine learning-based performance analytics tool that automatically diagnoses performance issues in servers and applications without human intervention. It has a small memory, CPU, and network footprint, uses adaptive machine learning to interpret data and scale with applications, and provides a holistic view of both application and system performance across servers. illuminate identifies the largest bottlenecks through machine learning, aggregates similar issues across servers, and auto-triggers on SLA breaches. It supports Linux systems and has a secure web-based dashboard.
Similar to Application and Website Security -- Designer Edition:Using Formal Specification Techniques To Discover Design Flaws (20)
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Application and Website Security -- Designer Edition:Using Formal Specification Techniques To Discover Design Flaws
1. Application and Website Security –
Designer Edition:
Using Formal Specification Techniques To Discover
Design Flaws
Daniel Owens
IT Security Professional
3. Introduction
• Systems generally come in two forms – Single
Level Security Systems (SLSS) and Multilevel
Security Systems (MLSS)
– In an SLSS, the system processes information of the
same sensitivity or privilege level, ignoring the user’s
need-to-know and clearance, but still enforce access
controls
– In an MLSS, the system must take into account
sensitivity levels, privileges, need-to-know, clearance
levels, and enforce access controls
• This work is generalized enough to apply to both
4. Previous Works
• Many previous works have looked for specific
flaws in specific systems
– The works were never intended to be general, simply
to provide analysis of a specific flaw in a specific
system
– This means that much of the works available are
difficult to apply to current or more general problems
• Additionally, most works ignore that functional
and security flaws stem from the same issues
5. Common Root Causes
• Most flaws only become problems after the flaw or
data forged by the flaw has successfully passed
through multiple checkpoints
– Any of the checkpoints could have prevented the flaw
– There are instances, such as faulty subsystems upon which
the current software relies
• Even these can be tested for, but that becomes a never-ending and
very costly thing to do, so we assume that those we have no
choice but to rely on have been heavily tested
• There is no such thing as a strictly ‘security’ or strictly
functionality flaw
6. Common Root Causes (cont)
• In 1996, Alph1 [5] clearly showed how buffer overflows can
be used to escalate privileges and execute arbitrary code
on the victim
– Buffer overflows cause visible functionality problems too – most
notably, the software being overflowed into and the software
doing the overflow will likely crash, have inconsistent data, or
operate in an unintended fashion
• More recently, Watchfire [32]made public an exploitation
technique to use dangling pointers to execute arbitrary
code on the victim
– Dangling pointers may cause visible functionality problems too –
again, most notably, the software could crash, have inconsistent
data, or operate in an unintended fashion
7. Common Root Causes (cont)
• Even weak passwords, often regarded as strictly a
security problem can create undesirable functionality
flaws
– The Morris worm exploited weak passwords and caused a
substantial degradation of services
– Conficker, which exploited a Windows bug and weak passwords,
and many other worms rely on bugs and weak passwords
• Even the most seemingly benign flaws, like off-by-one
errors can cause disastrous security and functionality
flaws
– Such flaws can be exploited to execute arbitrary code, but also
can be triggered by mere use and cause the system to crash or
have degraded services [13][15][19]
9. Input Validation
• Input validation flaws arise when input (data egressing the
process or thread from a source outside of the process or
thread) is not properly verified and sanitized prior to use
– These include come buffer overflows, format string flaws,
integer overflows, SQL injection, LDAP injection, SMTP injection,
code injection, command injection, Cross-Site Scripting, and
many other problems
• Proper and complete design documentation can help stop
these
• The flaws can be discovered using a variety of different
techniques, but no single technique can stop them all, only
a ‘cocktail’
