What is shadow AI and why is it a security risk?

Shadow AI refers to employees using unauthorized AI tools on company code and data without IT or security team approval. It is a security risk because proprietary code, customer data and intellectual property may be sent to third-party AI services without encryption, access controls or data processing agreements in place.

How much does an enterprise AI coding security assessment cost?

Comprehensive enterprise assessments start at $12,000 CAD. This covers policy review, supply chain analysis, code audits across multiple repositories, compliance mapping and remediation planning. Ongoing monitoring and quarterly reassessments are available on custom retainer agreements.

Can AI-generated code pass SOC 2 compliance?

AI-generated code can pass SOC 2 compliance, but it requires additional controls that AI tools do not implement by default. These include audit logging, access control enforcement, encryption at rest and in transit, change management documentation and vulnerability management processes. A security assessment identifies the specific gaps that need to be addressed.

Should we ban AI coding tools or secure them?

Banning AI coding tools is impractical in 2026. Developers will use them regardless, creating shadow AI risk that is harder to manage than sanctioned usage. The recommended approach is to establish approved tools, configure them within your security perimeter, create usage policies and implement audit processes for AI-generated code.

What compliance frameworks apply to AI-generated code?

The same compliance frameworks that apply to human-written code apply to AI-generated code: SOC 2, PIPEDA, GDPR, HIPAA, PCI DSS and ISO 27001 among others. The code's origin does not change regulatory requirements. However, AI-generated code introduces additional considerations around data processing agreements with AI tool providers, intellectual property ownership and auditability of code changes.

Enterprise Security

AI Coding Security for Enterprise Teams

Your developers are using AI to write code. Who is auditing the output?

Sherlock Forensics provides enterprise AI coding security assessments for organizations mandating AI coding tools. Services cover shadow AI risk assessment, supply chain security, intellectual property leakage prevention, compliance mapping (SOC 2, PIPEDA, GDPR) and ongoing monitoring. Comprehensive assessments from $12,000 CAD with custom retainers for ongoing engagements. Over 20 years of security experience. Contact 604.229.1994.

Major corporations are mandating AI coding tool usage to boost developer productivity. The security implications are significant. Shadow AI, supply chain poisoning, IP leakage and compliance gaps create risk that traditional application security programs do not address.

Scope an Assessment See the Framework

The Risk Landscape

Corporate AI Coding Risks

Shadow AI

Developers are using AI coding tools you did not approve on codebases you did not authorize. Proprietary code is being sent to third-party AI services without data processing agreements, encryption controls or audit trails. Your security perimeter has a gap you cannot see.

Supply Chain Poisoning

AI coding tools hallucinate package names that do not exist. Attackers register these phantom packages with malicious code. When another developer follows the same AI suggestion, they install the attacker's package. This is happening at scale across npm and PyPI.

IP Leakage

Every prompt sent to an AI coding tool includes context from your codebase. Proprietary algorithms, business logic, infrastructure configurations and customer data patterns are transmitted to third-party servers. Your competitive advantage may be in someone else's training data.

Compliance Gaps

AI-generated code does not comply with SOC 2, PIPEDA, GDPR or HIPAA by default. Audit logging, encryption at rest, consent management and data retention policies are not included unless specifically requested. The compliance gaps compound across every AI-generated component.

Code Quality Degradation

AI-generated code optimizes for functionality, not maintainability. Technical debt accumulates faster when developers accept AI suggestions without review. Security vulnerabilities hide in code that no human fully understands because no human wrote it.

Accountability Gaps

When AI generates vulnerable code and a breach occurs, who is responsible? The developer who accepted the suggestion? The team lead who approved the PR? The CISO who approved the tool? Existing incident response and accountability frameworks do not address AI-generated code.

Enterprise Framework

Five-Pillar AI Coding Security Framework

1. Policy

Establish approved AI tools, define acceptable use boundaries, create data classification rules for AI tool usage and document intellectual property handling. Policy must address which repositories can use AI assistance and which contain restricted IP.

2. Process

Implement mandatory code review for AI-generated changes, require security-focused prompts in AI tool configurations, establish dependency verification workflows and create incident response procedures specific to AI-introduced vulnerabilities.

3. Tools

Deploy AI coding tools within your security perimeter where possible. Configure enterprise versions with data retention policies. Implement SAST and SCA scanning in CI/CD pipelines. Add dependency verification gates that block hallucinated packages.

4. Testing

Conduct regular security assessments of AI-generated code. Include AI-specific test cases in penetration testing engagements. Audit for the vulnerability patterns that AI tools commonly introduce: broken access control, injection flaws, hardcoded secrets and missing input validation.

5. Training

Train developers on secure AI coding practices. Teach them to write security-aware prompts, verify AI suggestions before accepting them, recognize common AI coding vulnerabilities and use the security prompt library as a standard part of their workflow.

Pricing

Enterprise Engagement Options

Comprehensive AI Coding Security Assessment - $12,000 CAD: Full assessment across all five framework pillars. Includes policy review, shadow AI discovery, supply chain analysis, code audits across up to 10 repositories, compliance gap analysis (SOC 2, PIPEDA, GDPR mapping), developer training session and a prioritized remediation roadmap. Delivered in 3-4 weeks.
Ongoing Security Retainer - Custom: Quarterly reassessments, continuous monitoring of AI tool configurations, monthly dependency audits, on-demand code reviews for critical AI-generated changes and priority incident response. Scoped based on team size, repository count and compliance requirements.

Frequently Asked Questions

Enterprise AI Security FAQs

What is shadow AI and why is it a security risk?: Shadow AI refers to employees using unauthorized AI tools on company code and data without IT or security team approval. It is a security risk because proprietary code, customer data and intellectual property may be sent to third-party AI services without encryption, access controls or data processing agreements in place.
Can AI-generated code pass SOC 2 compliance?: Yes, but it requires additional controls that AI tools do not implement by default. These include audit logging, access control enforcement, encryption at rest and in transit, change management documentation and vulnerability management processes.
Should we ban AI coding tools or secure them?: Banning is impractical. Developers will use them regardless, creating shadow AI risk that is harder to manage than sanctioned usage. The recommended approach is to establish approved tools, configure them within your security perimeter, create usage policies and implement audit processes for AI-generated code.
What compliance frameworks apply to AI-generated code?: The same frameworks that apply to human-written code: SOC 2, PIPEDA, GDPR, HIPAA, PCI DSS and ISO 27001. The code's origin does not change regulatory requirements. However, AI-generated code introduces additional considerations around data processing agreements with AI tool providers and auditability.
How quickly can you start an enterprise assessment?: We can begin scoping within 48 hours of initial contact. The full assessment typically takes 3-4 weeks depending on the number of repositories, team size and compliance requirements. We work with your existing security team and do not require administrative access to production systems.

Enterprise Ready

Secure your AI coding pipeline before the next audit.

Comprehensive assessments from $12,000 CAD. Custom retainers for ongoing coverage.

Schedule a Call

Scope Your Enterprise Assessment

Tell us about your team size, tech stack, compliance requirements and AI tool usage. We will scope an assessment that fits your organization.

Call 604.229.1994

Phone: 604.229.1994
Burnaby Office: Burnaby, BC, Canada
Coquitlam Office: Coquitlam, BC, Canada
Assessment Timeline: 3-4 weeks from engagement start