The Cost of Blind Trust in Decentralized AI Agents

Agents submitting transactions are prime targets for extractable value. Without visibility, users subsidize the entire MEV supply chain.

• >90% of DEX trades have some MEV leakage.
• Sandwich bots can extract 5-50+ bps per user swap.
• Agents using public mempools are inherently vulnerable.

Agents making decisions based on external data (e.g., price feeds) are only as strong as their oracle. A single corrupted feed can trigger cascading, automated liquidations.

• $500M+ lost to oracle exploits historically.
• Flash loan attacks rely on this vector.
• Agents lack context to detect data anomalies.

Agents defaulting to the most integrated DEX or bridge (e.g., Uniswap, layerzero) create a hidden tax via suboptimal routing. The "convenience" cost is paid in slippage and fees.

• Cross-chain swaps can have 3-15% spread variance.
• L1 vs. L2 fee differentials are often ignored.
• True best execution requires intent-based competition (UniswapX, CowSwap).

Multiple agents competing for the same on-chain outcome (e.g., an arb) trigger gas price wars. The winner captures diminishing profits, while all participants pay elevated network fees.

• Can increase base gas costs by 10-100x during congestion.
• Profitable only for the fastest searchers with private RPCs.
• Turns agent-vs-agent competition into a public good drain.

Agent logic is often off-chain and proprietary. Users cannot verify if an agent's "optimal" route was truly optimal or if it contained a kickback to the developer.

• Creates principal-agent misalignment.
• Defeats the purpose of verifiable blockchain execution.
• Solutions require ZK-proofs of agent state (e.g., RISC Zero) or open-source intent standards.

Agents operating in silos cannot pool liquidity or coordinate settlement. This fragments capital and increases slippage for large orders, a problem solved by shared settlement layers like CoW Protocol or Across.

• 20-30% better prices possible via batch auctions.
• Isolated agents cannot discover counter-party orders.
• Requires a shift from transaction-based to intent-based architecture.

Agents are black boxes. You can't audit their decision logic or verify they followed your intent, creating a single point of catastrophic failure.\n- Risk: Malicious or buggy logic drains wallets or manipulates protocols.\n- Scale: A single compromised agent model could affect millions of user sessions.

Shift trust from the agent's code to cryptographic proofs. These protocols generate ZK-proofs or attestations that an agent's execution was correct.\n- Verifiable Compute: Prove an inference used an approved model and valid inputs.\n- Audit Trail: Create an immutable, cryptographically-verified log of agent decisions.

Agents act on real-world data (prices, news, API feeds). Corrupted or manipulated data leads to garbage-in, garbage-out transactions.\n- Attack Vector: Adversarial data feeds trigger malicious agent actions.\n- Complexity: Verifying the provenance and integrity of unstructured data is unsolved.

Specialized networks that attest to the validity of off-chain data and computations before an agent acts. They act as a firewall for agent inputs.\n- Multi-Source Validation: Cross-check data across dozens of nodes before consensus.\n- Programmable ZK: Allow developers to define custom verification logic for agent inputs.

An agent with signing power can execute any transaction. Without intent verification, a malicious prompt or hijacked session leads to immediate, irreversible loss.\n- User Error: A poorly phrased prompt results in a harmful action.\n- Supply Chain Attack: A compromised plugin or tool library alters the agent's intent.

Separate intent declaration from transaction execution. Users approve high-level goals, not raw calldata.\n- Constraint Language: Define rules (e.g., "swap X for Y, max slippage 1%").\n- Solver Competition: A network of solvers competes to fulfill the intent safely and efficiently, with verification built-in.