Modernizing the Application Penetration Engagement and Reporting Lifecycle

Modernizing the application penetration testing lifecycle is a critical step for consultancies and internal teams aiming for greater efficiency, consistency, and data-driven insights. Many experienced security engineers are all too familiar with the pain of legacy systems: a chaotic web of Word documents, Excel checklists, and manual data entry that is both error-prone and impossible to scale. This talk by Ryan Armstrong provides a masterclass in tackling this challenge head-on, detailing a comprehensive transformation from a disjointed, document-based workflow to a streamlined, automated, and centralized process.

This structured breakdown moves beyond theoretical advice, offering a practical blueprint for overhauling your entire engagement process. You will learn how to diagnose the specific failures of legacy systems and discover a concrete strategy for migrating to a modern reporting platform like PlexTrac. Furthermore, we will explore how to leverage the Microsoft Power Platform to build a central data model that automates tedious tasks, from initial project scoping to final analytics, ultimately freeing up your engineers to focus on what they do best: breaking things.

Diagnosing the Pains of a Legacy Pentest Engagement Lifecycle

A critical first step in modernizing any application penetration testing lifecycle is to conduct an honest and thorough diagnosis of the existing process. For many teams, this “legacy” lifecycle is a patchwork of manual processes, static documents, and over-extended office software that creates significant drag on efficiency and data integrity. The entire process, from initial client contact to final analytics, is often riddled with pain points that are accepted as “just the way things are.”

These systems can be described as information processing systems with an inherent data flow, but when that flow is fragmented across disconnected documents, the entire structure becomes brittle and inefficient. Let’s break down the specific pains identified at each stage of a traditional pentesting engagement.

Scoping and Intake: A Maze of Checklists and Hopes

The engagement begins long before any testing occurs, and it’s here that the first cracks appear. The process is characterized by a series of manual handoffs and disconnected documents.

• Excel-Based Scoping: The process typically kicks off with an Excel checklist for a subject matter expert to estimate effort. This is often insufficient, necessitating a follow-up call where testers take free-form notes.
• Isolated “Special Requirements” Docs: As client needs evolve, new documents are created to track special requirements. These are often Word documents saved in a folder, with the team simply hoping that the information is accurate and that the eventually-assigned tester will find and validate it.
• Error-Prone Intake: A separate intake document is sent to the client for technical details. This is often filled out by individuals unfamiliar with the original scope, leading to frequent mistakes and inconsistencies.
• Redundant Reviews: To combat intake errors, another manual process is created: the intake review. This involves a tester using yet another Excel checklist to compare scoping documents against the intake form. These checklists are described as “tedious” and “general,” leading to compliance fatigue and potential oversights.

At every step, critical engagement data is captured in static, isolated files, creating multiple sources of truth and relying on human diligence to bridge the gaps.

Testing and Reporting: The Tyranny of Word and Excel

The core activities of testing and reporting are where the inflexibility of legacy tools becomes most acute. While checklists and templates aim for consistency, they often introduce their own set of problems.

• The Pain of Checklists: During testing, engineers are saddled with more general-purpose Excel checklists for process and findings. For experienced testers, this becomes an “exercise in tedium” rather than a helpful guide. Attempts to make them dynamic using VBA (Visual Basic for Applications) result in a “huge mess” that is difficult to maintain and can’t handle the required complexity.
• The Word Reporting “Nightmare”: Using Microsoft Word for reporting is a common industry pain point. The legacy process detailed here attempts to make it manageable through heavy customization:
  • Custom VBA Macros: A custom ribbon with VBA scripting is used for formatting and generating summary tables. However, parsing a Word document is a “nightmare to build and maintain,” and features like CSV exports often fail or require manual fixes.
  • Plugin-Based Content Management: A commercial plugin, Smart Docs, connects to a SharePoint repository to pull in finding templates. While this makes the process “manageable,” the underlying structure is flawed. The finding templates themselves are stored as individual Word document attachments, not as structured data.
• Manual Template Maintenance: This document-based approach makes content management a “huge headache.” For example, updating a reference like the OWASP Top 10 across a library of over 400 findings requires manually downloading, editing, and re-uploading each Word document—a process described as “chaos.” The report templates themselves are filled with highlighted guidance and conditional text that must be manually deleted by the engineer for every report.

