Empower engineering teams to use AI coding assistants without exposing source code, secrets, API keys, credentials, or proprietary IP. Netra gives security and engineering security teams visibility, audit context, and policy guardrails for modern AI-assisted development.
AI coding assistants can read large project context, accept copied snippets, summarize repositories, generate patches, and exchange development details through prompts and responses. Traditional network proxies and legacy DLP tools often miss what happens inside AI IDEs, browser sessions, and CLI context windows. That creates new paths for source code, proprietary algorithms, hardcoded API keys, credentials, internal architecture details, and regulated data to leave the engineering environment.
Netra helps technical security and engineering security teams monitor how AI coding tools are used, identify sensitive development data in prompts and responses, and audit activity when risky AI-assisted development workflows need investigation. Security teams can reduce data risk while allowing developers to keep the productivity gains of tools such as Cursor, GitHub Copilot, and Claude Code.
Developers may paste functions, logs, stack traces, configuration files, or architecture details into an assistant to debug faster.
API keys, tokens, credentials, private endpoints, and environment variables can appear inside code snippets, terminal output, or generated diffs.
Without prompt and response visibility, teams struggle to answer who used which assistant, what data was shared, and whether the activity requires follow-up.
See which AI coding assistants are being used, who is using them, and how often engineering workflows interact with AI IDEs, assistants, and CLI tools. Netra helps teams monitor prompts, responses, uploads, copied content, user context, and tool activity so security teams are not limited to basic traffic logs.
Go beyond basic traffic logs. Netra helps authorized teams review the context of interactions between developers and AI assistants, including the prompt, response, user, tool, and sensitive data findings. Investigators can reconstruct what happened, understand whether source code or secrets were exposed, and determine the right follow-up action.
Netra analyzes AI coding conversations and workflow context for proprietary source code, API keys, access tokens, credentials, private URLs, configuration details, PII, and other sensitive patterns. Teams can define custom rules for critical repositories, high-value IP, regulated data, or sensitive engineering groups so alerts focus on real data risk.
Financial services, fintech, and regulated engineering teams need to prove they can adopt AI responsibly without exposing trading logic, customer data, credentials, model code, or proprietary platforms. Netra supports risk-based guardrails and investigation workflows so teams can reduce AI coding data risk without relying on broad bans that slow development.
AI coding security is the practice of protecting source code, secrets, credentials, proprietary logic, and development context as engineering teams use AI coding assistants. It gives security teams visibility into prompts, responses, files, and data movement so teams can adopt AI-assisted development without creating unmanaged data exposure.
Netra is designed to help security teams monitor AI coding workflows across popular AI IDEs, assistants, and CLI tools, including Cursor, GitHub Copilot, and Claude Code, while keeping policies focused on the sensitive data and user activity that matter most.
Netra analyzes AI coding prompts, responses, and workflow context for source code, secrets, API keys, credentials, proprietary IP, and other sensitive patterns. Teams can define policies for their highest-risk data and investigate the interaction that triggered an alert.
Yes. Netra helps authorized security teams audit and investigate AI coding assistant activity by preserving prompt and response context, user activity, tool usage, and sensitive data findings for review.
Netra helps financial services and other regulated organizations reduce AI coding data risk by monitoring AI assistant usage, detecting sensitive code and credentials, supporting investigation workflows, and enabling guardrails without requiring broad bans on developer productivity tools.
Schedule a demo to see how Netra can protect your organization's data and prevent insider threats.