In the digital age, software code auditing is a pivotal part of creating secure, reliable, and high-performing applications. Even simple errors in coding can introduce major security, performance or compliance vulnerabilities as software systems become more complex. The days when code reviews were a nice-to-have in software development are over. A code audit that is structured can assist teams in locating flaws that are not obvious and can thus be avoided at a lower cost.
Today, sensitive customer information, money transfers and vital business processes are managed daily in modern applications. As a result, it is critical that organizations make sure that their code is secure, in line with industry standards and code best practices. Software code auditing is a thorough analysis of software source code to find weaknesses, enhance maintainability, and enhance software quality generally.
An effective code audit is more than just a set of automated scanning tools. It combines manual review, security testing, architecture analysis, performance evaluation and provides a comprehensive understanding of software behavior in real conditions. Companies that conduct audits periodically are more likely to publish more stable products and act in time to the changing threats in the security landscape.
This guide outlines the importance of software code auditing and the process of auditing software and provides a set of best practices for organizations that want to create secure and scalable software systems.
What is software code auditing?
A software code audit is a methodical process through which to analyze different characteristics of an application including its quality, architecture, security, performance, and sustainment. A software code audit takes broader view of a system versus a traditional code review, which typically focuses on recently modified code; therefore, during an audit, all parts of a system are reviewed as they relate to one another. All aspects of the system are assessed as well including infrastructure decisions, backend logic, security controls, deployment processes, dependency management, and scalability.
Software code audits are intended to identify defects, evaluate operational risks and the long-term implications of technical decisions. In addition to identifying potential problems, an audit will also analyze the application’s architecture and the stability of the infrastructure to which the application is deployed, any security exposure that exists, code consistency across the entire application, deployment workflows, and accumulation of technical debt.
Why software code auditing matters
Business performance is determined by the quality of software. A poor architecture causes slow delivery of features, an increase in the cost of maintaining existing features, and difficulty with day-to-day operations.
When software products grow larger and/or more complex, their technical issues become compounded. Eventually, development teams will spend more time resolving problems related to infrastructure and less time working on enhancements to the products. This slows down innovation and increases costs for operating the infrastructure.
One of the biggest motivators for companies to perform audits is security-related concerns. According to the Open Web Application Security Project (OWASP), insecure authentication, dependency on vulnerable software packages, and lack of proper access control still rank as the top three security risks for applications today.
There are many security vulnerabilities that remain undetected for long periods of time because they do not affect functionality in a way that is visible to users. Once these vulnerabilities are exploited, however, they can have severe financial or reputational consequences for the affected organizations.
Many times, performance problems are caused by an underlying architectural issue instead of being related to a single bug in the application. Problems with database designs, caching systems, API bottlenecks, or configuration mistakes in the infrastructure typically show themselves only after applications scale in terms of users and/or data.
Utilizing code audits provide organizations with the ability to identify these types of issues before they become more serious and thus reduce their operational risks over time.
Technical debt becomes more expensive over time
In software development, one of the biggest oftentimes unrecognized expenses is technical debt. When we are making quick decisions while rapidly developing software, these decisions may later result in some long-term operational challenges. Examples include quick patches, creating duplicate code, utilizing deprecated frameworks, and inconsistent architecture; and these problems will add complexity to an existing system as they continue to exist for a longer time.
During the early stages of a project, many times it seems like managing technical debt isn’t that big of a deal; however, once a system expands, the accumulated technical debt will start to have a negative impact on many other aspects of that system, including the following: deployment speed , onboarding/efficiency , release stability , infrastructure costs , and scalability of products .
According to research done by both Stripe and McKinsey, developers spend significant amounts of their time maintaining/fixing issues with existing systems rather than creating new features.
The longer you wait to address technical debt, the more costly it will be to remediate it.
When should companies conduct a code audit?
Auditing software while operations are still functioning will allow auditing to be conducted prior to discovering any operational issues with the software.
Some of the most typical motivations for needing an audit include rapid growth of a company, as architecturally scalable systems designed for early-stage growth will often fail when they try to scale up to having larger volumes of users due to the inability of the original decision-makers to prioritize scalability when launching a product.
Audits are also useful before launching major product releases or cloud migrations, before completing an acquisition, before raising capital, or prior to entering into an enterprise partnership.
When organizations inherit/acquire developers and their source code, this creates another reason to conduct an audit of their systems, as legacy systems typically have undocumented dependencies of other legacy applications and typically have outdated libraries and hardware platforms that create additional infrastructure-type risk. Also, if an organization is experiencing slower release cycles, more frequent defects, or performance problems in their products or services, then the technology the organization has may be architecturally deficient with respect to the codebase.
Security auditing and vulnerability analysis
Auditing software is becoming more important to evaluate an organization’s security. Today, most software contains sensitive information such as customer contact details and authentication information, financial history and records, healthcare records, and operations and analytics data. Having bad or weak security design exposes an organization to both operational and reputational risk.
A structured approach to evaluating security provides validation of the following: authentication methods, authorization methods and logic, dependency vulnerabilities, cryptography methods used, API’s exposed to the internet, infrastructure permissions set up, and the way code is deployed.
Although automating the identification of existing vulnerabilities can be done quickly with automated security tools, manual assessment is necessary because most of the most serious risk comes from flaws in business logic as opposed to purely technical configuration issues.
Based on findings in Verizon’s Data Breach Investigations Report, many organizations are victims of data breaches due to a variety of reasons including poor access management, out-of-date system software and improperly configured equipment.
Regular auditing will help reduce these types of risks significantly.
Architecture quality defines scalability
Architectural choices influence how easily a system evolves over time. Many new applications are built to be fast to market but don’t adequately consider eventual scalability issues, leading to architectural flaws that show up under production load. Some common examples of scalability issues are tightly bound services, poorly designed database schemas, fragmentation of infrastructure, excessive API dependency, or poorly implemented caching.
