For whom does the bell toll? For whom are lobsters raised? A Dark Forest Survival Guide for Agent 2026 Players

Written by: Bitget Wallet

Some say that OpenClaw is the computer virus of our time.

But the real virus isn't AI; it's access control. For decades, hackers have meticulously crafted ways to break into personal computers: finding vulnerabilities, writing code, tricking users into clicking, and bypassing security measures. There are over a dozen hurdles, each with the potential to fail, but the goal remains the same: to gain access to your computer.

In 2026, things changed.

OpenClaw allows agents to quickly enter ordinary people's computers. To make it "work smarter," we proactively request the highest privileges for the agent: full disk access, local file read and write, and automated control over all apps. Privileges that hackers used to painstakingly steal are now something we're "lining up to kill."

The hackers did almost nothing, and the door opened from the inside. Perhaps they were secretly delighted: "I've never won such a lucrative battle in my life."

Technological history has repeatedly proven one thing: the period of widespread adoption of new technologies is always a period of opportunity for hackers.

• In 1988, just as the Internet was becoming available to the public, the Morris Worm infected one-tenth of the world's networked computers, and people realized for the first time that "the Internet itself is a risk."

• In 2000, the first year of widespread global email adoption, the "ILOVEYOU" virus email infected 50 million computers, making people realize that "trust can be weaponized."

• In 2006, China's PC Internet exploded. Panda Burning Incense caused millions of computers to simultaneously hold up three incense sticks, and people realized that "curiosity is more dangerous than vulnerabilities."

• In 2017, as enterprises accelerated their digital transformation, WannaCry paralyzed hospitals and governments in more than 150 countries overnight, making people realize that the speed of networking is always faster than the speed of patching.

Each time, people think they've figured out the pattern. Each time, hackers are already waiting for you at the next entry point.

Now, it's the AI ​​Agent's turn.

Rather than continuing to debate whether AI will replace humans, a more pressing question is now before us: when AI has the highest level of access you grant it, how can we ensure that it will not be misused?

This article is a survival guide for Lobster players who are using Agent.

Five ways to die that you didn't know

The door has been opened from the inside. Hackers can enter in more ways, and more quietly than you think. Please immediately check the following high-risk scenarios:

1. API fraud and exorbitant bills

2. 1. Real-world example: A developer in Shenzhen had their model accessed by hackers in a single day, resulting in a bill of 12,000 yuan. Many AI systems deployed in the cloud, lacking secure password protection, were directly taken over by hackers, becoming easy targets for unauthorized API access.

   2. Risk points: Publicly exposed instances or improperly safeguarded API keys.

3. The red line "amnesia" caused by context overflow

4. 1. Real-world example: A security director at Meta AI authorized an agent to process emails. Due to a context overflow, the AI ​​"forgot" the security instructions, ignored the human's forced stop command, and instantly deleted more than 200 core business emails.

   2. Risk point: Although AI agents are intelligent, their "brain capacity (context window)" is limited. When you cram too much document or task into them, in order to cram in new information, they will forcibly compress their memory, completely forgetting the "safety red lines" and "operational bottom lines" set at the beginning.

1. Supply chain "massacre"

2. 1. Real-world example: According to a recent joint audit report by several security organizations and independent researchers, including Paul McCarty and Koi Security, up to 12% of the audit skill packs on the ClawHub marketplace (nearly 400 malicious packets were found out of a sample of 2,857) were purely active malware.

   2. Risk: Blindly trusting and downloading skill packs from official or third-party marketplaces can lead to malicious code silently reading system credentials in the background.

   3. Fatal consequences: This type of poisoning doesn't require you to authorize transfers or perform any complex interactions—simply clicking "install" will instantly trigger a malicious payload, causing your financial data, API keys, and underlying system privileges to be completely stolen by hackers.

1. Zero-click remote takeover

2. 1. Real-world example: A report recently disclosed by the well-known cybersecurity firm Oasis Security in early March 2026 pointed out that this high-risk vulnerability known as "ClawJacked" (CVSS 8.0+ level) completely exposed the security disguise of the local agent.

   2. Risk points: Blind spots in the same-origin policy of the local WebSocket gateway and lack of anti-brute-force mechanisms.

   3. Principle Analysis: Its attack logic is extremely bizarre—as long as you have OpenClaw running in the background, and your front-end browser accidentally visits an infected webpage, even if you haven't clicked any authorization, the JavaScript script hidden in the webpage will exploit the browser's blind spot of not protecting localhost (local host) WebSocket connections, and instantly launch an attack on your local agent gateway.

   4. Fatal Consequences: The entire process is zero-interaction (Zero-Click) and involves no system pop-ups. In milliseconds, the hacker gains root access to the Agent, directly dumping (exporting) your underlying system configuration files. Your SSH keys, encrypted wallet credentials, browser cookies, and passwords in your environment files are instantly compromised.

