Security
Security, integrity, and accountable AI
Wild Eye AI builds AI-native systems for consequential work in law, technology, and science. Security is integral to how we design, evaluate, and improve those systems.
Our approach brings conventional application security together with AI-specific assurance. We focus on authorized access, secure development, data boundaries, controlled system behavior, vulnerability management, human oversight, and verifiable remediation.
Security leadership
Henry V. Alfano
Founder and CEO, Security Lead
Henry V. Alfano is accountable for the security of Wild Eye AI systems and the Fortress Evidence Intelligence Platform. He directs the company’s security posture, authorization boundaries, vulnerability-management practices, incident response, remediation priorities, and verification activities.
Restricted frontier security capabilities
Wild Eye AI maintains Trusted Access to restricted frontier AI security capabilities for authorized defensive work. These capabilities support vulnerability analysis, secure-code review, AI application assurance, and remediation validation within explicitly defined authorization boundaries.
Access is subject to provider verification, usage restrictions, monitoring, and continuing eligibility requirements. Wild Eye AI applies these capabilities under accountable human oversight, documented scope, and responsible security practices.
Our security approach
Secure development
Security considerations are incorporated into system architecture, implementation, review, and change management. We evaluate code, configurations, dependencies, interfaces, and data flows according to the sensitivity and intended use of each system.
Access and data boundaries
Systems should access only the information and capabilities necessary for their authorized purpose. We evaluate identity, permissions, tool access, data handling, and escalation boundaries to reduce unauthorized access or disclosure.
AI application assurance
AI-enabled systems introduce risks beyond conventional software vulnerabilities. Our assurance work examines agent authorization, tool boundaries, prompt-injection exposure, unintended data disclosure, evidence integrity, human approval requirements, and the ability to reconstruct consequential system activity.
Vulnerability management
Potential vulnerabilities are documented, triaged, and evaluated according to their likelihood, impact, and affected systems. Remediation is prioritized and fixes are verified before findings are considered resolved.
Incident response and remediation
Security concerns are assessed through a defined escalation and response process. Our objective is to contain potential harm, preserve relevant evidence, correct underlying causes, and verify that remediation is effective.
Systems and authorization scope
Wild Eye AI’s security function covers systems owned or operated by Wild Eye AI, including its legal evidence-intelligence platform currently known as Fortress.
Work involving client or third-party systems is performed only under explicit written authorization defining the systems, scope, permitted activities, and responsible parties.
Our defensive security work includes vulnerability triage and verification, secure-code and configuration review, evaluation of agent authorization and containment controls, analysis of prompt-injection and data-exposure risks, remediation guidance, and verification of fixes.
Responsible security reporting
We welcome good-faith reports concerning potential security issues in systems owned or operated by Wild Eye AI.
Before submitting a report:
- Do not test Wild Eye AI systems without explicit authorization.
- Do not access, modify, retain, or disclose another person’s information.
- Do not disrupt service availability or degrade system performance.
- Include sufficient detail for us to understand and reproduce the issue.
- Allow reasonable time for investigation and remediation before making information public.
Use the Security Contact form to submit a concern. Wild Eye AI will review the report, assess its potential impact, and coordinate appropriate next steps.
Security inquiries should be handled through the Security Contact form.
Trustworthy AI requires more than model capability. It requires disciplined controls, defined accountability, verifiable system behavior, and evidence that identified problems have been corrected.