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I will red team your llm application
Arham Ali
About this gig
Are your LLMs vulnerable to prompt injection or data leaks?
As businesses rush to integrate AI, security is often an afterthought. I am a Cybersecurity Professional specializing in AI risk management. I don't just find vulnerabilitiesI engineer the resilient infrastructure needed to neutralize them before they reach your models.
What I Offer:
- Adversarial Red-Teaming: Rigorous simulated attacks to identify jailbreaks and logic bypasses.
- Security Guardrails: Strict input/output filtering to prevent data leaks and block toxic content.
- Custom AI Gateways: Secure proxies (using PyTorch and modern stacks) that act as a buffer for your LLM APIs.
- Zero-Trust Frameworks: Verifiable, strict security protocols for your entire AI pipeline.
I bring hands-on experience in both offensive attacks and defensive system architecture, ensuring your application stays secure without slowing down the user experience.
- Message me today to secure your AI against emerging threats!
Get to know Arham Ali
Arham Ali
Cyber Security, Ai Services, Web Development
- FromPakistan
- Member sinceJun 2026
- Avg. response time1 hour
Languages
Urdu, English
I am a computer science student and cyber security professional with experience in engineering multi-layer security guardrails for LLMs and conducting adversarial red-teaming. I specialize in building AI-powered security gateways and full-stack applications using technologies like PyTorch, Next.js, and Firebase to solve complex technical challenges.
FAQ
What is a prompt injection attack?
It is a vulnerability where a user crafts a specific input designed to override the original instructions given to the AI model, potentially causing it to execute unauthorized actions or reveal hidden system prompts.
Do you need access to my source code?
For a Basic Red-Teaming Audit, I only need access to the user-facing application or API endpoints. For Standard and Premium packages where I implement guardrails or architectural gateways, backend access or collaborative staging environments will be required.
Can you secure models from OpenAI, Anthropic, or local open-source models?
Yes. Security guardrails and monitoring proxies are implemented at the application layer (between the user and the model), making them effective regardless of whether you are using an external API or a locally hosted model.
Will adding security guardrails slow down my application?
While filtering does add a small processing step, I optimize the architecture to ensure latency remains minimal and does not disrupt the real-time user experience.
