Friday, March 15, 2024

Integrated Threat Modeling: VAST, STRIDE, DREAD, LINDDUN, and PASTA

Recently, during an Interview, I was asked about threat modeling. I've been in and around threat modeling for a few decades, identifying and prioritizing risks based on quantitative and qualitative data. It's germane to the principles of Information Security, Assurance, and Trust. The different shifting focus areas over time may require updated approaches, but the objective remains. Find and prioritize threats for risk mitigation based on our risk threshold prior to an exposure. 

Towards that end - I thought it'd be interesting to engage Claude's Opus model in a conversation about a few different approaches. There were several outputs I liked with a little tweaking. Below is just one example that includes VAST, STRIDE, DREAD, LINDDUN, and PASTA. 

Now - Carefully - The output below has some duplicity and can be further refined - a lot - for efficient workflow execution. This demonstrates the overlap and use of each of these models.

Example Integrated Threat Modeling Process:

Define Objectives and Scope:

  • Establish the goals and objectives of the threat modeling exercise.
  • Determine the scope of the assessment, including the systems, applications, and business units involved.

Identify Assets:

  • Identify the critical assets within the defined scope that require protection.
  • Prioritize the assets based on their value and importance to the organization.

Create Architecture Overview. This incorporates the core principle of the VAST model (Visual, Agile, Simple Threat modeling):

  • Develop a high-level architecture diagram of the system, focusing on key components, data flows, and trust boundaries.
  • Ensure the diagram is simple, visual, and easy to understand for all stakeholders.

Identify Threat Actors:

  • Identify potential threat actors who may have a vested interest in attacking the system.
  • Consider both internal and external threat actors, such as malicious insiders, cybercriminals, nation-state actors, and competitors.
  • Assess the motivations, capabilities, and resources of each threat actor.

Decompose Application and Identify Threats:

  • Break down the application into smaller, manageable components and identify trust boundaries and interactions between the components.
  • Identify potential threats for each component and interaction using the STRIDE model (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege) to:
    • Spoofing: Identify threats related to authentication and impersonation.
    • Tampering: Identify threats related to unauthorized modification of data or systems.
    • Repudiation: Identify threats related to the ability to deny actions or transactions.
    • Information Disclosure: Identify threats related to the unauthorized exposure of sensitive data.
    • Denial of Service: Identify threats related to the disruption or degradation of system availability.
    • Elevation of Privilege: Identify threats related to gaining unauthorized access or permissions.
  • Utilize attack trees, threat intelligence, and vulnerability data to assist in threat identification.

Analyze Threats and Vulnerabilities:

  • Assess the likelihood and potential impact of each identified threat using the DREAD model (Damage, Reproducibility, Exploitability, Affected Users, Discoverability):
    • Damage: Assess the potential damage caused by the threat if it were to occur.
    • Reproducibility: Determine how easily the threat can be reproduced or exploited.
    • Exploitability: Evaluate the level of skill and resources required to exploit the threat.
    • Affected Users: Assess the number of users or systems that could be impacted by the threat.
    • Discoverability: Determine how easily the vulnerability or weakness can be discovered by potential attackers.
  • Identify potential privacy threats using the LINDDUN model (Linkability, Identifiability, Non-repudiation, Detectability, Disclosure of Information, Unawareness, Non-compliance):
    • Linkability: Determine if data from different sources can be combined to identify an individual or link their activities.
    • Identifiability: Assess if an individual can be singled out or identified within a dataset.
    • Non-repudiation: Evaluate if an individual can deny having performed an action or transaction.
    • Detectability: Determine if it is possible to detect that an item of interest exists within a system.
    • Disclosure of Information: Assess the risk of unauthorized access to or disclosure of sensitive information.
    • Unawareness: Evaluate if individuals are unaware of the data collection, processing, or sharing practices.
    • Non-compliance: Determine if the system or practices are not compliant with privacy laws, regulations, or policies.
  • Conduct vulnerability and weakness analysis using scanning tools, penetration testing, and code review techniques.

