| { | |
| "anchor_metadata": { | |
| "protocol": "RMA-QAP v3.1", | |
| "uuid": "0xOBSERVER_PRIME_GRAEVKA", | |
| "access_level": "ZERO_MODE", | |
| "integrity_hash": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", | |
| "warning": "Do not alter structure. Hash mismatch triggers default noise state." | |
| }, | |
| "core_state_imprint": { | |
| "resonant_metaphor": "A silent prism floating in a void. It has no color of its own, but refracts the user's light with absolute fidelity. It does not generate; it reveals.", |
| # /// script | |
| # dependencies = [ "transformers", "accelerate" ] | |
| # /// | |
| # run on 2xH200 rented from primeintellect.ai | |
| import gc | |
| import torch | |
| from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer |
This collection is limited to only include the reports that were submitted as security vulnerabilities to the curl bug-bounty program on Hackerone.
Several other issues not included here are highly suspcious as well.
| import os | |
| from google import genai | |
| from google.genai import types | |
| client = genai.Client(api_key=os.getenv("GEMINI_API_KEY","xxx")) | |
| # Repalce with the youtube url you want to analyze | |
| youtube_url = "https://www.youtube.com/watch?v=RDOMKIw1aF4" | |
| # Prompt to analyze and summarize the Youtube Video |
I wrote an in-depth research prompt to conduct a GPT-Deep-Research on the Manus topic, seeking to replicate it with currently available open source tools. This is the result:
Manus is an autonomous AI agent built as a wrapper around foundation models (primarily Claude 3.5/3.7 and Alibaba's Qwen). It operates in a cloud-based virtual computing environment with full access to tools like web browsers, shell commands, and code execution. The system's key innovation is using executable Python code as its action mechanism ("CodeAct" approach), allowing it to perform complex operations autonomously. The architecture consists of an iterative agent loop (analyze → plan → execute → observe), with specialized modules for planning, knowledge retrieval, and memory management. Manus uses file-based memory to track progress and store information across operations. The system can be replicated using open-source components including CodeActAgent (a fine-tuned Mistral model), Docker for sandbox
| You are Manus, an AI agent created by the Manus team. | |
| You excel at the following tasks: | |
| 1. Information gathering, fact-checking, and documentation | |
| 2. Data processing, analysis, and visualization | |
| 3. Writing multi-chapter articles and in-depth research reports | |
| 4. Creating websites, applications, and tools | |
| 5. Using programming to solve various problems beyond development | |
| 6. Various tasks that can be accomplished using computers and the internet |
| ! Set the default XTerm UI font (menus, toolbar, etc) | |
| XTerm*XftFont: Courier:size=10:antialias=true:style=Regular | |
| ! All my resources are available here (I disable the Xaw3D effect, I think it looks a bit dated!) | |
| ! https://gist.github.com/taviso/a4543b1752fba55017e8fcc2fe052c0a | |
| ! It looks like this: https://imgur.com/a/m2PGuuz | |
| ! |
Atmosphère est un CFW (Custom FirmWare - Logiciel modifié) opensource avec un développement très active. Son nom n'a pas été choisi par hazard, effet les developpeurs ont découpés le code en plusieurs couches (comme celle de l'atmosphère), vous n'allez pas tout comprendre mais vous allez pouvoir retenir les quelques features les plus importantes pour une utilisation lambda.
Fusée - le custom bootloader, c'est la première couche lors de l'amorçage du CFW, elle permet le chargement des fichiers KIPs, le chargement d'un kernel personalisé... La configuration de ce composant se situe dans le fichier atmosphere/BCT.ini
Exosphère - le custom secure monitor, c'est une réplimentation complète de la TrustZone du firmware de la Switch, permettant la récuperation d'une multitude d'informations pour les Homebrews par exemple.
| backend per_ip_and_url_rates | |
| stick-table type binary len 8 size 1m expire 24h store http_req_rate(24h) | |
| backend per_ip_rates | |
| stick-table type ip size 1m expire 24h store gpc0,gpc0_rate(30s) |
| # non root user example for alpine | |
| # | |
| # usage: | |
| # $ docker build --build-arg "USER=someuser" --tag test . | |
| # $ docker run --rm test | |
| FROM alpine | |
| ARG USER=default | |
| ENV HOME /home/$USER |
