𝗪𝗵𝗲𝗻 𝗔𝗜 𝗕𝗲𝗰𝗼𝗺𝗲𝘀 𝗔 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗪𝗲𝗮𝗽𝗼𝗻
Anthropic's Mythos models changed the security world. They do not just explain bugs. They find and exploit new vulnerabilities in unfamiliar code.
This capability changes the balance between attackers and defenders. Anthropic kept the unrestricted Mythos 5 model limited to a small group of experts. The public gets Fable 5. This version has safeguards that block high-risk cybersecurity prompts.
The danger is real. A model that finds bugs helps both sides. A defender uses it on their own code. An attacker uses it on everyone else's code.
Attackers do not follow safeguards. They use AI to scan old smart contracts for weaknesses right now. If you ship code with value, you must assume attackers use AI to find your flaws.
The current defense strategy has a flaw. Safeguards cannot tell a legitimate audit from an attack. If your prompt looks risky, the AI might give you a lower quality answer without telling you. This makes the public model a blunt tool for defenders.
I do not get less careful because of AI. I get more systematic. Here is my approach:
- I run AI analysis on my own code aggressively. I want to find bugs before an attacker does.
- I treat old or unverified contracts as high risk. Automated tools target these first.
- I never trust an AI clean bill of health. I still perform manual reviews because models miss things.
AI does not make security work obsolete. It raises the standard. You must assume the attacker already ran a model on your code.
An auditor who refuses to use AI is at a disadvantage. You must meet an AI-equipped attacker with AI-equipped defense. Use the tools on your own code, understand their limits, and keep your human judgment.
Do not respond with fear. Respond by using these tools to find your own bugs first.
Optional learning community: https://t.me/GyaanSetuAi