Post-Delivery: Data Silos and Manual Analytics

Once a report is delivered as a static PDF, the valuable data within it becomes almost impossible to leverage at scale. The information is effectively locked away in archived folders.

• No Central Data Collection: The entire process results in a collection of static Word, Excel, and PDF documents. There is no central database, meaning crucial metadata and engagement information “basically disappear” after archiving.
• Painful, Manual Analytics: The lack of a data-centric model makes any form of analytics a grueling, manual task. To provide a client with high-level statistics on their findings, the process is literally to “go into all these folders and I take the PDFs out and I’m counting things… it sucks.”
• Inability to Ask Strategic Questions: This system makes it impossible to answer critical business or process questions, such as quantifying the effectiveness of a DAST tool versus manual testing, because there is no mechanism to track this type of data systematically.

Case Study: The Manual Grind of Generating Client Analytics from Static PDFs

1. Receive Request: An enterprise client requests high-level analytics to understand persistent issues and collective risk across their entire portfolio of applications that have been tested over time.
2. Locate Static Reports: The security professional must manually navigate to archived test folders, which store all the static documents from previous engagements in a decentralized manner.
3. Extract Data from PDFs: For each relevant engagement, the final report—a static PDF document—is opened. This document contains all finding data but in an unstructured, non-machine-readable format.
4. Manual Tallying and Classification: The professional reads through each PDF, manually counting the number of findings. More importantly, they must read the details of each finding to manually classify them (e.g., by vulnerability type, severity, or affected application) to identify persistent cross-application issues.
5. Aggregate and Deliver: The manually counted and classified data is then compiled into a separate, newly-created summary document to fulfill the client’s request. There is no existing analytics process or tool.

This case study demonstrates a critical failure point in a legacy application penetration testing lifecycle: the inability to generate client analytics without extreme manual effort. The entire process relies on treating static PDF reports as the final source of truth, creating massive data silos. When a client requested a high-level overview of their security posture—a common and reasonable business request—the only available method was for an engineer to manually go into archived folders, open each individual PDF, and physically count and classify findings. This workflow is not a structured process but a painful, ad-hoc reaction that is incredibly inefficient, prone to human error, and completely unscalable. It perfectly illustrates why automating security workflows and centralizing data away from static documents is essential. The pain of this manual “analytics” process is a primary driver for modernizing the penetration testing reporting process and adopting a data-centric platform.

Overhauling the Penetration Testing Reporting Process

A critical component of modernizing the application penetration testing lifecycle is overhauling the core deliverable: the report itself. The legacy system, built on Microsoft Word, presented significant inefficiencies despite being enhanced with custom VBA macros and a commercial plugin, Smart Docs, for content management. This setup was inflexible, making it a “nightmare” to parse content for tasks like generating CSV exports for clients. The entire penetration testing reporting process was hindered by manual effort, such as testers having to manually un-highlight conditional text or delete guidance sections from the final document.

From Legacy Structures to a Modern Finding Design

The first step in the overhaul was a strategic rethink of the report’s structure, moving away from legacy formats inherited from network testing. An analysis of publicly available penetration test reports revealed substantial variation across the industry and highlighted the need for a more logical, application-centric design.

The old finding structure was confusing, with vague sections like “Observation” and “Implication” alongside a general “Findings” section that acted as a catchall for technical details, reproduction steps, and impact analysis. This made reports difficult to parse and understand.