10. Finding Input Validation Flaws With
UML
• Many input validation flaws can be found
using UML diagrams and use case scenarios,
or can be protected against using well-crafted
OCL statements that are translated into code
during implementation
– This includes detecting or preventing certain
instances of injection attacks (SQL, XSS, command,
code, LDAP, SMTP, JSON, etc) and overflows
(buffer, off-by-one, etc)
11. UML Input Validation Example
• There is the potential that query could allow SQL injection
(DBHandler performs the Database handling), or that the user
could enter otherwise incorrectly formatted information
– OCL and supporting documentation comes into effect here
– context GUI
inv: query.matchesRegEx(“a-zA-Z0-9 ”) and query.size()<40
• Note that this requires an OCL extension be written that accepts regular
expressions
• This also forces the design team to clearly specify all data
12. Sidenote
• Regular expressions that dictate data content should be
whitelists, not blacklists
– Whitelists dictate what is allowed, blacklists dictate what is not
• All input should have OCL constraints that dictate the
allowable content (a whitelist) and the maximum (and
minimum in certain cases) size
– This helps to stop overflows and injection, as well as providing
carefully crafted and examined whitelists that conform to the
requirements, while providing input validation
• Of course if keywords and characters with special meaning
are in the whitelist, the input will have to be properly
escaped in the code – hard to convey in UML diagrams, but
pre conditions and invariants can be used to do this with
more OCL extensions
14. Data Flow
• Data flow flaws arise when data take paths that are
untrusted or can present various problems
– Many of these issues concern integrity and confidentiality
– The data may be modified while it traverses the less
trusted/untrusted path such that it causes problems – note
that such data should be examined prior to use
• Examples include traversing a hostile environment,
traversing faulty systems, and experiencing the data
loss that is normal in any environment
15. Data Flow (cont)
• It is extremely important to know data flow in
environments where there are levels of trust or in
MLSSs
– Most kernels implement a limited form of hierarchical
protection domains, or ‘protection rings’
• This prevents problems in outer rings from impacting the inner
ring (both functionality and security benefits)
• The military and systems requiring high fault tolerance benefit
• Limiting access points by having ‘gates’ can help
prevent or limit the scale of compromises, as well as
contain damage should a fault occur
16. Finding Data Flow Flaws With UML
• Certain data flow flaws can be exposed by
UML diagrams, but mostly in Use Case
diagrams
– This involves ensuring that data re-entering the
system has not be tampered with or is not
malicious (in some cases, both should be checked)
• This is similar to input validation, since the
data reentering the system is assumed to be
data from an external source
17. Use Case Data Flow Example
Use Case Number 1
Use Case Name Initial Data Distribution
Overview Follows the distribution of initial data in the distributed system
Type Primary
Actors Master (P0) and Slave Processors (P1-PN)
Properties
Performance O(n)
Security Data crosses system’s boundaries prior to use
Preconditions Other
All slaves are up and waiting for the master to communicate
Flow Main Flow:
1. Master prepares each matrix segment (one per slave)
2. Master sends each matrix segment to the responsible slave
3. Master enters waiting state pending responses
4. Slaves receive matrix segment
5. Slaves transmit go-ahead to master
18. Use Case Data Flow Example (cont.)
• What happens if the slaves never receive the matrix segments sent to
them?
– The master will wait forever
– This should be handled as an Alternate Flow in the Use Case
• What happens if some of the data in the matrix segment is lost or
modified?
– At best the result will be inaccurate
– At worst the slave may become compromised or crash, resulting in the master
waiting forever for the slave to respond
– This should be handled as subflows – the master should hash the matrix segment
and send the hash along with the segment
• The hash should also be encrypted or signed if the environment is hostile
• What if someone injects a slave response (affirmative or negative)?
