Secure the Code. Secure the Pipeline. Ship With Confidence.
From code commit to cloud deployment, we embed security into every stage of the software delivery lifecycle. AI-native scanning catches what traditional tools miss, policy-as-code enforces guardrails at pipeline speed, and supply chain verification ensures the integrity of every dependency, container, and artifact you ship.
Code Ships Faster Than Security Can Keep Up
Engineering teams deploy dozens of releases per week. AI copilots accelerate output further. Security reviews happen after the fact, if at all. The gap between delivery velocity and security coverage is widening, and attackers are exploiting it.
Vulnerable Dependencies and Supply Chain Risk
Every application depends on open source libraries and third-party components. Developers inherit hundreds of transitive dependencies without understanding the security posture of each one. A single compromised package can cascade across your entire codebase. Supply chain attacks have become a primary vector: dependency confusion, typosquatting, and abandoned projects with known CVEs live in production codebases. Without automated supply chain verification, organizations cannot guarantee the integrity of the code they ship.
AI-Generated Code Outpaces Security Review
AI-generated code ships faster than security teams can review. Copilot-written code bypasses traditional review gates, introduces novel vulnerability patterns, and creates dependencies on AI-suggested packages that may not be vetted. LLM-generated code inherits training data biases, reproduces known-vulnerable patterns, and hallucinates package names that could become typosquatting targets. Traditional SAST tools were not built to detect AI-specific vulnerability signatures, and pattern-matching scanners lack the semantic understanding to evaluate business logic in AI-generated output.
Pipeline Velocity Versus Security Review
Engineering teams deploying multiple times per day cannot wait for manual security review cycles that take days or weeks. The result is a growing backlog of unreviewed changes shipping to production, or security becoming a bottleneck that slows delivery to a crawl. Neither outcome is acceptable. Organizations need automated security gates that operate at pipeline speed without introducing friction that drives developers to bypass controls entirely.
Secrets Exposure and IaC Misconfigurations
API keys, database passwords, and cloud credentials get committed to version control daily. Even after removal, secrets persist in Git history forever. The same pattern extends to infrastructure as code: Terraform modules, CloudFormation templates, and Kubernetes manifests define production infrastructure, but most teams lack automated scanning for security misconfigurations. Publicly accessible storage buckets, overly permissive IAM roles, and unencrypted databases ship to production because IaC security review happens after deployment, if it happens at all.
8 Pillars of Application Security.
From dependency analysis to AI-powered testing, our framework secures the entire software delivery lifecycle, covering code, pipelines, infrastructure, and AI-assisted development workflows.
Software Composition Analysis
Continuous SCA scanning across all dependencies, transitive and direct. We identify vulnerable packages, outdated libraries, and license compliance issues. SBOM generation supports vendor supply chain audits and build provenance attestation.
Static Application Security Testing
Deploy SAST scanning integrated into your CI/CD pipeline to catch vulnerabilities before code merge. We configure scanning for your tech stack, tune for your codebase patterns, and prioritize findings by exploitability. AI-powered SAST adds semantic analysis that understands business logic and detects context-dependent vulnerabilities that pattern-matching scanners miss.
DAST and API Security
Runtime vulnerability scanning against deployed applications and APIs. DAST detects exploitable flaws that static analysis misses: authentication bypass, authorization gaps, and session management weaknesses. We map API inventory, enforce authentication and authorization, apply rate limiting, and detect exploitation attempts with behavioral analytics.
Secrets Detection and Rotation
Real-time scanning of code repositories, CI/CD logs, and infrastructure as code to detect exposed credentials. We implement automated secret rotation, credential vault integration, and pre-commit hooks that prevent secrets from entering version control in the first place.
Infrastructure as Code Security
Scan Terraform, CloudFormation, Kubernetes manifests, and Helm charts for security misconfigurations before deployment. Enforce organization-wide IaC policies through automated pull request checks and CIS benchmark validation across AWS, Azure, and GCP environments.
Pipeline Security and Policy as Code
Harden CI/CD pipelines against injection attacks, credential exposure, and unauthorized modifications. Implement branch protection, signed commits, and pipeline integrity verification. Define security policies in code using Open Policy Agent, Sentinel, or custom frameworks, enforced automatically at build time, deploy time, and runtime.