The new, revised finding structure introduces clearer, more purposeful sections:

• Background: Provides context for the finding, replacing ambiguous legacy sections.
• Steps to Reproduce: A dedicated section detailing how to replicate the vulnerability. This was added specifically because clients were often having difficulty understanding the issue from the technical description alone.
• Risk Assessment: A specific area to explicitly justify the assigned risk rating, answering the “why is this a high-risk finding?” question directly.
• Standards Referencing: A structured way to map findings to multiple standards like CWE, ASVS, and the OWASP Top 10.

Selecting and Adopting a Modern Reporting Platform

With a new report structure defined, the team formed a task force to evaluate modern reporting platforms. They developed a 12-question form to assess key features and sought demos from various vendors. A critical requirement was strong support for technical reviews and collaboration, as this is a primary mechanism for providing feedback and mentorship to testers.

The team ultimately chose PlexTrac reporting as it best suited their use cases. A key technical advantage was its use of CK Editor, which supports rich text (HTML). This was a strategic decision to ensure content remained platform-agnostic, preventing the kind of vendor lock-in that made migrating away from the old Word/Smart Docs system so painful. The ability to manage finding content as HTML means that if they ever need to switch platforms again, the transition will be significantly easier. The team even used the CK Editor inspector tool to view the underlying HTML, which proved essential for debugging content migration issues.

Centralizing and Automating Security Engagement Management

A critical step in modernizing the application penetration testing lifecycle is moving away from disparate, static documents and toward a central source of truth. The legacy approach of using separate checklists and Word documents for each stage results in data silos, inefficiency, and a high potential for error. By treating the entire engagement as an information processing system, you can develop a cohesive data model that underpins and streamlines the entire workflow.

Building a Central Data Model with Microsoft Lists

The foundation for effective security engagement management is a centralized data model. Instead of storing critical information in isolated Word documents and Excel files, a structured database provides a single source of truth. A practical approach is to leverage Microsoft Lists (built on SharePoint) to create this central repository. This allows you to define and track a wide range of attributes for each engagement, client, and finding in a structured manner with appropriate data types.

Key benefits of this approach include:

• Data Consistency: It eliminates the “multiple sources of the same data” problem, which leads to inconsistencies and errors when information is copied manually.
• Dynamic Interfaces: Instead of static checklists, you can build dynamic forms directly in Microsoft Lists or with Power Apps. These forms can intelligently adjust the fields presented to the user based on the engagement type, reducing cognitive load and ensuring only relevant data is collected.
• Metadata Tracking: You can track metadata that was previously lost or impossible to capture, such as scoping accuracy, which findings were discovered by DAST vs. manual testing, or even the estimated bug bounty payout for a given vulnerability type.

Automating Security Workflows with Power Automate

Once engagement data is centralized, you can begin automating security workflows that were previously manual and error-prone. The Microsoft Power Platform’s Power Automate is a powerful low-code tool for this purpose. By creating automated flows, you can trigger actions based on data entry or status changes in your Microsoft List.

A prime example discussed is automating the handoff from the scoping team to the sales team:

• Legacy Process: A tester would manually gather information from various documents, construct an email to the sales contact detailing the estimated effort and requirements, and hope the information was copied correctly.
• Automated Process: After the scoping data is entered into the central Microsoft List, a tester can click a button to trigger a Power Automate flow. This flow automatically:
  1. Constructs a standardized, pre-formatted email containing all necessary information for the sales proposal.
  2. Sends the email to the correct sales contact.
  3. Simultaneously sends a separate, tailored email to the project management platform with the information needed for project setup.

This automation not only saves significant time but also enforces standardization, improves maintainability, and drastically reduces the risk of human error in transferring critical engagement details.

