AI-assisted, not AI-trusted.
GK Data uses custom AI agents for reconnaissance, signal correlation, and documentation strategy. That does not replace human security work. Validation, exploit reasoning, impact analysis, and reporting decisions stay manual.
Operating Principles
Automation is useful for organizing signal. Security decisions still need hands, evidence, and judgment.
AI-Assisted Recon
Custom agents help map assets, compare patterns, organize notes, and document testing strategy so manual effort lands where it matters.
Manual Validation
Every meaningful issue is reproduced, reviewed, and impact-tested by a human before it becomes a finding.
Evidence-Led Reporting
Reports prioritize proof, reproduction, risk, and remediation instead of vague scanner output or inflated severity.
Fix Verification
When included in scope, fixes are retested so teams know whether the original exposure is actually resolved.
Engagement Flow
A simple workflow keeps the work pointed at useful outcomes instead of noise.
Scope
Define targets, access, exclusions, timelines, reporting expectations, and communication rules.
Recon
Use manual research and custom agents to map assets, roles, workflows, integrations, and likely attack paths.
Test
Perform hands-on offensive testing across web, API, mobile, network, cloud, and website surfaces.
Report
Deliver concise findings with reproduction steps, evidence, impact, risk, and remediation guidance.
Verify
Retest fixes when included so the team knows whether the issue is resolved.
No AI Slop
AI can accelerate organization and recon. It cannot be allowed to invent findings, skip proof, or replace exploit validation.
What AI helps with
Asset clustering, note cleanup, pattern comparison, test-plan drafting, documentation structure, and keeping long investigations readable.
What stays human
Exploit reasoning, reproduction, impact testing, severity judgment, client-facing claims, and every final report recommendation.
Want the testing to be practical, documented, and human-verified?