TelhawkTELHAWK
Solutions · AI Agents

AI Agent Security Validation

Prove, prioritize, remediate, and validate security findings across AI agents, MCP servers, tools, connectors, and agent frameworks.

Vendor-neutral by design

Telhawk works across frontier AI systems.

Autonomous AI agents create new authorization, tool-use, and prompt-injection risks. Telhawk and Galen© produce proof-backed evidence and validated remediation across agent frameworks.

Telhawk is not tied to any single model vendor. We help validate, remediate, and document security findings across GPT-5.5, Claude Mythos, Fable 5, Gemini, open-source models, and autonomous AI agents.

Common security challenges

Expanded access surface
Each connected tool or data source becomes part of the agent's authorization model.
Prompt injection
Untrusted content can influence which tools the agent calls and with what arguments.
Excessive autonomy
Sensitive actions may be reachable without explicit human approval gates.
Tool-call accountability
Logs may be incomplete, making attribution and review difficult.
Cross-tenant exposure
Shared tools can leak data between customers without strict scoping.
Validation across runs
Agent behavior can drift; fixes need re-evaluation, not point-in-time review.
From overload to validated outcomes

AI-generated findings overload is the new bottleneck.

Modern AI security tools can generate thousands of findings. Without proof, prioritization, remediation context, and validation, those findings turn into a backlog instead of an outcome.

Validation and remediation workflow

  1. 1Ingest findings from AI scanners, audits, agents, and existing tools.
  2. 2Galen© attaches proof: code paths, data flows, missing guards, and permissions.
  3. 3Findings are prioritized by exploitability and business impact.
  4. 4Remediation guidance is generated with contextual fix recommendations.
  5. 5Corrections are validated to confirm the vulnerable path is closed.
  6. 6Audit-ready evidence packages are produced automatically.

Evidence generation and audit readiness

Proof-backed findings tied to specific code and data paths
Prioritized remediation queue with exploitability context
Validated fixes with before-and-after evidence
Exportable audit-ready reports
Finding history and remediation timeline
Coverage across models, agents, APIs, and code

Weeks or months of work, completed in hours.

Telhawk and Galen© turn raw AI findings into proof-backed, prioritized, remediation-ready outcomes with validation and audit-ready evidence.

Talk to an Expert See How Galen© Works