Automating the Scoping-to-Sales Handoff with Power Automate

1. Centralize Data: The first step is to move away from static documents and centralize all engagement scoping data into a Microsoft List. This list is configured with specific columns (fields) to capture all necessary information, such as effort estimates, client requirements, and other technical details formerly kept in disparate Excel and Word files. This creates a single, structured source of truth for each engagement.
2. Implement Power Automate Trigger: A Power Automate flow is created and linked to the Microsoft List. The flow is designed to be triggered manually by a tester after they have filled out and validated a scoping item. The transcript states, “…you click the Automation and it sends that email automatically.” This is typically implemented as a button within the List’s interface for a selected item.
3. Configure Automated Email to Sales: The core of the automation is a ‘Send an email’ action within Power Automate. The flow is configured to:
   • Pull specific data fields directly from the triggering Microsoft List item (e.g., ‘Effort Estimate’, ‘Customer Requirements’).
   • Populate a standardized email template with this dynamic data.
   • Send this structured email directly to the appropriate sales contact.
4. Integrate with Project Management: In a parallel action within the same Power Automate flow, a second email is constructed and sent. The transcript notes it “simultaneously…sends a separate email to the project management platform with the information that is needed there.” This second email is formatted with the specific data required by the project management system to initiate a new project, automating that data entry point as well.
5. Achieve Standardization: The outcome is a fully automated and standardized handoff. The sales team receives consistent, accurate information in a predictable format, which allows them to use a “better proposal document template” without needing to interpret or re-format technical details. The project management system is also updated without manual intervention.

This proof of concept demonstrates a practical solution for a common bottleneck in the application penetration testing lifecycle: the manual handoff from technical scoping to sales. The legacy process required a tester to manually gather data from static documents, compose an email, and send it to the sales team, a workflow described as inefficient and highly “prone to error.” The modernization strategy centers on automating security workflows using the Microsoft Power Platform. By centralizing all scoping data in a Microsoft List, the organization establishes a single source of truth for security engagement management. A low-code Power Automate flow is then built to trigger off a completed scoping record. Upon activation, the flow automatically pulls key fields and dispatches two separate, standardized emails: one to the sales team with the necessary data to build a client proposal, and another to the project management platform to create a new engagement record. This automation eliminates manual data transfer, enforces consistency, and allows for more efficient penetration testing reporting process initiation, freeing up engineers from administrative overhead.

Implementing a System to Track DAST vs. Manual Finding Efficacy

1. Identify the Data Management Limitation: The existing process lacked a method to systematically quantify the effectiveness of Dynamic Application Security Testing (DAST) tools versus manual testing efforts. This made it impossible to generate data-driven evidence for tool value, as the legacy reporting system did not support tracking this kind of metadata.
2. Establish a Structured Finding Database: The foundational step was to migrate from storing finding templates as individual Word documents to a centralized, structured database using Microsoft Lists. This platform allows for the creation of custom attributes for each finding entry.
3. Add a “Finding Source” Metadata Field: A new field was added to the finding schema in Microsoft Lists. This attribute was designed to capture the origin of each finding, with potential values like “DAST Tool,” “Manual Discovery,” or even specific tool names.
4. Integrate into the Reporting Workflow: As part of the modernized penetration testing reporting process, testers are now required to populate this “Finding Source” field for every vulnerability documented. This becomes a mandatory step within the new reporting platform (PlexTrac reporting), ensuring data consistency.
5. Enable Efficacy Analysis: With this data now centrally collected and structured, the team can perform queries and analytics to determine the percentage of findings sourced from DAST versus manual testing. This provides a quantifiable measure of tool efficacy and ROI, informing decisions within the application penetration testing lifecycle.

The speaker described a common challenge: skepticism about the value and ROI of expensive DAST tools compared to manual penetration testing. The legacy system, based on static documents, offered no way to track which findings were discovered by which method, leaving the team with only anecdotal evidence. The PoC for solving this was a direct result of modernizing their security engagement management and reporting infrastructure. By migrating their entire finding library to a structured database in Microsoft Lists, they gained the ability to add new metadata fields. They implemented a simple but powerful system by adding a single attribute to track the source of each finding (DAST vs. manual). This small change, integrated into their PlexTrac reporting workflow, now allows them to quantify the efficacy of their tools, directly addressing the business need for data-driven analysis and improving their overall application penetration testing lifecycle.

