From risk analysis to implementation: this is how you build a secure application framework

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Designing and implementing frameworks for application security is essential to keep systems safe, from the initial design phase through daily management. In this blog, we discuss how organizations and development teams can follow a structured approach that integrates risks, requirements, and security principles from the very beginning. We cover the most important core principles, explain how theoretical models and frameworks are applied in practice, and show how a continuous improvement cycle contributes to safer and more reliable applications.

This blog is also highly relevant for people developing AI applications. For AI systems, it is particularly important to implement an application security framework during the design phase, before the system is built and data is processed. AI models rely on large amounts of data, often including sensitive information, which means risks such as data leaks, unauthorized access, and misuse can arise quickly. By incorporating security early according to a framework, the fundamental principles of confidentiality, integrity, and availability are ensured, allowing both the system and its data to be used safely.

If you are interested, you can also read this blog to learn how to develop systems that require user logins effectively.

What does a framework for application security actually mean?

When organizations say an application must be built according to a security framework, they usually mean that security should not be an afterthought. It should not be something you check only after everything is already built. Instead, security must be consciously integrated into decisions from the initial idea through daily management. Concretely, this means considering risks at every step and planning how to control them.

A framework for application security is therefore not a single tool or a simple checklist. It is a coherent system of principles, processes, and measurement points that provides guidance for safely designing, building, and managing applications. It helps organizations examine risks in a structured way and select appropriate measures to mitigate them.

In secure software engineering literature, this approach is seen as a shift from reactive to proactive work (OWASP, n.d.). Rather than waiting for a vulnerability to appear, you anticipate where problems might arise and plan to prevent them. Well-known models, such as the Secure Software Development Framework from NIST (https://csrc.nist.gov/publications/detail/sp/800-218/final) and maturity models from OWASP (https://owasp.org/www-project-samm/), emphasize that security is not only a technical concern but must also be embedded organizationally. The principle is simple: errors and vulnerabilities become far more costly if discovered late. This idea has been widely supported in the literature.

In short, the earlier you prevent a problem, the less damage it causes. This can be achieved by creating a development plan from the start that integrates risk analysis and security principles as core components of the process.

Theoretical foundations of secure software engineering

Application security is not just a collection of best practices; it is grounded in clear theoretical principles. A key foundation is risk management, as described in ISO 31000 (https://www.iso.org/standard/65694.html) (ISO, 2018). In this framework, risk is understood as a combination of likelihood and impact. This means organizations must consider not only whether an event could occur but also the potential consequences if it does.

Another core principle is defense in depth, which involves applying multiple layers of security. If one measure fails, additional layers provide protection. This concept originates from military strategy and was formalized in the IT context by the National Security Agency (NSA) as a structured approach to layered information security, combining physical, technical, and administrative safeguards into a robust whole.

Classical design principles also play a major role. Saltzer and Schroeder (1975) introduced concepts such as least privilege and fail-safe defaults.

• Least privilege ensures that users and systems are granted only the permissions strictly necessary for their tasks.
• Fail-safe defaults mean that access decisions are based on explicit permission rather than exclusion. By default, access is denied unless it is explicitly granted. If an error occurs in a mechanism that grants permission, the system fails safely by refusing access, making the issue apparent quickly.

Examples of practical implementations of least privilege include:

• Identity and Access Management (IAM), including multi-factor authentication
• Role-Based Access Control (RBAC) or Attribute-Based Access Control (ABAC)
• Token management as a dedicated and critical architectural component

These foundational principles continue to shape secure architecture and secure coding practices. An application security framework translates these theoretical concepts into concrete actions, such as performing risk analysis, implementing layered security, and carefully designing authorization models.

In practice, this means organizations must build multiple layers of protection into system designs and strictly limit access rights to what is necessary.

Security by Design as a core principle

Security by Design is a fundamental principle in modern application development. It means that security is integrated from the very first stage of system design. This contrasts with traditional models, where functionality is built first and security is added later. In literature, this approach is often called “shift left” because security activities are performed earlier in the development process.

In practice, Security by Design requires considering confidentiality, integrity, and availability, which is the well-known CIA triad from information security (ISO, 2018), already when defining requirements. Other critical aspects include data minimization, retention periods, and purpose limitation, which often become strict design requirements at this stage.

During this early phase, it is essential that requirements are precise, verifiable, and complete. Vague or implicit requirements almost always lead to design choices that are difficult or costly to correct later, especially in areas such as authorization models, data classification, or integrations with external systems. Requirements that are not clearly documented are open to interpretation, which often causes errors.

Organizations must determine in advance which data is sensitive, which threats are realistic, and which security measures are appropriate. Clearly defining the intended purpose of the application, including what it must achieve, for which user groups, and within which boundaries, prevents functionality from expanding unintentionally in ways that increase the attack surface. Well-defined requirements not only describe the goal but also include measurable criteria to determine whether the goal has been safely achieved.

Threat modeling is a common practice for this, using methodologies such as STRIDE, originally developed by Microsoft and now widely applied in the industry (OWASP, n.d.). STRIDE allows teams to systematically analyze possible threats, including spoofing, tampering, and privilege escalation. Conducting this analysis early prevents discovering vulnerabilities only after deployment. Security then becomes a fixed quality requirement on the same level as performance or user-friendliness.