– Perhaps random network chatter
– Perhaps a malefactor
– This should be handled as a subflow (if it is a concern) – the master and slave
should use encrypted channels or traffic
• All environments outside the software (the network and even the
system’s bus) should be assumed buggy/malicious in most cases
19. UML Data Flow Example
• Data flowing between the two packages (VideoLibrarySystem and Users)
should be protected
– This is easiest by providing ‘chokepoints’ – normally making a single class on each
side (frontend, backend, middleware, etc) that handles interprocess/internetwork
communication and protecting all methods in that class
• Classification should actually be placed in each package
– This not only serves to decouple the interface and backend, but also helps to serve
as another sanity check and reduce the likelihood of a fault in one package
effecting the other package
20. Finding Data Flow Flaws With Models
• UML cannot be easily used to find many of the more
complex data flow flaws
– Alloy, ORC, and SMV, as well as similar modeling languages
can find many of the more complex data flow flaws
• Examples include verifying that algorithms effectively protect
against or detect data tampering, spoofing, denial of service (to
the extent possible), and information disclosure
• More than anything, modeling can help to verify the
adequacy of controls, but (as a consequence) also
detect when the data flow could potentially expose the
system to threats
21. Alloy Data Flow Example
/** Program to verify enforcement of the x86 protection rings **/
abstract sig Ring{}
one sigRingZero, RingOne, RingTwo, RingThreeextends Ring{}
one sig Policy{order:Ring->Ring}
{order=(RingThree->RingTwo)+(RingTwo->RingOne)+(RingOne->RingZero)+(RingZero->Ring)+(RingOne->Ring)+
(RingTwo->RingTwo)+(RingTwo->RingThree)+(RingThree->RingThree)}
sig Program{onRing: one Ring}
sig State{programs: setProgram,connections: programs->programs}
{ -- Note that we are allowing programs to connect to themselves (this is common)
noprog: Program | prognot in programs -- Ensures all Programs are in our state
no progA, progB: Program | progA->progBin connections and progA.onRing->progB.onRingnot in Policy.order-- Enforce Policy.order
}
assert verifyDataFlow{all state: State | not getAnInvalidDataFlow[state]}
predgetAnInvalidDataFlow[state: State]{ -- Attempts to find an invalid data flow (one that violates Policy.order
some progA, progB: Program | progA->progBinstate.connectionsand progA.onRing->progB.onRingnot in Policy.order
}
• Models can be used to verify control of data flow
• They can also show that algorithms to protect or contain
damage are accurate
• Boolean logic models can even check fault tolerance, like
examining mechanisms that automatically adjust data
flow to route around faulty paths
– This ensures that the algorithm works
23. Access Control
• Access control flaws occur when access to a
resource is improperly granted or denied
– Can exist under numerous circumstances:
• Race conditions, improperly assigning access control
restrictions, improperly protecting resources, shared
resources, etc.
• A tremendous amount of work has been done
concerning access control violations and
modeling
– The works tend to pick on specific access control
violations, like time-to-check-time-to-use and
breaking Bell-La Padula model
24. Finding Access Control Flaws With
UML
• Many access control flaws can be exposed by UML
diagrams
– Sequence diagrams can expose race conditions, some
instances of starvation and deadlock, and time-to-check-
time-to-use
– Use cases and design diagrams can expose some instances
of improperly protected resources and instances where
shared resources can lead to access control flaws
• Note that UML will expose these flaws in the design
and may not expose flaws in algorithms or internal
working mechanisms – for that models must be used
25. Use Case Access Control Example
• In this example of a basic medical record system, there are four actors –
the Doctor, Nurse, Records Office, and Front Desk
– The Front Desk can create a record (person) and delete a record
– The Records Office can only view records
– Doctors can view and modify records
– Nurses can view and modify records
• There are multiple potential access control flaws
– Deletion is often as good as modification
– Modification can include deletion (erase all of the data in the record is the same as
deleting the record and creating a new one)
• In fact, the two can replace most of each other’s functionality and capability, with regard to the
destructive force/results
26. UML Race Condition Example
• In this example, a parallel Branch and Bound Knapsack solver written in
Java spawns multiple threads that then attempt to solve the knapsack
problem
– Each of the thread (ParallelKnapsackWorker) works for a period of time, say 5
seconds and then the thread notifies ParallelBranchAndBoundthe best knapsack
found thusfar
• If the thread has finished, it posts a final notification and is joined
– The threads sleep immediately after sending notification so that
ParallelBranchAndBound can then grab the current data from the thread (to