Strategies for Migrating and Managing Finding Template Content

Migrating a large library of finding templates is one of the most significant hurdles in modernizing the application penetration testing lifecycle. The intellectual property contained within these templates—often hundreds of well-written, detailed findings—is a critical asset. However, when this content is trapped in legacy systems like Word documents, it becomes a liability, hindering efficiency and scalability. The key to a successful transition lies in moving from an unstructured, tool-specific format to a structured, platform-agnostic database that can serve any reporting tool, including modern platforms like PlexTrac.

The Pitfalls of Legacy Content Management

The previous system relied on a commercial Word plugin, Smart Docs, to connect to a SharePoint repository. While this provided a basic content library, it had a fundamental flaw: the finding templates were stored as individual Word document attachments within a SharePoint list. This approach presented several major challenges:

• Lack of Structured Data: Although the SharePoint list had attributes, the core content of the finding (description, remediation, references, etc.) was opaque, locked inside a Word document. It was not stored as native data types, making it impossible to query or manage programmatically.
• Manual and Error-Prone Updates: Performing bulk updates was a nightmare. For example, to update a reference to a new OWASP Top 10 version across all relevant findings, an engineer would have to download all 400+ Word documents, manually perform a find-and-replace, and then bulk re-upload them. This process was described as “chaos” and was incredibly inefficient and prone to error.
• Vendor and Tool Lock-In: The entire library was dependent on the combination of Word and the Smart Docs plugin. Migrating away from this ecosystem meant facing a massive, manual effort to extract and restructure the content.

Adopting a Platform-Agnostic Content Database

To overcome these limitations and ensure future flexibility, the strategic decision was made to decouple the finding content from the reporting platform. Microsoft Lists was chosen as the new, centralized database for the entire library of finding templates. This modern approach offered significant advantages:

• Structured Data and Rich Metadata: Instead of Word attachments, each component of a finding—description, risk assessment, steps to reproduce, references—was stored in its own field with appropriate data types. This included support for rich text (HTML), which is highly compatible with the CKEditor used in the new reporting platform, PlexTrac reporting.
• Platform Independence: By storing content as structured data with HTML for formatting, the library is no longer tied to a specific vendor or tool. If the team decides to switch from PlexTrac in the future, the migration process would be as simple as exporting the data from Microsoft Lists into the new platform’s required format.
• Enhanced Analytics and Value: This structured model allows for tracking rich metadata that goes far beyond the report content. For example, a new process was implemented to track attributes like Bug Bounty Eligibility and Approximate Bounty for each finding. This data, stored alongside the template, enables novel analysis, such as comparing the cost of a pentest report versus an equivalent bug bounty payout—insights that were previously impossible to generate.

The Technical Migration Workflow

The practical migration from unstructured Word documents to a structured Microsoft List was a significant technical undertaking that required custom scripting. The process involved several key steps:

1. Develop Parsing Scripts: Team members developed scripts to programmatically open the legacy Word document “Snippets” used by Smart Docs.
2. Extract and Structure Content: The scripts parsed the content from the different sections within each Word document.
3. Generate a CSV: The extracted data was organized and exported into a single, structured CSV file, with columns mapping to the fields in the new Microsoft List.
4. Import to Microsoft Lists: The CSV was uploaded to create the new, structured content library in Microsoft Lists, instantly populating it with over 400 findings.
5. Automate Export for Reporting Platform: A final automation was built to export the content from the Microsoft List into a CSV format compatible with PlexTrac’s database import functionality. This allows for seamless and repeatable updates from the central content library to the reporting platform.

Navigating the Challenges of Process Modernization

Modernizing an application penetration testing lifecycle is as much a project management and change management challenge as it is a technical one. Even with a clear vision for automating security workflows, teams will face significant real-world friction. These challenges move beyond tool selection and into the complex realities of business operations, human factors, and the process of migrating from an entrenched legacy system.

The Conflict Between Internal Projects and Billable Work

A primary hurdle, especially within a consultancy, is the constant tension between internal improvement projects and client-facing billable work. Team members are perpetually busy, and it’s difficult to secure dedicated, consistent project time. This reality inevitably leads to projects taking much longer than anticipated and requires a pragmatic approach to scheduling and resource allocation.

