AI Security Audit
Secure the AI layer before adversaries exploit it on-chain.
Get a quoteA specialist security review of AI-integrated smart contracts, on-chain model outputs, AI oracle feeds, and LLM-governed protocol components — guarding against adversarial inputs, model manipulation, and the new vulnerability classes that AI integration introduces.
The integration of AI into blockchain protocols creates an entirely new attack surface that traditional audit methodologies are not equipped to assess. AI oracle feeds can be manipulated to feed false data to contracts. LLM-governed components can be exploited through prompt injection. On-chain inference systems can be attacked via adversarial inputs that cause models to produce outputs triggering unintended contract state changes. Deep Guard's AI Security Audit applies cutting-edge adversarial machine learning research to the specific threat model of AI-integrated Web3 systems.
Our process, step by step.
Every engagement follows a structured methodology. No steps are skipped. No shortcuts are taken.
AI Integration Mapping
We catalogue every point where AI intersects with your on-chain system: oracle feeds, governance routing, inference calls, LLM-powered proposal processing, and any off-chain AI component whose outputs affect on-chain state.
Adversarial Input Testing
We craft adversarial inputs designed to cause AI components to produce outputs that trigger unintended, exploitable on-chain state changes — testing the boundary between AI behaviour and contract logic.
Oracle Manipulation Analysis
AI oracle feeds are tested for manipulation resistance: data poisoning attacks, model drift exploitation, and scenarios where an adversary controls sufficient training or inference-time input to influence oracle output.
Prompt Injection Testing
For LLM-governed components — governance proposal routing, natural language interfaces, automated decision systems — we test for prompt injection attacks that could cause the model to bypass intended constraints.
Model Output Validation Review
Review of the mechanisms by which your contracts validate and act on AI model outputs — identifying gaps where invalid, manipulated, or out-of-distribution outputs could trigger unintended execution.
AI integration security report
Comprehensive documentation of every AI-related vulnerability identified, with severity ratings and remediation guidance.
Adversarial attack documentation
Demonstrated adversarial inputs and attack chains showing real exploitability of identified vulnerabilities.
Output validation recommendations
Specific improvements to how your contracts validate and bound-check AI model outputs before acting on them.
AI architecture guidance
Design-level recommendations for structuring AI integrations to minimise the attack surface at the architectural level.
Ready to get started?
Talk to a Deep Guard engineer about your protocol and get a scoped quote within 24 hours.