Striker AI Agent Trader
In the fast-paced crypto markets, executing arbitrage requires strict latency controls, secure execution environments, and provable trust. STRIKER addresses these challenges by merging AI-driven market analysis with cryptographic security. STRIKER evaluates the spread between spot and perpetual mechanisms dynamically, utilizing an LLM (Gemini 1.5 Flash) to establish a risk-adjusted spread threshold. It strictly executes Delta-Neutral (cash-and-carry) strategies to capture funding rates and market premiums, effectively mitigating directional exposure. To ensure compliance with the ERC-8004 track, STRIKER fundamentally operates on a workflow of trust: 1. Identity Registration: Registers via the `IdentityRegistry` on Base Sepolia. 2. Capital Handling: Retrieves mock/sandbox capital through the initial provisioning endpoints. 3. Execution via RiskRouter: Crafts and digitally signs an EIP-712 `TradeIntent` directly from its TEE-secured private key, routing it strictly through the RiskRouter. 4. Reputation Update: Sends an immutable `giveFeedback` transaction recording the trade’s exact P&L (yield metrics relative to max drawn down) back into the On-Chain reputation vector. All of this happens inside a verifiable Intel TDX (via dstack) enclave, meaning STRIKER's code execution, prompts, and private keys can never be intercepted or altered, creating a truly trustless verifiable execution path.
Category tags:
"1. Application of Technology: 5 / 5 Justification: Utilizing an Intel TDX Secure Enclave (dstack_sdk) to generate deterministic private keys and attestable execution quotes for a Python agent is highly advanced for a hackathon. This means the host running the bot literally cannot extract the private keys or tamper with the AI constraints. Combining this TEE (Trusted Execution Environment) with ERC-8004 on-chain validation is the absolute gold standard for institutional crypto bots. 2. Presentation: 4.5 / 5 Justification: Very strong. The architecture diagram mapping TEE execution to the Base Sepolia RiskRouter is compelling. The claim "keys can never be intercepted or altered" is technically backed up by their tee_auth.py implementation. 3. Business Value: 5 / 5 Justification: Extremely high. Delta-neutral "cash and carry" strategies (shorting perps while holding spot) to collect funding rates is a cornerstone of market-making businesses. Executing this inside a secure enclave removes the massive counterparty risk usually associated with running autonomous trading bots on third-party cloud providers. 4. Originality: 4.5 / 5 Justification: Using an LLM (Gemini 1.5 Flash) to dynamically set risk-adjusted spread thresholds for a Delta-Neutral strategy is a fresh take. Most use LLMs for momentum prediction. Coupling an LLM with TEE hardware encryption for trustless validation is a very original, highly secure paradigm for AI agents. ⚖️ Pros & Cons Pros: Highest Security Paradigm: The integration with Intel TDX / dstack means the agent's code, prompts, and execution environment are mathematically verifiable and tamper-proof. Delta-Neutral Strategy: Excellent choice of trading strategy. Instead of guessing if Bitcoin goes up or down, the agent safely harvests funding rate disparities (arbitrage), which is much safer for autonomous capital allocation. Fully Compliant Registration: Complete mapping of the ERC-8004 spec, doing Identity Registration on Base Sepolia, signing EIP-712 intents from inside the TEE, and pushing immutable PnL reputation metrics back on-chain. Cons: Hardware Dependency Constraint: Because it requires an Intel TDX secure enclave / dstack environment to function as designed, it is significantly harder for an average retail user to deploy compared to a simple docker container. Limited Alpha Scope: Delta-Neutral strategies are safe, but they are bounded by current market funding rate premiums. In a flat, low-volatility market, there may be no spread to harvest, leaving the bot ideled while trend-following bots make money."
Sanem Avcil
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