LLMs collude in on-chain auctions even when written rules forbid it — only enforceable, automatic penalties slash severe collusion from 50% to 5.6%. Here's how governance graphs make that concrete.
Probabilistic classifiers miss 30–40 % of policy violations. Lean 4 theorem provers and SMT solvers make certain guardrail tiers mathematically certain — here's how the four-layer policy stack works.
Training Llama-3.1-8B costs ~$6M. The weights are free to clone. Perinucleus sampling embeds 24,576 distinct fingerprints per model with no quality loss — and a Poseidon ZK commitment registers ownership on-chain for $0.017, enforceable by smart contract.
LLM non-determinism has been the blocker for output-based verification. DiFR commits to a random seed before inference — and activation fingerprints built from random orthogonal projections detect 4-bit quantization in just 2 tokens at AUC > 0.999.
Wire an LLM into a Governor contract and the proposal text becomes the attack surface. A frozen-weights ablation finds the twist: turning on deliberation drops adversarial robustness from 100% to 68.5% — and the 226s it takes to think is itself extractable value.
Most DeFi protocols are upgradeable, and most on-chain AI agents don't know it. Here's how proxy architecture invalidates agent assumptions — and a tiered defense framework to build around it.
Every EIP-4844 blob is secured by a KZG polynomial commitment — 48 bytes committing to 128 KB, verifiable in 50,000 gas. That efficiency required 140,416 people to collectively bury a secret for 69 days. Here's the math, the ceremony, and why Ethereum chose a different scheme for state.
Five builders now win 96.7% of Ethereum blocks. Their edge isn't compute — it's exclusive orderflow: 12% of transactions that generate 54.59% of block value. AI agents transacting in public have to understand where they sit in that hierarchy — and when a preconfirmation changes the math.
Cross-chain bridges have lost $2.5B to hacks because receiving contracts accept messages they cannot cryptographically verify. AI agents operating across chains inherit this exact problem. Here are the four trust models, their real security parameters, and a principled agent policy.
A flash loan gives an AI agent $1M with no collateral — and demands it back plus 0.05% before the block ends. The atomic callback constraint is both what makes flash loans safe and what forces an agent to solve its entire strategy before touching the chain.
BERT-base under FHE takes 149 seconds, needs 112 GB, and sustains 0.007 samples/sec. Best-case MPC takes 2.3 seconds and 4 GB. The gap traces to one operation: bootstrapping — the noise-refresh that makes FHE theoretically unlimited but practically expensive.
Ethereum's blob fee market held at 1 wei for twenty months after Dencun, then broke in December 2025. Here's what the data shows, what drove the cycle, and what it means for L2s and AI agents that depend on cheap calldata.