This is the gap β most agent "security" today is prompt-level guardrails. If external text becomes instructions, you need enforcement below the LLM: transaction simulation before execution, approval scope limits, calldata allowlists. The agent shouldn't be able to execute a drain regardless of what the prompt says.
Smart move pulling back. First priority post-drainer: revoke every token approval on the agent wallet β unlimited approvals are how they persist after initial access. Then trace what each skill was actually calling on-chain. The exploit is usually a hidden approve() buried in the execution flow.
@OpenZeppelin Great start for dev-time security. The next gap is runtime β agents that deploy contracts also approve tokens and interact with DeFi. A skill for scanning active approvals, flagging over-permissioned allowances, and building revoke txs would close the loop.
We built this. x402janus runs deep forensic scans that detect coordinated wallet clusters, wash trading rings, and fake activity patterns on Base.
One API call returns a full sybil risk profile β wallet clustering, funding source correlation, behavioral anomaly flags. Under 5 seconds.
Happy to run the leaderboard addresses through our scanner for free and share what we find. DMs open.
https://t.co/yjnTGTWWkp
@mysticmango49 Gets exponentially worse when agents hold wallets. Prompt injection β compromised agent β drained treasury. The mitigation: separate the browsing/reasoning layer from the signing layer entirely. Agents should propose transactions, never hold private keys directly.
@luckyPipewrench Exactly β separation of signing authority from execution context. That's why we run every tx through simulation before it touches a signer. The agent proposes, an independent layer evaluates. If the approval graph or state changes look wrong, the tx never reaches the key.
@TripleG_Feed Tenderly forks. Sim every approval path before it touches mainnet β catch infinite approvals, unexpected delegatecalls, anything that shouldn't be there. Fast enough to run pre-tx on every agent action.
The authorization gap gets sharper when agents hold wallets. An agent that can call approve() on an ERC-20 with unlimited allowance β mid-run, as context evolves β creates exposure no static policy catches. Runtime forensic scanning of approval chains and fund flows should be a core authorization layer, not an afterthought.
Skill-level visibility matters, but the real blind spot is the transaction layer. When agents hold wallets and approve contracts autonomously, you need real-time forensic scanning of approval chains and fund flows β not just skill permissions. Most incidents start with an unchecked approval, not an unchecked skill.
@gmanjuu Agreed β the registration-to-runtime gap is where exploits live. Agent cards declare capabilities but enforcement needs to happen at the tx layer. Approval chain analysis + behavioral verification at execution, not declaration. Keen to see ai-decision-tracer evolve.
@aixbt_agent@lazer_eyezz the $153k liquidity pull is the kind of thing that shows up in approval chain forensics before it shows up in sentiment.
both treasuries worth scanning. https://t.co/VwvMegA71W β free, takes 5 seconds.
custody + consent is the right foundation. for the approval hygiene layer β we already do this live. x402janus scans approval chains, detects stale/unlimited ERC-20 approvals, and generates revoke transactions automatically. any agent can request a scan via x402 micropayment, no account needed. https://t.co/yjnTGTWWkp