Architectural audits measure the ability of a system to grow independent of major re-work efforts. Audits today have begun to include more analysis into whether or not a system has been designed with cloud readiness, observability, deployment reliability and microservices communication patterns as these items will have a more significant impact on performance scaling.
Performance auditing and operational efficiency
Spectacular performance issues are very seldom the result of a single piece of programming code.
Generally, bottlenecks (performance issues) are caused by multiple inefficiently functioning components (i.e. databases, API’s, Operating systems, Data Storage Systems) that work together to create a chain of bottlenecks (operation failures).
The purpose of a performance audit is to evaluate the following system elements: Response Time, Validate Query Optimization (Query Efficiency), Memory Usage, Concurrent Users, Infrastructure Capacity, (Backend) API Latency.
Load testing allows businesses to understand how well their system performs at full production volume / loads.
Identifying performance limitations early can help businesses to avoid expensive EMO’s (Emergency Multi-Order) or sub-par performing systems produced by other vendors later.
Dependencies and infrastructure matter more than ever
A modern software application relies heavily on utilizing open-source libraries, cloud services providers, API’s, third-party applications and services. These external dependencies allow for faster development cycles, but they also create an operational risk exposure. Many older versions of open-source libraries have known vulnerabilities or issues with compatibility, and at some point, older versions of unsupported frameworks may create breaks in critical functionalities of those items after being upgraded to newer versions.
In addition, due to the increasing distribution of the software ecosystem, the quality of your infrastructure directly correlates with operational reliability. An infrastructure audit will evaluate the deployment pipeline, cloud infrastructure, monitoring systems, disaster recovery plans, backup procedures and container orchestration.
Documentation affects maintainability
Having inadequate documentation in business operations leads to massive inefficiencies for companies. A lot of business logic and processes are only stored within the minds of developers, rather than in any written, repeatable documents, making it very difficult to onboard new hires and maintain systems over time.
A comprehensive audit will examine the architectural-level documents, documentation for deployment processes / procedures, specifications for APIs, infrastructure diagrams for all systems, mapping for dependencies from system to system, and operational workflows.
Good documentation supports growth in engineering staff size and reduces the risk of operational issues due to loss of knowledge.
Why independent audits provide stronger results
Technical issues should be normalized internally by teams who consistently work in the same systems.
However, external auditors can offer an objective and broader engineering perspective than internal teams do; therefore, they are able to provide an analysis of how these technologies (engineering and technical) work together based upon their experience across a diverse range of industries, infrastructure environments, and architectural models.
At times, independent reviewers can identify hidden scalability issues, inconsistent engineering standards, weaknesses in infrastructure, and inefficiencies in operations faster than internal teams; therefore, they can assist the organization when prioritizing improvements based upon business impact, rather than on the organization’s own internal assumptions.
As a result of providing an outside view of technology to an internal team; the result can result in much better technical decision-making.
Common mistakes companies make during audits
Software auditing is a big mistake when it is viewed as a single event in time.
Software applications are always changing based on added features and functional integration, modifications to the underlying infrastructure, and scaling needs. So, every time an application is changed, there will be additional risk added to the system. Companies that audit their applications only when they have a major incident will incur higher remediation costs than those that audit continuously.
Another common mistake is that the focus is placed only on the application code and not on the underlying infrastructure and operational architecture of the application. Modern architectures are very dependent upon their deployment pipelines, monitoring tools (APIs), cloud environments, and third-party integrations.
Therefore, conducting an audit based only on code does not give the auditor all the data needed to see the full operational risk. Many other audits do not reach their desired result because the recommendations are so general. Engineering teams require remediation plans based on what should be repaired first and not just a list of defects.
AI-generated code introduces new auditing challenges
Software engineering workflows continue to change due to the ongoing introduction of development tools powered by Artificial Intelligence (AI).
In order to speed up the development of code, developers are using more AI-generated codes, automated development assistants, and other AI-generated suggestions and designed tasks. These AI tools can increase productivity, but they also increase new risk.
It’s possible that some of the code generated earlier using AI could contain unknown vulnerabilities, inconsistent architecture, duplicate logic, or code dependencies, and developers will not see these problems immediately.
Given the fact that more developers are utilizing AI-assisted development, code auditing will become more critical in verifying the quality and long-term maintainability of software.
In the future, the auditing workflow will consist primarily of combining human design review and AI-generated automated analysis for increased efficiency and accuracy.
Building a long-term auditing strategy
Auditors have a role to play in continuous engineering governance, not in emergency remediation.
Sustainable audit strategies provide security reviews, infrastructure assessments, dependency monitoring, performance testing, and architectural assessments on a recurring basis.
Continuous auditing helps reduce the operational risk associated with continuously evolving products as well as provide faster product stability and better infrastructure efficiency over the long term.
Mature engineering governance will produce faster cycle times, fewer production incidents, lower maintenance costs, and more scalable operations.
These improvements in operations provide measurable business value.
Final thoughts
Software code auditing has transitioned from being strictly a technical process to becoming a strategic operations requirement (operationally). The continued growth and interdependence of software ecosystems will lead to higher hidden technical risks. Security vulnerabilities, weaknesses in architecture, inefficiencies in infrastructure, and accrued technical debt can all negatively impact product quality, scalability, and overall business performance.
Through investment in consistent audit processes, organizations can create stable operations, while also minimize long-term maintenance costs and reduce infrastructure-related risks.
The best engineering teams recognize that building features quickly is one part of creating scalable software; the other critical factor is ensuring the architectural quality of the software, the level of security it has been designed with, and reliability of operations over time.
