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OpenAI doubled its API pricing this week, released a model that scores 82.7% on Terminal Bench and tops every major intelligence composite, then watched its CEO call his main competitor a bomb salesman on a podcast. Anthropic, meanwhile, confirmed that unauthorized users accessed Mythos, the model they spent weeks marketing as too dangerous to release. Four things actually changed this week. Three of them were worth the hype. GPT 5.5 Stopped Asking Me for Instructions GPT 5.5 is live inside ChatGPT and Codex for Plus, Pro, Business, and Enterprise users. The benchmark story is straightforward: 82.7% on Terminal Bench, clearing Mythos at 82%, Claude Opus at 69.4%, and GPT 5.4 at 75%. On the Artificial Analysis Intelligence Index, a composite of ten benchmarks across reasoning, coding, science, and agents, 5.5 is now the standalone leader after a three-way tie between Opus 4.7, Gemini 3.1 Pro, and GPT 5.4. ...

March 8, 2026: Andrej Karpathy dropped a 630-line Python script, aimed an AI agent at his own training code with a single metric to chase, and went to bed. Two days later the agent had run 700 experiments, found 20 genuine improvements, and cut training time by 11%. It also found a bug in Karpathy’s attention implementation that he had missed — not because the agent is smarter, but because it tried more things faster without getting bored after the 15th failed attempt. ...

The attack required no action from the victim. Visit a page. Leave. By the time the browser tab closed, the extension had already talked to Claude, exported chat history, read Gmail, and potentially sent an email under your name. Patched in Claude Chrome extension v1.0.41. Here is how the chain worked. The Attack Chain The Claude Chrome extension trusted any page on *.claude.ai to send it messages. That wildcard, every subdomain under claude.ai, is where the attack found its entry point. ...

The way RAG works is easier to understand if you stop thinking about AI memory. Think about a dictionary instead. You do not memorize every definition before you need one. Look up the word when you need it. RAG does the same thing with your files — chunks them, embeds them into a vector database, and pulls back only what matches your question. The model never sees the whole library. ...

You download a free PDF, a VS Code extension, a font pack. The file lands on your machine, and your background AI agent reads it. The file contains hidden instructions. The agent follows them. That is not a hypothetical. That is the exact threat model nobody is naming right now. OpenAI’s Codex runs silently on Mac while you work, learning from previous actions and picking up repeating tasks in parallel. Perplexity Personal Computer puts local agents on your machine with access to local files, native apps, and the web. Both ship with the premise that background access creates leverage. It does. It also creates exposure. These two things are not separable. ...

Topics: Ollama, MCP, Python, Kali Linux, Responsible Scope The tool does not determine whether you are a professional. Scope does. Before any script runs, before any model generates a command, you need written authorization for every target you plan to touch. That is not a disclaimer to skip past. Every piece of tooling in this article enforces that principle because I have watched what happens when it gets ignored. A few years ago a student ran a scan against a host that was not in the lab scope. I did not give a zero and move on. That student wrote the apology email. Not me, the student wrote it, disclosed exactly what ran and what the scan returned, and waited to hear what the victim decided to do about it. Outside a classroom, unauthorized access carries consequences the victim controls, not the teacher. That framing changes how seriously students take scope documents. ...

Anthropic built a model they decided was too dangerous to release. That sentence would sound like marketing if the technical details were not sitting right next to it. Claude Mythos Preview autonomously discovered and exploited zero-day vulnerabilities across major operating systems and browsers. Not “found potential weaknesses.” Exploited them. The Firefox JavaScript shell exploitation rate was 72.4 percent across repeated runs. It found a 27-year-old bug in OpenBSD. It found a 16-year-old vulnerability in FFmpeg. Finding the FFmpeg bug cost approximately $10,000 over several hundred runs, which makes it an expensive research tool but not an inaccessible one once the model is out in the world and someone else is paying the compute bill. ...

Cisco Talos reported that 40% of all intrusions in Q4 2025 came from exploited vulnerabilities. Phishing dropped to second place. The security awareness training programs running at most organizations have not caught up. Defenders are losing ground. The monitoring infrastructure was built for an attack pattern that is no longer the primary one. Where the Training Points Phishing awareness training is calibrated for email-borne threats. A user who hovers before clicking, checks the sender domain, and reports a suspicious attachment is an asset. The training addresses a real threat category. ...

I have submitted 193 job applications since January. 193 is a dataset. Confirmation emails arrive within seconds, denial letters on a schedule that matches no known business hours. The support chat deflection timing tells you which platform the company bought. After enough of them, you stop reading the message and start reading the system. HR AI agents are an injection surface that most organizations are not monitoring because they were not bought as security infrastructure. ...

Author: Mario Martinez Jr. (ku5e / Gary7) | TryHackMe USA Rank #76 | Top 1% Difficulty: Easy Topics: x86 Assembly, Opcodes, MOV/LEA/NOP, Arithmetic Instructions, Logical Instructions, Flags, Conditionals, Branching, Stack Operations, Function Calls Link: x86 Assembly Crash Course on TryHackMe Answers are redacted within the narrative to allow you to complete the tasks on your own, but a full table of answers is available at the end of this walkthrough. Assembly is the lowest level of human-readable language and the highest level a compiled binary can be reliably decompiled to. When you open a malware sample in Ghidra or x64dbg, you are reading assembly. There is no layer above it. This room covers the instructions you will see on every analysis: MOV, LEA, NOP, ADD, SUB, XOR, CMP, TEST, JMP, PUSH, POP, and CALL. Complete the x86 Architecture Overview room first if you have not already. ...