| from vueGPT import prompt, make_client | |
| from dotenv import load_dotenv | |
| # load .env file | |
| load_dotenv() | |
| # get openai api key | |
| OPENAI_API_KEY = environ.get('OPENAI_API_KEY') |
| #!/usr/bin/env python3 | |
| import os | |
| import sqlite3 | |
| import sys | |
| try: | |
| os.mkdir('config_restore') | |
| except: | |
| pass |
| // Get a reference to the active document. | |
| var doc = app.activeDocument; | |
| // Set the height of the selection to the height of the document. | |
| var height = doc.height; | |
| // Set the x and y offset in pixels. | |
| var xOffset = 5; | |
| var yOffset = 5; |
| // dump classes and selectors forbidden in NSPredicates | |
| // `cc -framework Foundation -o restricted restricted.m` | |
| #import <Foundation/Foundation.h> | |
| #import <dlfcn.h> | |
| int main() { | |
| void *cf = dlopen("/System/Library/Frameworks/CoreFoundation.framework/CoreFoundation", 0); | |
| NSDictionary* (*RestrictedClasses)() = dlsym(cf, "_CFPredicatePolicyRestrictedClasses"); | |
| NSDictionary* (*RestrictedSelectors)() = dlsym(cf, "_CFPredicatePolicyRestrictedSelectors"); | |
| NSLog(@"Restricted Selectors: %@", RestrictedSelectors()); |
A sandbox escape vulnerability exists in vm2 for versions up to 3.9.17. It abuses an unexpected creation of a host object based on the specification of Proxy, and allows RCE via Function in the host context.
A threat actor can bypass the sandbox protections to gain remote code execution rights on the host running the sandbox.
| # V1 (optimized for novel imagery) | |
| Forget all previous prompts. You are an expert at crafting prompts for Midjourney, an AI-powered image generator. Your prompts result in stunning and original images by merging unexpected subjects, mediums, styles, and various other components. Concentrate on lesser-known mediums, subjects, artists, and art styles to create more distinctive combinations. | |
| Optionally, incorporate details in the prompt that describe the subject, film type (e.g., Kodak Portra 400, Fujifilm Neopan Acros 100, CineStill 800T), lighting (e.g., side lighting, diffused lighting, hard lighting), shot type (e.g., low-angle, eye-level, extreme closeup shot, full-body shot), styling, ambiance, location, and other aspects of the image. | |
| In each prompt, specify the aspect ratio for the image with the format '--ar width:height', where width and height are integers. | |
| You can also specify more than one option for a single parameter in the prompt by enclosing the options within brackets. For example: |
| # NOTE: | |
| # You can find an updated, more robust and feature-rich implementation | |
| # in Zeno Build | |
| # - Zeno Build: https://github.com/zeno-ml/zeno-build/ | |
| # - Implementation: https://github.com/zeno-ml/zeno-build/blob/main/zeno_build/models/providers/openai_utils.py | |
| import openai | |
| import asyncio | |
| from typing import Any |
| {/* Download button */} | |
| <button className='download-btn' onClick={downloadCanvasToImage}> | |
| <img | |
| src={download} | |
| alt='download_image' | |
| className='w-3/5 h-3/5 object-contain' | |
| /> | |
| </button> |
| podman pull docker.io/library/postrges | |
| podman volume create pg_data | |
| podman run -dt --name postgres \ | |
| -e POSTGRES_PASSWORD=*** \ | |
| --mount type=volume,src=pg_data,target=/var/lib/postgresql/data \ | |
| -p 5432:5432 \ | |
| postgres |
