TelhawkTELHAWK
Proof-backed AI security

Turn AI security findings into validated fixes.

For code, APIs, AI agents, and AI-generated software.

AI can generate more findings than teams can triage. Telhawk's Galen engine helps prove what is real, prioritize what matters, guide remediation, and validate that corrections worked.

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Find the risk.·Prove it.·Prioritize it.·Help fix it.·Validate the correction.
The Galen Proof Pipeline
Inputs
Code · APIs · AI agents · AI-generated software · existing AI findings
Galen proof engine
Galen Proof Engine
Maps the evidence behind the risk
Code pathData flowMissing guardPermissionsFix context
AI / LLM layer
AI Security Review
LLMs reason over structured evidence, not disconnected raw inputs
Focused contextEvidence packageRisk reasoning
Proof + Guidance
Proof-backed finding with remediation direction
Validation
Corrected issue reviewed and confirmed
Validated fix

Galen gives AI security review the structured evidence it needs to move from possible findings to proof-backed outcomes.

The AI security bottleneck

AI findings can cost millions to prove, fix, and validate.

AI security tools can generate thousands of findings, but generating findings is only the beginning. Every result still requires review, proof, prioritization, remediation, validation, and documentation. Telhawk uses Galen to transform raw AI findings into proof-backed, prioritized, remediation-ready outcomes with validation and audit-ready evidence—reducing work that traditionally takes weeks or months to just hours.

Finding overload
AI audit tools can generate thousands of findings, including speculative, duplicate, or low-value issues.
Expensive human review
Every result still needs people to decide whether the issue is real, exploitable, and worth fixing.
Developer staffing burden
Companies may need more developers and security engineers just to review, fix, retest, and document AI-generated findings.
Remediation backlog
Large finding volumes can turn into months of engineering work before the business sees validated security improvement.
Validation uncertainty
A suggested fix is not the same as a validated fix. Teams still need to prove the risky path was actually closed.
Audit documentation gaps
Security leaders need durable proof, remediation records, and validation status — not screenshots, chat logs, or raw AI output.

Turn Thousands of AI Findings Into Validated Outcomes in Hours

Hours, not weeks
Without Telhawk
The traditional grind
  • AI scanner generates thousands of findings
  • Security teams manually review results
  • Engineers investigate and prioritize issues
  • Developers build and test fixes
  • Teams manually validate remediation
  • Audit evidence is collected and documented
Weeks or months
With Telhawk + Galen
Proof-backed, validated outcomes
  • Findings are automatically correlated and prioritized
  • Evidence and exploitability are validated
  • Remediation recommendations are generated
  • Fixes are verified through automated validation
  • Audit-ready evidence packages are created
  • Results are tracked and documented automatically
Completed in hours

AI tools generate findings. Telhawk delivers validated remediation and audit-ready proof.

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Vendor-neutral coverage

Built for Frontier AI Systems

Telhawk helps organizations validate, remediate, and document security findings across frontier AI systems including GPT-5.5, Claude Mythos, Fable 5, Gemini, open-source models, and autonomous AI agents. Telhawk works across frontier AI systems, agent frameworks, and enterprise AI deployments — not tied to any single model vendor.

GPT-5.5Compatible
Claude MythosCompatible
Fable 5Compatible
GeminiCompatible
Open-source modelsCompatible
Autonomous AI agentsCompatible

Looking for cross-vendor coverage? See Frontier LLM Security Testing →

The Telhawk difference

Most tools produce alerts. Telhawk produces evidence.

Galen is designed to provide the proof behind a finding: the affected code path, security-relevant data flow, missing guard or control, remediation context, and validation status after correction.

01
Vulnerable path identified

Galen pinpoints the affected route, handler, or agent action.

02
Proof attached

Code path, data flow, missing guard, and permission boundary are bound to the finding.

03
Fix guidance provided

A concrete, contextual remediation recommendation accompanies the proof.

04
Correction validated

Galen re-evaluates the corrected code to confirm the vulnerable path is closed.

Why Galen makes AI better

A smarter AI still needs better evidence.

An LLM can read code, explain logic, suggest vulnerabilities, and generate remediation ideas. But alone, it may miss relationships across routes, handlers, permissions, data flows, and guard conditions. Galen gives AI security workflows structured proof so the task becomes focused and verifiable.

Raw LLM prompt

"Review this codebase and find security issues."

Telhawk-enhanced prompt

"Here is the vulnerable route, data path, dangerous input, missing authorization guard, sensitive operation, recommended remediation, and corrected version. Determine whether the vulnerable path remains."

That is a fundamentally different problem.

Commercial offerings

Choose the Galen workflow that fits your team.

Galen Managed Security Audit
Telhawk runs the audit for you.

Expert-led audits for code, APIs, AI agents, access paths, data flows, remediation, and validation. Best for high-stakes reviews, enterprise requirements, diligence events, and teams that want a completed security outcome.

Explore Managed Audit
Galen Direct Security Audit
Your team runs Galen directly.

Secure portal, repository, API, or workflow access to Galen-powered audits for developers, AppSec teams, SaaS companies, and enterprises.

Explore Direct Audit
Galen AI Code Generator Application
Security review inside AI coding workflows.

Galen reviews AI-generated or AI-modified code before it reaches the developer, repository, pull request, or production pipeline.

Explore Code Generator Security
Galen Partner-Delivered Security Audit
Partners deliver Galen-powered audits.

MSPs, MSSPs, consultancies, platforms, and resellers can offer proof-backed AI security audits without building their own analysis engine.

Explore Partner Model
Security surfaces

Built for modern software risk.

Application Code

Routes, handlers, guards, and sensitive operations.

APIs and Endpoints

Authorization, tenancy, and input validation.

AI Agents

Tools, permissions, prompts, and operational behavior.

Access & Permission Paths

Role boundaries and privilege escalation paths.

Data Flows

Sensitive data movement across services and storage.

Remediation & Fix Validation

Confirm corrected code actually closes the vulnerable path.

Production-Designated Code Versions

Targeted review of the code intended for release.

AI-Generated Code

Review of code drafted by AI coding tools and agents.

Embedded validation

Cleaner AI-generated code before developers accept it.

  1. 1Developer asks AI coding tool to build or modify code.
  2. 2AI code generator drafts the code.
  3. 3Galen reviews the generated or modified code.
  4. 4Galen returns proof-backed findings.
  5. 5AI generator or developer remediates the issue.
  6. 6Galen validates the corrected code.
  7. 7Developer receives cleaner, security-reviewed code.
Example

A developer asks an AI coding tool to create a customer invoice endpoint. Galen identifies that the endpoint checks login but does not verify customer ownership. Galen returns the vulnerable route, dangerous parameter, missing guard, and recommended tenant-scoped correction. The issue is fixed and validated before the developer accepts the final code.

From findings to results

Security progress requires more than discovery.

Proof-backed findings
Prioritized risk
Remediation guidance
Proposed corrections
Validation after fixes
Exportable reports
Audit-ready evidence
Finding history

Do not spend months sorting through AI security findings.

Let Galen and Telhawk help turn the findings that matter into proof, remediation, and validated fixes.

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