Container and Supply Chain Security
Scan container images for vulnerabilities, enforce base image policies, and validate runtime configurations. Implement admission controllers that prevent non-compliant images from deploying to production clusters. Verify dependency provenance, enforce license compliance, and generate software bills of materials with artifact signing across all pipelines.
AI Code Security and DevSecOps Integration
Scanning and validating AI-generated code from copilots, code generators, and LLM-powered development tools. We detect AI-introduced vulnerability patterns, hallucinated package references, and insecure code suggestions. Security gates are embedded into AI-assisted development workflows, with policy checks on AI-generated pull requests and guardrails ensuring AI tools operate within your security and compliance boundaries.
From Assessment to AI-Powered Assurance
Every organization starts somewhere. Our maturity model gives you a clear path from initial gap analysis to continuous, AI-aware security assurance across code, pipelines, and infrastructure.
Assessment and Gap Analysis
Security posture is unknown. No automated scanning, no dependency inventory, and no secrets management policy. CWS conducts a full codebase and pipeline audit, maps the attack surface, and identifies the highest risk gaps across your SDLC and CI/CD infrastructure.
AppSec Assessment
- Codebase and pipeline security audit
- Dependency risk inventory
- Secrets exposure scan
- SDLC and IaC gap analysis
Tooling and Pipeline Integration
SAST, SCA, IaC scanners, and secrets detection tools are deployed into CI/CD pipelines. Scanning runs on every commit and pull request. Container images are scanned before registry push. Findings are triaged and prioritized by severity. Developers receive baseline security training and remediation playbooks.
Pipeline Integration
- SAST, SCA, and IaC pipeline deployment
- Secrets detection in CI/CD and pre-commit hooks
- Container image scanning and dependency inventory
- Vulnerability triage and prioritization workflow
Enforced Secure SDLC
Security gates block risky merges automatically. Policy-as-code governs what ships to production. IDE plugins surface findings in real time. SBOM generation, API security enforcement, supply chain verification, and automated remediation guidance are standard across all teams and pipelines.
Security Governance
- Merge-blocking security policies
- Policy-as-code enforcement at build and deploy time
- API security enforcement and SBOM tracking
- Supply chain verification and artifact signing
AI-Powered Continuous Assurance
Security is woven into architecture, design, and AI-assisted workflows. Autonomous AI code review validates copilot output. AI-powered vulnerability prediction identifies risks before code is written. Self-healing pipelines automatically remediate common findings, and continuous AI model security assessment ensures LLM-powered tools operate within compliance boundaries.
Managed AppSec Operations
- Autonomous AI code review and validation
- AI-powered vulnerability prediction
- Self-healing pipeline remediation
- Automated compliance reporting with AI audit trails
Where Partners Apply This First
These are the three most common entry points for VARs, distributors, and ISVs building application security practices for their customers.
Financial Services SAST Enablement
A $500M fintech company built and deployed banking APIs with no security scanning in CI/CD. We integrated Snyk and SonarCloud into their GitLab pipeline, tuned scanning rules for their Python and Go codebases, and trained developers on remediation. Within 3 months, they remediated 847 vulnerabilities across 89 microservices.
- 847 vulnerabilities remediated pre-production
- 99.8% CI/CD security gate pass rate
- Zero code-based incidents in 12 months
Supply Chain Security After a Dependency Incident
After a compromised npm package affected their build pipeline, a software company engages CWS to implement comprehensive supply chain controls. We deploy dependency verification, artifact signing, SBOM generation, and build provenance attestation. Every dependency is verified against known-good checksums before builds proceed.
- Full software bill of materials for every release
- Automated blocking of known-compromised packages
- Build provenance attestation meeting SLSA Level 3
AI SAST and DAST Catching What Traditional Scanners Miss
A platform company using AI coding assistants across 200 developers discovers that traditional SAST tools miss context-dependent vulnerabilities in AI-generated code. We deploy AI-powered SAST that understands business logic and AI DAST that generates intelligent attack scenarios. The AI scanners identify broken access controls, insecure data flows, and logic flaws that pattern-matching tools consistently overlook.
- Up to 40% more critical vulnerabilities detected versus traditional SAST
- AI DAST generating context-aware attack scenarios for each application
- Mean time to remediation reduced through AI-generated fix suggestions
Explore Specific Engagements
These service pages detail the specific engagement types available within this program.
Make Secure Code and Pipelines the Default.
Embed security into development workflows and delivery pipelines. Catch vulnerabilities before they reach production, from first commit to final deployment.
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