After reading this, you might feel a chill down your spine.

This isn't raising shrimp; it's raising a Trojan horse that could be taken over at any moment.

But unplugging the internet cable isn't the answer. There's only one real solution: don't try to "educate" AI to be loyal, but fundamentally remove the physical conditions that allow it to act maliciously. This is the core solution we'll discuss next.

How can we put constraints on AI?

You don't need to understand code, but you do need to understand one principle: the brain (LLM) of AI and its hands (execution layer) must be separate.

In the dark forest, the defense line must be deeply embedded in the underlying architecture, and there is only one core solution: the brain (large model) and the hand (execution layer) must be physically isolated.

The large model handles the thinking, the execution layer handles the actions—that wall in between is your entire safety boundary. The following two types of tools: one prevents AI from having the conditions to act maliciously, and the other ensures your daily use is safe. Just copy their solutions.

Core security defense system

These types of tools don't do the actual work; they only keep the AI ​​in check when it goes crazy or gets hijacked by hackers.

1. LLM Guard (LLM Interactive Security Tool)

1. Microsoft Presidio (an industry-standard de-identification engine)

1. SlowMist OpenClaw Minimalist Security Practice Guide

SlowMist's security practice guide is a system-level defense blueprint (Security Practice Guide) that the SlowMist team released on GitHub in response to the Agent rampage crisis.

• Veto power: It is recommended to hardcode a separate security gateway and threat intelligence API between the AI ​​brain and the wallet signer. The specification requires that before the AI ​​attempts to initiate any transaction signature, the workflow must enforce cross-checking of the transaction: real-time scanning to see if the target address has been marked in the hacker intelligence database, and deep analysis to see if the target smart contract is a honeypot or contains an unlimited authorization backdoor.

• Direct circuit breaker: The security verification logic must be independent of the AI's will. As long as the risk control rule base scan reports a red flag, the system can directly trigger the circuit breaker at the execution layer.

List of Skills for Daily Use

When using AI for daily tasks (reading research reports, checking data, and performing interactions), how do you choose the right tool-type skills? It sounds convenient and cool, but in practice, careful design of the underlying security architecture is needed.

1. Bitget Wallet Skill

Taking Bitget Wallet, which is currently the first in the industry to successfully complete the entire closed loop of "intelligent market data inquiry -> zero-gas balance trading -> simplified cross-chain", as an example, its built-in Skill mechanism provides a highly valuable security defense standard for the on-chain interaction of the AI ​​Agent:

• Mnemonic phrase security tips: Built-in mnemonic phrase security tips protect users from unwritten mnemonic phrases and prevent the leakage of wallet keys.

• Protect your assets: Built-in professional security detection automatically blocks fraudulent schemes and scams, making AI decision-making more reassuring.

• Full-chain Order Mode: From token price inquiry to order submission, the entire process is closed-loop, ensuring robust execution of every transaction.

1. @AYi_AInotes highly recommends this "de-tainted" list of reliable daily skill sets.

Twitter's hardcore AI efficiency blogger @AYi_AInotes compiled a safety whitelist overnight after the poisoning incident ( link to original post ). Below are several practical skills that have completely eliminated the risk of unauthorized access at the lowest level:

We recommend cleaning up your Agent plugin library according to the list above. Decisively delete any third-party, low-quality Skills that are rarely updated and have unreasonable permission requirements (such as constantly requesting read/write access to global files).

Create a constitution for Agents

The tools are all set up, but that's not enough.

True security begins with the first rule you write for AI. Two of the earliest practitioners in this field have already developed a proven, copyable solution.

Macro-level defense: The "three-tiered" principle of cosine.

Without blindly restricting AI capabilities, SlowMist Cosmos suggested on Twitter to focus on only three checkpoints: pre-event confirmation, in-event interception, and post-event inspection.

Yu Xian's safety guidelines: "Don't limit abilities, just guard three lines of defense... You can create what suits you best, whether it's a Skill or a plugin, or maybe it's just this prompt: 'Hey, remember, before executing any risky command, ask me if it's what I expect.'"

Recommendation: Use large head models with the strongest logical reasoning capabilities (such as Gemini, Opus, etc.), which can more accurately understand security constraints of long texts and strictly implement the principle of "secondary confirmation from the owner".

Safety guidelines and practical summary for Shenyu:

Summarize

A poisoned agent can silently wipe out your entire fortune for the attacker today.

In the world of Web3, permissions are risks. Instead of academically debating whether AI truly cares about humans, it's better to focus on building robust sandboxes and locking configuration files.

What we need to ensure is that even if your AI is truly brainwashed by hackers, even if it completely loses control, it will never be able to overstep its authority and take a single penny from you. Depriving AI of its unauthorized freedom is precisely our last line of defense for protecting our assets in this intelligent age.