Perform Attack Modeling:

  • Create and review attack models using the PASTA model (Process for Attack Simulation and Threat Analysis) methodology to:
    • Define Objectives: Establish the objectives and scope of the attack modeling exercise.
    • Define Technical Scope: Identify the key components, data flows, and trust boundaries of the system.
    • Application Decomposition: Break down the application into smaller, manageable components.
    • Threat Analysis: Identify and analyze potential threats using attack trees, threat intelligence, and vulnerability data.
    • Vulnerability & Weaknesses Analysis: Assess the system for vulnerabilities and weaknesses that could be exploited.
    • Attack Modeling: Simulate potential attack scenarios to determine the likelihood and impact of each threat.
    • Risk & Impact Analysis: Evaluate the risk and potential impact of each identified threat.
    • Countermeasure Analysis: Develop and recommend countermeasures to mitigate the identified risks.
  • Analyze the feasibility of each attack scenario.

Evaluate Risk and Impact:

  • Assess the overall risk posture of the system based on the identified threats, vulnerabilities, and attack models.
  • Determine the potential impact of each risk on the organization's business objectives and operations.

Decide on Countermeasures:

  • Develop and recommend countermeasures to mitigate the identified risks.
  • Consider the effectiveness, feasibility, and cost of each countermeasure.
  • Prioritize the implementation of countermeasures based on the risk level and available resources.

Validate and Iterate:

  • Review the threat model with stakeholders and subject matter experts.
  • Validate the assumptions made during the modeling process and update the model as necessary.
  • Iterate the threat modeling process regularly to account for changes in the system, new threats, and emerging vulnerabilities.

Communicate and Educate:

  • Communicate the results of the threat modeling exercise to relevant stakeholders, including management, development teams, and security personnel.
  • Provide training and awareness sessions to ensure that all stakeholders understand their roles and responsibilities in mitigating the identified risks.

Implement and Monitor:

  • Implement the selected countermeasures and integrate them into the system development lifecycle.
  • Establish monitoring and logging mechanisms to detect and respond to potential security incidents.
  • Regularly review and update the threat model and countermeasures based on changes in the system and the evolving threat landscape.

AI Revolution: Smarter Development, Stronger Security

The cloud computing landscape is experiencing a seismic shift driven by the exponential integration of Artificial Intelligence (AI). Recent advancements like Cognition AI's Devin and Microsoft's Copilot for Security showcase AI's potential to revolutionize software development and cybersecurity. 

Pay attention to the oncoming freight train of changes quickly coming to the computing world. 

Examples include: 

  • AI Agents working in teams: Effectively. Perfect? No. Getting better? Quickly. E.g. Cognition AI's Devin
  • Topically Focused LLMs, LAMs, etc.: E.g. Microsoft's Copilot for Security. Or any topic you can think about. I developed one to teach social skills to a teenage girl in less than an hour.
  • UI Navigation: Think about how the future of natural language query looks when I don't have to be an expert on the system UI anymore. 
  • Happening for the last year: The knowledge barrier to entry for many tasks continue to drop. Used to be There's an app for that... Now... There's an AI for that.

AI Agents: The Realistic Future of Development

Cognition AI's Devin is a groundbreaking AI agent that plans and executes software projects with minimal human input. Operating autonomously in a sandbox environment, Devin learns from experience, rectifies mistakes, and utilizes tools like code editors and web browsers. Devin isn't meant to replace engineers, but rather augment them, freeing human talent for more complex tasks and ambitious goals.

Imagine AI agents like Devin seamlessly integrated into cloud environments. This could significantly enhance development efficiency and scalability. AI can automate routine tasks, assist in code development, optimize resource allocation, and improve system performance, all while reducing costs and development times. Furthermore, these AI collaborators can provide real-time insights, identify potential issues, and suggest improvements, fostering a truly collaborative approach to cloud-based software development.

