Solutions · GPT-5.5

GPT-5.5 Security Validation

Prove, prioritize, remediate, and validate GPT-5.5–generated security findings — without being locked to any single AI vendor.

Vendor-neutral by design

Telhawk works across frontier AI systems.

Teams using GPT-5.5 for security analysis, code review, or agentic workflows often face thousands of raw findings. Telhawk and Galen© turn those outputs into proof-backed, validated security outcomes.

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

High finding volume

GPT-5.5 can surface large volumes of potential issues, many speculative or duplicate, overwhelming security review.

Missing exploit context

Raw LLM output rarely includes the code path, data flow, and missing guard that prove a finding is real.

Hallucinated vulnerabilities

Without grounding evidence, GPT-5.5 can produce confident but unverified security claims.

Remediation guesswork

Suggested fixes may not align with the actual route, framework, or permission model in use.

No validation loop

Without re-evaluation, teams cannot prove the vulnerable path was actually closed.

Audit gaps

Chat transcripts are not durable, structured evidence for regulators or customers.

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

1Ingest findings from AI scanners, audits, agents, and existing tools.
3Findings are prioritized by exploitability and business impact.
4Remediation guidance is generated with contextual fix recommendations.
5Corrections are validated to confirm the vulnerable path is closed.
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.