Developer AI risk is not limited to a single coding assistant. It can emerge across integrated development environments, browser-based tools, repositories, CI/CD pipelines, command-line workflows, model APIs, plugins, and third-party development platforms.
Developers may submit proprietary code, credentials, architecture details, customer information, or internal documentation to external AI services. AI-generated code may also introduce insecure dependencies, vulnerable patterns, licensing concerns, or unverified output into production workflows.
Existing application security and code-scanning tools typically evaluate code after it has been written or committed. They do not always show which AI tool generated or modified the code, what information was submitted to that tool, which external models were involved, or whether the activity was approved.
AI now operates across employee tools, developer environments, SaaS platforms, embedded features, third-party vendors, and autonomous agents. Without continuous exposure management, organisations cannot reliably see what AI is running, what data and systems it can access, what it costs, or whether appropriate ownership and controls are in place.
Traditional governance programmes often depend on questionnaires, spreadsheets, policy documents, and periodic reviews. Veranthios creates a continuously updated operational record of AI activity, ownership, exposure, cost, controls, decisions, and evidence across the enterprise.
Veranthios converts live governance activity into defensible evidence, including AI inventories, ownership records, risk assessments, approvals, control status, remediation activity, and audit trails. This gives boards, auditors, regulators, and customers a clearer view of enterprise AI exposure.
Veranthios continuously identifies AI-assisted development activity across coding tools, repositories, CI/CD workflows, plugins, APIs, and developer platforms. It creates a live view of where AI is being used, which services developers are interacting with, and where sensitive engineering information may be exposed.
Identify approved and unapproved AI coding tools, assistants, extensions, APIs, and connected development services.
Map AI activity across repositories, development environments, CI/CD pipelines, and software delivery workflows.
Veranthios evaluates developer AI exposure according to data sensitivity, credential exposure, repository importance, tool approval status, development context, and potential blast radius. Security and engineering teams can assign ownership, prioritise remediation, and apply governance without blocking productive developer workflows.
Surface where API keys, secrets, proprietary code, or sensitive engineering data may have entered external AI systems.
Prioritise high-risk activity based on repository criticality, data sensitivity, business impact, and governance exposure.
Veranthios records the AI tools involved, affected repositories and workflows, exposed information, accountable owners, risk decisions, and remediation actions. This creates a defensible record for security reviews, compliance assessments, executive reporting, and customer assurance.
Maintain evidence of developer AI activity, detected exposure, ownership decisions, and remediation status.
Give development teams actionable findings while providing security, risk, and leadership with a clear view of enterprise exposure.