Case Studies

Context

A new Kubernetes-hosted payment gateway was approaching production with no formal threat model. Regulatory requirements mandated a documented risk assessment before go-live.

Approach

Facilitated a 3-session threat modeling workshop using STRIDE taxonomy. Created data-flow diagrams across 8 microservices, identified trust zones, and modeled 40+ threats. Scored and prioritized by DREAD methodology.

Impact

Identified 3 critical permission scope violations prior to deployment. Required implementation of mutual TLS between services and scoped RBAC roles, preventing potential privilege escalation paths.

Context

Engineering teams were shipping container images and third-party dependencies without any automated security gates, creating supply-chain risk.

Approach

Designed a multi-stage security pipeline integrating Trivy for container image scanning, OWASP Dependency-Check for SCA, and Gitleaks for secrets detection. Built a centralized SARIF reporting layer feeding into GitHub Security tab.

Impact

Achieved 100% coverage of container registries. Automated detection of 200+ vulnerable dependencies in Q1, with remediation SLAs enforced programmatically via PR labels and Jira integration.

Context

An internal REST API powering a SaaS platform was flagged for security review before a major enterprise customer audit.

Approach

Performed black-box API penetration testing using Burp Suite Pro and custom Python scripts. Focused on authentication flows, JWT handling, BOLA/BFLA, and rate-limiting controls.

Impact

Discovered a critical authentication bypass via JWT algorithm confusion (CVE-class). Delivered a technical report with proof-of-concept, CVSS scoring, and a step-by-step remediation guide. Issue was patched and re-tested within 72 hours.

Context

Traditional security training often fails because it's disconnected from the actual coding process. Developers need security guidance *at the moment* they are writing code.

Approach

Integrated a custom LLM-based security advisor into VS Code and IntelliJ via a private extension. The assistant monitors the active file and suggests security improvements as the developer types.

Impact

Adopted by 200+ engineers. Post-implementation data showed a 30% reduction in 'Insecure Design' findings during architecture reviews.

Context

Traditional DAST scanners often fail to identify deep business logic issues (like BOLA) because they lack understanding of the application's state and multi-step workflows.

Approach

Engineered a custom API scanner that uses Reinforcement Learning (RL) to explore API endpoints. The tool dynamically generates payloads based on previous responses, effectively 'learning' how to navigate the API to find vulnerabilities.

Impact

Identified 3 critical Broken Object Level Authorization (BOLA) flaws and 2 complex multi-step auth bypasses that were missed by standard automated tools.

Context

After deploying SonarQube across 50+ repositories, the security team was overwhelmed with over 5,000 findings, many of which were low-risk or false positives.

Approach

Built an AI-assisted triage agent that consumes findings via API, analyzes the surrounding code context and data flow, and assigns a 'Probability of Exploitability' score.

Impact

Automated the triage of 85% of incoming SAST findings. Reduced the security team's manual triage effort from 20 hours/week to just 2 hours/week, allowing them to focus on complex, high-impact vulnerabilities.

Context

Engineering teams were shipping code faster than the security team could manually review, leading to a bottleneck in the PR process and occasional security debt.

Approach

Developed an in-house AI linting agent that integrates with GitHub/GitLab. The agent uses a fine-tuned LLM to analyze code diffs, identify potential security flaws (like insecure use of cryptographic primitives or hardcoded secrets), and provide contextual remediation advice.

Impact

Reduced manual PR security review time by 60% and caught 40+ high-risk vulnerabilities before they reached the main branch. Improved developer awareness by providing instant feedback during the development cycle.