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I will perform ai agent security testing and llm red teaming
Safi Ullah Khan
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Are you deploying an LLM or autonomous AI system? If your application connects to APIs, databases, or user inputs, it may be vulnerable to prompt injection, data leaks, and tool abuse. My AI Agent Security services identify critical flaws before attackers do.
As a cybersecurity expert, I provide LLM red teaming to uncover prompt injection, jailbreaks, tool hijacking, and insecure output handling. Every LLM red teaming engagement strengthens your AI Agent Security posture.
What I Offer:
Advanced LLM red teaming for jailbreaks and guardrail bypasses.
Comprehensive AI Agent Security audits for prompt injection and data leaks.
Threat modeling for RAG pipelines, vector databases, and AI agents.
Proactive AI Agent Security testing for unauthorized tool and API execution.
Deliverables:
A detailed LLM red teaming report with proof-of-concept findings and developer-focused remediation to improve your AI Agent Security.
My LLM red teaming methodology follows the OWASP Top 10 for LLMs and MITRE ATLAS. I specialize in AI Agent Security to help you deploy secure AI applications with confidence. LLM red teaming is essential before launching any production AI system.
Conoce a Safi Ullah Khan
Safi Ullah Khan
Python Automation , Web Security, AI Agents Security, Cloud Security
- DePakistán
- Miembro desdeabr 2024
- Última entrega2 meses
Idiomas
Inglés, Urdu
Computer Systems Engineer with 5+ years of experience in Cybersecurity, AI Agent Security, QA Engineering, API Testing, and Python Development. I specialize in LLM Red Teaming, Prompt Injection Testing, API Security, Web Security, QA Automation, and Secure Software Development. Skilled in Python, Java, C++, JavaScript, Wazuh SIEM, OpenSearch, Linux, Threat Hunting, and Security Automation. I deliver secure, scalable, and high-quality solutions with a strong focus on performance, reliability, and client satisfaction.
Mi porfolio
FAQ
What is the difference between an LLM pentest and AI agent security testing?
An LLM pentest focuses primarily on the model's inputs and outputs (jailbreaks, prompt injection). AI agent security testing goes deeper—it assesses how an autonomous agent interacts with tools, databases, and APIs, ensuring malicious prompts cannot force the agent to execute unauthorized actions
Do you need access to my source code?
Not necessarily. I can perform black-box AI red teaming simply by accessing your application's user interface or API endpoint. However, having access to system prompts or architecture diagrams allows for a much more thorough white-box AI security audit.
