Contact person: Business Client

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Location: Indore, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I’m still at the planning stage of a new AI solution and want to lock down security before any code is written. My immediate priority is a thorough vulnerability assessment focused on AI model security—everything from how training data could be poisoned to ways a hostile actor might extract or manipulate model parameters down the road. Model robustness and secure deployment will matter later, but for now I need to understand the full attack surface and the concrete steps required to harden it from day one.

You’ll help me:
• Map potential threat vectors using frameworks such as MITRE ATLAS, OWASP for ML, or similar tools you trust (Adversarial Robustness Toolbox, CleverHans, Foolbox, etc.).
• Produce an actionable risk-ranked report that details each vulnerability and the mitigation strategy, including any controls to embed in our MLOps pipeline.
• Review (or co-create) high-level architecture diagrams, flagging weak points in data ingestion, training, inference, and model storage.
• Recommend best practices for secure coding, access control, monitoring, and incident response specific to AI workloads.

Acceptance criteria
1. Written assessment clearly lists each identified risk, its severity, and a validated mitigation.
2. Recommendations cite or align with recognized standards (e.g., NIST AI RMF, ISO/IEC 27034, or equivalent).
3. Final deliverable includes an interactive session to walk me through the findings and answer follow-up questions.

If you have a solid track record in red-teaming machine-learning systems or implementing defense-in-depth for AI pipelines, I’d love to review your approach and timeline." (client-provided description)