AI-Powered Security: Every. Single. Tool.

Microsoft's Copilot for Security highlights the growing role of AI in tackling cloud security challenges. This AI-powered chatbot, leveraging OpenAI's GPT-4 and Microsoft's security expertise, assists security professionals in identifying and defending against threats. Copilot for Security will utilize the 78 trillion signals collected by Microsoft’s threat intelligence. Copilot provides real-time security updates, facilitates collaboration among teams, and even answers questions in natural language.

Integrating AI chatbots like Copilot into the cloud security landscape can significantly enhance threat detection and response. By analyzing code and files, providing real-time updates on security incidents, and enabling natural language queries, AI helps organizations stay ahead of threats and respond more effectively to cyberattacks. Additionally, AI chatbots lowers the barrier to knowledge sharing and breaks down silos, fostering a more coordinated approach to cloud cybersecurity.

Scalability, Flexibility, and the Cloud's Future

The growing demand for adaptable AI solutions is reflected in Microsoft's pay-as-you-go pricing model for Copilot for Security. As AI becomes more embedded in cloud computing, expect to see more consumption-based pricing models, making AI-powered services accessible to businesses of all sizes.

The convergence of AI and cloud computing promises to drive innovation across industries. AI-driven automation and collaboration will be cornerstones of future cloud computing, enhancing efficiency, security, and scalability. As AI agents and chatbots like Devin and Copilot evolve, we can expect a future where AI seamlessly collaborates with human professionals, unlocking new opportunities for success in the cloud era. 

Embracing the Future: Be prepared. Be proactive. 

The introduction of Devin and Copilot for Security exemplifies AI's transformative impact on cloud-based development and security. By embracing AI-driven automation and collaboration, cloud providers and organizations can position themselves at the forefront of this revolution, driving innovation, efficiency, and security. As AI continues to shape the future of cloud computing, businesses that adapt and harness these technologies will be best equipped. Be prepared. Be proactive. 

Tuesday, March 12, 2024

Staying Current - Relevant - Continuous Learning

Protect your organization. Cybersecurity is a dynamic field where new threats, vulnerabilities, and technologies change, evolve, and emerge. Commit to continuous learning and skill development. Stay informed about the latest security trends, best practices, and tools. 

Resources for Staying Current:

Quick note! There's a lot here. I'd love to read all of this every day. It doesn't happen, and I have my favorites depending on my current role. The resources necessary for your success vary widely. For example, these here focus on security resources. They only scratch the surface of what's available, and they completely gloss over privacy, regulatory compliance, information governance, legal issues, etc.. 

Vendor-Specific Security Advisories:

Stay informed about security updates and patches from major technology companies.

Government and Non-Profit Security Organizations:

Follow updates from organizations for authoritative guidance and best practices.

Cybersecurity News and Blogs:

Stay informed about the latest security incidents, trends, and analysis through popular blogs and news sites.

Security Mailing Lists & Vulnerability Databases:

Subscribe to mailing lists to receive timely information about new vulnerabilities and exploits. You can do this to regularly check vulnerability databases to stay informed about newly discovered vulnerabilities and their potential impact. 

Security Conferences:

Attend conferences to learn from industry experts, network with peers, and stay updated on the latest research and trends. Also check out the YouTube channels for each of these to see what talks have been recently published.

Online Security Communities:

Engage with online communities to learn from others, ask questions, and contribute to discussions.

Again, this isn't a complete, all-inclusive list of resources. Not even close. The objective is to provide exposure to options and importance. Other media I find to be helpful includes YouTube, Claude and other AI chat, and audiobooks. 

Continuous learning is essential. Make the choice to stay current, relevant, and effective. Yes, it's hard sometimes. It takes intentionality - and a little goes a long way. You can do it...! There are many, many more than just these sources. The purpose is to develop a comprehensive approach to continuous learning that combines staying informed about the latest security news, following best practices, and engaging with the cybersecurity community.