prevent a race condition where the data is changing as the parent retrieves it)
– The parent then calls notify() to wake the thread
• This can, itself, create race conditions, deadlock, and starvation because Java doesn’t allow the
program to specify which thread to wake
27. UML Race Condition Example (cont)
• Note that we now have two threads notifying
ParallelBranchAndBound at the same time
– This means that one of the notifies is either going to go unheard
(image on the left) or…
– …We have a very serious race condition where what we were trying to
protect from (ParallelBranchAndBoundgrabbing data while it is being
updated) occurs and worse – we have the complete loss of data as one
thread wakes another instead of ParallelBranchAndBound, who then
performs another notify() – potentially accidentally waking another thread
and causing a complete loss of control
28. UML Access Control Example
• Without any OCL to prevent it, a Student can rent a scientific video
– something that the requirements clearly stated should not be
possible
– If implemented as the diagram dictates, the system does not meet the
required access control capabilities… OCL should be included
29. UML Access Control Violations
• Carefully examine privileges
– Fields should always be private unless they are marked ‘final’
– Methods should be private unless there is good reason
• In most cases only constructors, getters, and setters should be anything other
than private
– Getters and setters should be limited and only available when required
• Carefully examine sequence diagrams for potential starvation,
deadlock, and race conditions
• Examine OCL to ensure that it prevents instances where
access to certain resources is inadvertently granted by the
diagram were the OCL incorrect or missing
– Common examples include bypassing the login to gain access to
protected data and using input validation flaws to gain access
30. Finding Access Control Flaws With
Models
• UML can find many of the access control flaws, but
may also create some
– As in the example where the lack of OCL allowed a
violation of the requirements and a breech
• Modeling, however, can help to discover complex or
covert access control flaws
– Models trivially discover covert channels and side channels
– Models also can be used to define the rules that will
enforce intended controls
• They can also prove that intended controls fail to achieve the
desired effect
– Models have even been used to discover previously
unknown access control flaws
31. Prolog Access Control Example
/** Excerpt from [14] -- a model to ensure database subtransactions are atomic, do not conflict, and can be rolledback/recovered from **/
haveto(Node1, Action1, Node2, Action2) :-
catch(not(maynot(Node1, Action1, Node2, Action2)), _, true).
cdefs(a, A, B) :-
cdefs(t, A, B),
haveto(A, abort, B, abort).
cdefs(b, A, B) :-
checkorder(A, begin, B, _).
cdefs(ba, A, B) :-
cannot(A, commit, B, _),
checkorder(A, abort, B, _).
cdefs(bc, A, B) :-
cannot(A, abort, B, _),
checkorder(A, commit, B, _).
cdefs(c, A, B) :-
checkorder(A, commit, B, commit).
cdefs(ex, A, B) :-
haveto(A, commit, B, abort).
• The full model identified several new subtransaction conflicts as
well as the previously unknown state of ‘ignored dependencies’
that were easy to discover using a logic model
– Conflicts include instances where race conditions are present, the
database cannot rollback/recover if something fails, access control
mechanisms are violated, or two subtransactions are attempting to
perform conflicting operations like committing and strongly committing
the same link
• Using Prolog, similar flaws are trivial to detect and correct
– Alloy can also be used to find certain access control flaws – Prolog is
generally better, though
33. Encryption
• Cryptographic flaws exist in all known crypto schemes
and their implementations
– Some flaws are far more egregious than others
– Flaws includepoor randomness, poor entropy collection,
poor keys, weak S-boxes, key exchange flaws, key sizes,
and reversibility of the algorithm
• Evil oracles have always been the Achilles’ heel and allowed the
reversing of the entire MD5 family (MD5, SHA, etc)
• Modeling and diagramming have uncovered previously
undiscovered flaws in common software
– Web-browsers have been shown to be trivial to hijack
sessions from because of the way they handle SSL
34. Finding Encryption Flaws With UML
• UML can be used to find some common cryptographic
flaws
– Most of the flaws are found in state and sequence
diagrams
– Encryption flaws found in state diagrams are usually just
for that ‘oracle’
• If a state diagram shows a flaw in OpenSSL’s handling of SSL, a
similar flaw may or may not exist in other implementations of SSL
– Flaws discovered in sequence diagrams are likely flaws in
the actual algorithm
• These flaws, of course, exclude mathematical errors,
other than to point out that the particular
implementation relies on a library that provides weak
entropy or randomness (e.g. rand)
35. UML Encryption Flaw Example (cont)
• Note the Trusted Third Party
– What if this trust were undue?