The Human Factor: Learning Curves and Measuring Success

A new, more efficient system isn’t immediately an improvement for everyone. Experienced engineers who are experts in the legacy system will face a significant learning curve. Their initial productivity may even decrease as they adapt, making their buy-in and feedback critical.

Furthermore, objectively measuring the success of these new processes is often infeasible without adding excessive overhead. Rather than trying to force quantitative metrics, the more effective approach is to aim for qualitative consensus. Gathering feedback through direct communication and surveys with the expert users—the testers themselves—is the most reliable way to gauge if the new system is truly an improvement.

Technical Hurdles and Phased Rollouts

No platform is a perfect solution. Any modernization effort will encounter limitations, bugs, and unexpected behavior in new tools, requiring either sacrifices in the desired workflow or creative workarounds. Because of these and other unanticipated issues, a “big bang” migration is extremely risky.

The recommended strategy is a phased, iterative rollout. This approach is not without its own pain points, as it can create a transitional “middle ground” where team members are using a mix of old and new processes. However, it is essential for risk management, as it allows the team to plan for and execute fallback plans, reverting to the old system when a new process fails or encounters a critical edge case.

Frequently Asked Questions (FAQ)

Why is Microsoft Word a bad choice for modern pentest reporting?

Microsoft Word is poorly suited for modern reporting because it treats reports as static, unstructured documents. This makes it a “nightmare” to programmatically parse data for analytics, requires heavy manual effort to maintain consistency (e.g., deleting highlighted guidance text), and locks valuable finding data in a format that cannot be easily queried or reused. Complex VBA macros and plugins used to overcome these limitations often create a brittle, unmaintainable system.

What is the main benefit of using a centralized data model like Microsoft Lists?

The main benefit is creating a single, structured source of truth for all engagement data. This eliminates data silos, reduces errors from manual copy-pasting, and enables automation. Once data is centralized, you can use tools like Power Automate to automate handoffs (e.g., from scoping to sales) and run analytics that were previously impossible, such as tracking DAST vs. manual finding efficacy or measuring scoping accuracy.

How do you migrate hundreds of finding templates from Word docs without manual data entry?

The key is to use custom scripting to automate the extraction process. The workflow involves developing scripts that can programmatically open each legacy Word document, parse the content from its different sections, and organize that data into a structured format like a CSV file. This CSV can then be imported directly into a modern database like Microsoft Lists, preserving the intellectual property without a massive, error-prone manual migration effort.

What’s the biggest non-technical challenge when modernizing these processes?

The biggest non-technical challenges are change management and resource allocation. For expert users, adapting to a new system involves a significant learning curve, and their initial productivity might dip. It’s crucial to gather their feedback to ensure the new process is a true improvement. In a consultancy, it’s also extremely difficult to balance internal project work with billable client engagements, which can significantly extend project timelines.

Conclusion

Modernizing the application penetration testing lifecycle is not merely about adopting new tools; it’s a strategic shift from a fragmented, document-based workflow to a cohesive, data-centric system. By diagnosing the inefficiencies of legacy processes rooted in Word and Excel, we can build a strong business case for change. The journey involves adopting a modern reporting platform like PlexTrac for its collaborative and platform-agnostic capabilities, centralizing all engagement data in a structured database like Microsoft Lists, and leveraging low-code tools like Power Automate to eliminate manual, error-prone tasks.

While the path includes technical hurdles, project management challenges, and a necessary learning curve for the team, the outcome is a more efficient, scalable, and data-driven security program. This transformation frees up highly skilled engineers from administrative tedium, enables powerful analytics, and ultimately elevates the quality and consistency of the entire security engagement process.

Tools & Other References:

• PlexTrac - Penetration Test Reporting & Management Platform
• Microsoft Power Platform Official Documentation
• The OWASP Application Security Verification Standard (ASVS)