Going Beyond Regular Security Tests 

Our concierge model helps you test AI and LLM systems, simulate real-world intrusion paths, and investigate malware with minimal back and forth (just like your own team).
Speak to Your Concierge

Going Beyond Regular Security Tests 

Our concierge model helps you test AI and LLM systems, simulate real-world intrusion paths, and investigate malware with minimal back and forth (just like your own team).
Speak to Your Concierge

Your Security Posture Isn’t Bulletproof

If an attacker tried today, how far
could they get, and how fast?

The security gap now is exposure chaining: one weak identity, one misused permission, one overlooked endpoint, and the attacker is suddenly inside core systems.
KLEAP runs controlled simulations and investigations that show real attack paths and the right fixes that reduce risk.
Attackers spend more time abusing identity paths than other vulnerabilities. 
Normal operational shortcuts implemented poorly enables lateral movement.
Vulnerabilities from what you  cannot see within your own systems.
AI & LLM features add a quiet risk layer that bypasses  traditional control points.

We Protect. What Many Overlook.

What this solves: AI systems vulnerable to prompt injection, data leakage through retrieval, unsafe tool actions, and model misuse.

How KLEAP helps: We test retrieval layers, integrations, permissions, output handling, and how the system behaves under adversarial input.

What this solves: Vulnerabilities across your risk surface that can compromise your high-impact systems and sensitive data.

How KLEAP helps: We simulate adversary behavior: reconnaissance, initial access, escalation, lateral movement, and objective-based actions.

What this solves: Figuring out the malware’s origin and infection points, what it does, whether it persists, what it affects, and how to contain it.

How KLEAP helps: We perform triage and analysis to understand system behavior, persistence mechanisms, and likely exploits.

AI & LLM Testing

What this solves: AI systems vulnerable to prompt injection, data leakage through retrieval, unsafe tool actions, and model misuse.

How KLEAP helps: We test retrieval layers, integrations, permissions, output handling, and how the system behaves under adversarial input.

Red Team Assessments

What this solves: Vulnerabilities across your risk surface that can compromise your high-impact systems and sensitive data.

How KLEAP helps: We simulate adversary behavior: reconnaissance, initial access, escalation, lateral movement, and objective-based actions.

Malware Analysis

What this solves: Figuring out the malware’s origin and infection points, what it does, whether it persists, what it affects, and how to contain it.

How KLEAP helps: We perform triage and analysis to understand system behavior, persistence mechanisms, and likely exploits.

Your Advanced Security Issues Need KLEAP 

Advanced security testing only works when it is structured.
KLEAP runs every engagement with clear rules, checkpoints, and visibility, so your team always knows what is happening and why.
Objectives & Rules of Engagement 
Attack Planning
Execution with Realistic Techniques
Validation & Impact Proof
Reporting & Remediation Guidance
Closure Support & KT

Your Advanced Security Issues Need KLEAP 

Advanced security testing only works when it is structured.
KLEAP runs every engagement with clear rules, checkpoints, and visibility, so your team always knows what is happening and why.
Objectives & Rules of Engagement 
Attack Planning
Execution with Realistic Techniques
Validation, Impact Proof
Reporting & Remediation Guidance
Closure Support & KT

Protecting Against Advanced Threats Is Hard. Working With Us Isn't.

Speak to Your Concierge
Speak to Your Concierge
LLM apps have unique failure modes: prompt injection, insecure output handling, data leakage through retrieval, and tool misuse. KLEAP tests the entire workflow: model behavior, retrieval, tools, permissions, and how outputs are consumed.

Penetration testing is scope-based: it looks for vulnerabilities across defined systems and validates exploitability to reduce security risk. 

Red teaming is objective-based: it simulates a real adversary trying to reach a goal such as domain access, sensitive data exposure, or operational disruption. Red team assessments focus on chaining weaknesses across identity, endpoints, and controls to measure real attacker reach and speed. Both reduce risk, but red teaming tests how your environment behaves under realistic attacker behavior.

Common red team scenarios are chosen based on business impact and how real incidents unfold: 

  • Data exfiltration: prove whether sensitive data can be accessed and moved out through realistic paths 
  • Insider-style misuse: validate how far an account with legitimate access can go beyond its role 
  • Endpoint compromise to escalation: start from a workstation foothold and test privilege escalation and lateral movement 
  • Credential theft and reuse: simulate how attackers use stolen credentials to pivot across systems 
  • Ransomware-style blast radius: measure what systems become reachable if a single endpoint is compromised 

KLEAP helps you select scenarios that match healthcare and manufacturing risk: downtime, trust impact, and operational disruption. 

AI and LLM penetration testing evaluates how an AI feature can be abused to leak data, bypass controls, or trigger unsafe actions. It typically includes: prompt injection testing, data leakage through retrieval (RAG), insecure output handling, permission and tool misuse, and identity and access boundary checks across AI workflows. KLEAP tests the full pipeline: model interaction, retrieval layer, integrations, tools, and how outputs are used downstream. 

KLEAP tests prompt injection as an abuse path, not a text trick. We attempt to override system instructions, extract restricted data, and cause unsafe outputs. For tool actions, we test whether the model can be manipulated into calling tools or APIs it should not, using the wrong permissions, or performing actions without proper user intent confirmation. We also test guardrails: input controls, tool permission boundaries, output validation, and logging so AI actions are auditable. 

AI systems change faster than traditional apps. Retesting is most important after new tool integrations, expanded data sources, prompt and policy changes, role or permission changes, model upgrades, and workflow changes that alter how outputs are used. For teams shipping frequently, a quarterly cadence with targeted retests after major changes is a practical baseline. KLEAP can scope lightweight retesting so you reduce AI security drift without slowing delivery. 

A malware investigation should deliver clarity your team can act on: what the malware does, how it persists, what systems it likely touched, and what to contain first. KLEAP provides behavioral findings, extracted indicators of compromise (IOCs), likely infection vectors, persistence mechanisms, and guidance for containment and recovery steps. The goal is not just identification but also reducing reinfection risk and closing the path that enabled the malware.

Frequently Asked Questions