• The entire algorithm could be broken
• SSH suffers this problem as well
• What if the attacker spoofed the client,
rather than the server?
– The client never posts a certificate, so can
be trivially spoofed
• SSHv1 suffered this flaw; SSHv2 and
TLSv1/TLSv1.1 normally ‘authenticate’ the
client (weakly)
• What if the attacker downgraded the
cipher spec?
– This would allow the attacker to more
easily retrieve the session key
• This is common and normally done by
spoofing the client
• In many cases the client or server
downgrades as a matter of course
– Compatibility being the major reason
– The result is a much weaker algorithm
36. Finding Encryption Flaws With Models
• UML can only find encryption and cryptographic flaws
that are ‘surface level’
– Flaws in S-boxes, the underlying mathematical
assumptions, etc, are invisible in any UML diagram
• Modeling, however, can be used to discover many of
the flaws that UML and OCL are unable to find
– Models easily evaluate truth statements, such as those
about trust and who knows what when
• As well as who trusts whom and when
– Models can also help determine why levels of trust are
what they are
– Most importantly, models can verify the math behind the
algorithm
37. Prolog Encryption Flaw Example
/** Excerpt from a model to ensure the proper sharing of cryptographic keys**/
trust(Node1, Level1, Node2, Level2) :-
catch(not(violatesTrust(Node1,Level1, Node2, Level22)), _, true).
keyExchange(Key, A, B) :-
trust(A,_,B,high).
keyExchange(Key, A, B, C):-
trust(A,high,C,high),
trust(B,high,C,high).
sessionKeyExchange(Key,A,B):-
trust(A,high,B,high),
keyExchange(Key,A,B).
• The full model explains how most systems perform key exchange
– Or more correctly how most systems should perform the key exchange
• Models like this can help prevent a system from performing a poor
key exchange or one that leaves a system vulnerable to hijacking
before, during, or after the key exchange
• Using Prolog, logic statements like those governing trust and
security decisions can prevent the mistakes of SSHv1 and SSL
– The mathematics could be proven in Prolog, but there are much better
tools for that…
38. Coq Encryption Flaw Example
/** Excerpt from a model to prove mutual exclusion of a cryptographic algorithm**/
Lemma correct:forallmemo:Memo,Cycle memo->Oracle->CorrectTrace.
refine
(cofix choice : forallmemo:Memo,Cycle memo->Oracle->CorrectTrace :=
fun (memo:Memo)(cycle:Cycle memo)(oracle:Oracle)=>
SCons _ _ memo _ (choice (proc (hd oracle) memo) _ (tl oracle))).
• Numerous languages exist to help prove the correctness of cryptographic
algorithms
– Many of them rely on Prolog to provide the knowledge base and logic
• Coq and PVS are commonly used to prove the underlying mathematical
theorems
– In the example above, Coq is proving the lemma that illustrates a key property of
mutual exclusivity
– Failing this lemma means that the algorithm fails to provide mutual exclusion
• By using a mixture of Prolog-based languages and theorem solvers, most
common encryption flaws can be eliminated or reduced
– Alloy generally fails to provide the capabilities and is much more difficult in this
realm than Prolog-based solutions
40. Conclusion
• Formal Specification Techniques can be used to detect design flaws
– In some cases, after-the-fact models and diagrams have detected
flaws in implementations
• These are more costly and difficult to remedy than had they been caught in
the design phase
• In most instances, the flaws can be caught through both modeling
and to some degree with diagrams
– Many of the flaws can be seen through sequence diagrams and use
cases
– Other flaws can be caught with class diagrams
• Prolog is a powerful language that enables most modeling
languages to discover some of the more complex flaws
– This is particularly true with flaws that require changing states or
heavy logic and a powerful knowledge base
41. Acknowledgements
• This work relied heavily on previous works of
mine for examples, to include the modeling
examples provided
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