Another widely cited tool is the Application Security Verification Standard (ASVS), which provides standardized acceptance criteria to verify that security requirements are realized in both design and implementation. ASVS operationalizes the verifiability of requirements and ensures that security objectives are measurable and testable.

In short, establishing clear, verifiable security requirements from the outset and systematically mapping potential threats is essential for building secure applications.

How security by design works in practice

In practice, Security by Design begins with explicitly formulating security requirements alongside functional requirements. This means describing not only what the system must do, but also how it must remain safe. If requirements are insufficiently detailed at this stage, development teams may make assumptions about access rights, data retention periods, or confidentiality levels. Such assumptions are rarely fully corrected later and can lead to structural vulnerabilities. Requirements should therefore be specific, measurable, and traceable to business goals and risk analyses.

The next phase is design, in which security principles such as segmentation, strong authentication, and encryption are incorporated as standard practice.

During development, programmers follow secure coding guidelines, often based on knowledge bases such as OWASP (https://owasp.org/) (OWASP, n.d.). Key practices include input validation, secure error handling, and correct use of cryptography.

Testing goes beyond functional validation. Security scans, including static and dynamic code analysis, and sometimes penetration tests, are performed. Security does not end at delivery. Monitoring, logging, and patch management remain necessary. Security by Design is therefore not a one-time action, but a continuous process. Organizations must continuously monitor and improve security even after systems go live.

Why security by design makes an organizational difference

Implementing a security framework affects not only technology but also organizational structure. Security becomes a shared responsibility. This requires clear definitions of roles, responsibilities, and measurable objectives. Data management remains critical. These practices ensure that security does not depend on a single specialist, but is embedded structurally within the organization.

Security by Design also requires transparent decision-making about risks and active management involvement. Organizations that define and operationalize their requirements from the outset and translate them into an integrated framework gain administrative control. This allows them to demonstrate which risks have been consciously accepted and which measures have been taken. The approach strengthens not only security but also auditability and compliance.

Security becomes a strategic theme rather than a purely IT issue. Organizations that manage this well often discover that security is not an obstacle, but a source of trust among customers and stakeholders.

In a time of rapid technological change, including advances in artificial intelligence that transform business models and processes, thorough research into existing theories, standards, and best practices is essential. By systematically mapping different solution options, organizations gain insight into underlying assumptions, strengths, weaknesses, and contextual applicability. Combining multiple perspectives and models into a coherent, adapted framework enables better alignment with the organization’s strategic and technological reality. No standard model fits every context, so customization based on well-founded knowledge improves both effectiveness and legitimacy.

A strong security framework also addresses dependencies on external components, libraries, and suppliers. External dependencies can introduce vulnerabilities, unknown risks, or malicious code outside the organization’s direct control, which can significantly increase the attack surface.

Finally, KPIs and metrics are essential when designing a security framework. Without measurable indicators, such as mean time to detect (MTTD), the percentage of patched systems, or results from security audits, a framework cannot be demonstrated to be effective and provides insufficient administrative control. Measurable indicators are indispensable for auditability and compliance.

From theory to process: everything summarized in steps

If you summarize the process, you see a number of logical steps. First, you perform a risk analysis to gain insight into assets, threats, and vulnerabilities. Based on this, you then set priorities. Parallel to this, the intended effects of the application are made explicit and translated into concretely operationalized requirements. This means that each goal is linked to clear acceptance criteria and security boundary conditions, so that no room remains for interpretation differences between business, architects, and developers. In addition, it must also be clear what the minimum requirements are that a framework for application security must contain. A handy tool for this is to subdivide these requirements into design criteria such as feasibility, desirability, and viability. In this way, it becomes easier later to demonstrate that the desired goals and requirements have been realized.

Then, you work out concrete security requirements and design the architecture according to principles such as least privilege and defense in depth, supplemented with usable literature and lessons learned from other proven models. Then, you test the created framework (or your prototype), perform a number of iterations to improve the framework, and implement secure coding standards in this. Before going live, a security review takes place. Then follows the management phase, in which monitoring and periodic reassessment of risks are central. Together, these steps form a continuous improvement cycle, comparable to PDCA, but specifically focused on security.

Briefly summarized, organizations and companies must always follow a clear, step-by-step cycle of risk analysis, design, testing of the prototype, implementation, renewed testing, iterations where necessary, and monitoring in order to achieve better results.

Summary: click below to enlarge the image.

References

• International Organization for Standardization. (2018). ISO 31000:2018 Risk management Guidelines. https://www.iso.org/standard/65694.html
• National Institute of Standards and Technology. (2022). Secure Software Development Framework (SSDF) Version 1.1 (SP 800-218). https://csrc.nist.gov/publications/detail/sp/800-218/final
• OWASP Foundation. (z.d.). OWASP Software Assurance Maturity Model (SAMM). https://owasp.org/www-project-samm/
• Saltzer, J. H., & Schroeder, M. D. (1975). The protection of information in computer systems. Proceedings of the IEEE, 63(9), 1278–1308. https://ieeexplore.ieee.org/document/1451869