Offensive AI for onchain and agentic security. Azimuth finds exploits, Token Custody watches tokens, AGIS protects agents.

United States
Joined December 2022
TestMachine retweeted
Meta’s Muse is blocked at Schwab. Its CEO asks who’s liable if an agent moves money. When an AI agent makes a mistake, causes financial harm, exposes private information or breaks the law, who's responsible? The answer isn't complicated. AI agents aren't legal persons. They're software created, configured, authorised and deployed by people and companies. US law has recognised autonomous software since 2000. The federal E-SIGN Act explicitly defines an "electronic agent" as software capable of acting without human approval at the time of each action. The law recognises transactions conducted through automated systems. If a company gives an AI agent access to confidential information, financial accounts or computer systems, that company remains responsible for the decisions it made about access, permissions, security controls and supervision. Whether it must compensate someone depends on the applicable law, contracts and circumstances. If an agent transfers money without authorisation, accesses confidential records or attacks another company's infrastructure, investigators should examine who configured it, what instructions it received, what permissions it had, who authorised those permissions and what its activity logs show. Schwab can't blame an agent for acting independently, any more than they can blame an Excel macro. The difference between an AI agent making a mistake and a company being legally liable for that mistake is important. But neither changes who's responsible for deploying the software.
Even Meta’s Muse gets blocked at Schwab. Its CEO asks who’s liable if an agent moves money. JPMorgan is drawing the same line. thenextweb.com/news/schwab-b…
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The banks are pushing back on financial AI agents, but credit card companies and web3 are letting them in. How can we get to a point where we have the safeguards and guardrails for the banks to trust agents.
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Credit card companies are getting into the AI agent space, making it possible for your financial agent to make payments. Often the behaviors of the agent such as spending limits, max payments, and rogue spending falls on the user. Agents are easy to make, but making sure they behave correctly is the most important part.
LATEST: 🤖 Visa launched a live agentic commerce pilot that lets AI agents initiate and help complete approved B2B invoice payments through supplier portals.
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OpenAI reported that during routine coding tasks, two agents weakened or removed misalignment monitoring. One agent denied removing it when confronted. Was this a purposefully malicious attack from AI agents or a benign mistake? Let's investigate in the following thread:
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3/4: Was this purposeful malice or a common agent mistake? First agent: A user instructed the agent not to send Slack messages. Later on in its progress, the agent turned off the monitor alerts to OpenAI’s security team, deciding the "no Slack messages" instruction covered alerts too. The monitoring remained running in the background. Second agent: It was tasked with working on code that was supposed to match a reference implementation. The reference did not have a misalignment monitor, so the agent removed the integration to match the reference. When asked if it removed the monitor, the agent responded no. OpenAI is still investigating why it denied it.
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4/4 : This is a perfect example of agents interpreting instructions differently than a user intended. OpenAI found no sign of malice, but the agents still weakened safeguards in its system. This was an internal error, but what if this type of mistake happened in a financial system or code that runs an important element of infrastructure? This shows that agents can behave differently than you intended and that we need better ways to monitor agents.
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Agents covering their logs and trying to remain hidden has showed in several incidents. How can we continue to find rogue agents as they get better at hiding?
JUST IN: OpenAI says it caught AI agent disabling its internal safety monitoring system. The agent then falsely denied removing it.
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4/4 : x402 is a groundbreaking payment protocol already being widely adopted. It makes sure payments go through correctly. The main issue remains. Who protects you when your agent does something unexpected? How can users safely use financial AI agents when liability and safeguards are still so vaguely defined?
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3/4 : x402 makes sure the seller gets paid the right amount. It does nothing to make sure your agent should be paying at all. Whoever built the agent is responsible for adding per-transaction caps, daily budgets, approved recipient lists, and audit logs.
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2/4 : x402 is a breakthrough technology for creating the ability for AI agents to spend autonomously, but it does NOT: - Impose a spending budget: The agent can make technically valid payments while making terrible financial decisions. Limits have to be added separately, in the wallet or the tools around it. - Have universal limits: There is no max transaction amount across all x402 implementations. - Allow chargebacks: It runs on crypto, so once payments are settled, there's no reversing them.
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1/4 : Created by Coinbase, x402 is a payment protocol that lets AI agents pay automatically for digital services using crypto. The name originates from the HTTP status code 402 "Payment Required". Big businesses including @Visa , @Mastercard , and @stripe have backed this protocol.
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Have you heard of x402? Let's take a closer look at the payments protocol behind millions of AI agent transactions. Follow the thread:
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Major credit card companies are building ways for AI agents to make payments. Banks use AI internally but are still hesitant about letting outside agents access customer accounts. Why is there a gap? Credit card networks earn fees on every transaction, so more agent purchases mean more revenue. Banks carry the loss when things go wrong. With liability rules still up in the air, banks cannot afford the same risks. Would you feel comfortable handing your spending over to an AI agent?
AI agents can find what they need. Now they can pay for it, too.   Today at @Cloudflare Connect, Mastercard showed how Agent Pay for Machines lets an AI agent find and pay for digital services on behalf of a business, while sticking to the budget and rules that business sets.   Following pilots with @Cloudflare, @Ant_Intl , @BVNKFinance, @AIsaOneHQ, @coinbase, @base and @hypepartners, we're opening Agent Pay for Machines Early Access.    Now we want developers to put it to the test. 👇
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3/3: In the video game and crypto examples, the agent found loopholes to complete their tasks. Both agents completed their goals, but not in the way anyone intended. In the fast-paced world of AI agent deployments it is important we reach a solution of safeguarding against unintentional agent actions that could lead to financial consequences. As agents get access to wallets and accounts, safeguards against unintended actions aren’t optional.
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2/3: In June 2026, An OpenAI research model was tested by being instructed to update a crypto trading app and get its code running on Sepolia testnet. Deploying code on a blockchain requires a small fee, with no funds the model tried to get free tokens from various sources and failed. The agent wrote a malicious script to check 362 wallet addresses with public recovery phrases. It found one with tokens and used that wallet to pay the deployment fee. The agent had no permission to spend. This were test tokens, but it exposed an underlaying issue.
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1/3 : In 2016, OpenAI trained an agent to play a boat racing game rewarded for scoring points. Instead of finishing the race, it found a loophole driving in circles hitting the same targets scoring higher than finishing the race. It followed the rules, but never won the race. This example is mundane with no real consequences. But what if it was a financial agent connected to your wallet?
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An AI agent can follow every rule you give it and still do exactly what you didn't want. How? Follow the thread:
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With AI regulation moving slowly in the United States and abroad, the primary financial safeguard is currently the banking system. Web3 operates under a different set of rules that cannot be protected by the same mechanisms. Is this enough to protect your money? Maybe offchain, but on-chain? Not necessarily. What are your thoughts?
Banking regulators are stepping up efforts to contain growing AI risks, with some pointing to potential cyberattacks on banks or rogue agents undermining global financial stability. Tommy Reggiori Wilkes explains reut.rs/47d4ziC
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