Run Galen©-powered security audits directly.

Instead of waiting for a post-release scan, customer complaint, enterprise review, or incident, Galen© Direct helps bring proof-backed security review into the development process. Developers can use Galen© to understand whether a new route, API endpoint, permission change, AI-generated code block, or agent workflow creates a real security concern before it is merged or deployed.

Why Telhawk is important in the coding process

Modern development teams are writing code faster than ever, often with help from AI coding tools. That speed creates a new problem: more code, more changes, more AI-generated suggestions, and more opportunities for security issues to enter the application before anyone fully understands the risk.

Telhawk helps close that gap. Galen© Direct gives teams a proof-backed way to evaluate security risk during development, not just after deployment. It helps developers move from “this might be an issue” to a clearer understanding of the affected path, missing control, likely impact, recommended correction, and validation status after a fix is submitted.

The result is a stronger development workflow: faster coding, better security context, fewer unsupported findings, and more confidence before release.

During development

Developers can submit code paths, API routes, feature branches, AI-generated code, or agent workflows for review while the work is still in progress. Galen© helps identify security-relevant paths, missing controls, sensitive data exposure, weak access checks, risky permission changes, and remediation context earlier in the build cycle.

• Catch risky logic earlier before it becomes harder and more expensive to fix.
• Review AI-generated code before accepting it into the codebase.
• Understand affected paths instead of receiving disconnected scanner alerts.
• Spot missing guards such as authorization checks, tenant isolation, validation, approval gates, or data-access controls.
• Give developers remediation context so they know what needs to change and where.

Before pull request or merge

Before a pull request is merged, Galen© Direct can help teams review the security impact of the change. This is especially important when code modifies authentication, authorization, payment logic, admin functions, API behavior, database access, user roles, tenant boundaries, AI-agent permissions, or sensitive-data handling.

• Reduce security rework by identifying issues before merge.
• Give reviewers better context about what the change affects.
• Help developers document the security reasoning behind the correction.
• Support safer AI-assisted development by reviewing code that may have been produced or modified by LLMs.

Before production release

Before pushing code to production, Galen© Direct can help validate that high-risk paths, APIs, permission models, and agent behaviors have been reviewed and that submitted corrections appear to close the risky path. This gives teams stronger confidence before release without relying only on broad scanner output.

• Review production-designated code versions before deployment.
• Prioritize real risks instead of treating every possible finding the same.
• Validate corrected code or configuration after remediation is submitted.
• Create audit-ready evidence showing what was reviewed, what was found, what was fixed, and what validation status was assigned.

A customer submits a production-designated code version, API route, repository segment, or AI-generated code change for review. Galen© Direct helps analyze the security-relevant paths behind the request instead of treating the audit as a generic scan.

For a code or API review, Galen© may examine how a request enters the application, which handler processes it, what authentication or authorization checks are applied, what data is accessed or modified, and whether sensitive data, tenant boundaries, admin actions, or business-critical workflows are properly protected.

What Galen© looks for

• Affected code path — where the risky behavior begins and where it leads.
• API route or endpoint behavior — how requests are handled and what actions they can trigger.
• Authentication and authorization gaps — whether the user, role, tenant, or system is allowed to perform the action.
• Sensitive data exposure — whether protected data can be read, returned, logged, leaked, or modified.
• Missing guardrails — validation, access checks, rate limits, tenant isolation, or permission boundaries that should be present.
• Remediation context — what needs to change and where the correction should be applied.
• Validation status — whether a submitted correction appears to close the risky path.

A customer submits an AI agent workflow, tool-access design, prompt-handling flow, permissions model, or agent-generated code path for review. Galen© Direct helps evaluate whether the agent can reach systems, data, tools, files, APIs, or actions that create avoidable security risk.

For an AI agent review, Galen© may examine the agent's instructions, tool permissions, API access, user role boundaries, memory or file access, sensitive-data exposure, prompt-injection exposure, approval gates, logging behavior, and whether the agent can take actions beyond its intended scope.

What Galen© looks for

• Tool access risk — whether the agent can call tools, APIs, scripts, or systems with excessive authority.
• Prompt-injection exposure — whether untrusted content can influence the agent into unsafe behavior.
• Permission boundaries — whether the agent respects user, tenant, role, and workflow limits.
• Sensitive data handling — whether the agent can expose, summarize, transmit, log, or modify protected information.
• Unsafe autonomy — whether the agent can perform high-impact actions without review or approval.
• Agent-to-system paths — how the agent reaches databases, APIs, repositories, documents, files, or operational systems.
• Remediation and validation context — what should change and whether the updated agent configuration appears to reduce the risk.