Disable Windows Defender Using (Defender Control)

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Since Vista, Microsoft Defender is included with Windows . It’s a small piece of software that runs in the background to help protect ,your computer from malware (malicious software) like viruses, spyware, and other potentially unwanted software. Some spyware protection is better than none, and it’s built in and free! But… if you are already running something that provides great anti-malware protection, defender will probably wasting precious resources , there’s no need to have more than one application running at a time.

The problem with all Defender versions in Windows Vista and above is it’s integrated into the operating system and installs by default with no visible or hidden option to uninstall. Many people are looking for ways to disable or remove it from their system as they prefer to use other software , for example on Windows 8 and 10 you cannot turn off Microsoft Defender completely anymore , A click on Settings in Microsoft Defender opens the control panel for the program in the new Windows Settings application. You can turn the program’s real-time protection off temporarily, but if it’s off for a while Windows will turn it back on automatically. It is unclear why Microsoft made the decision to change the behavior of Microsoft Defender in this regard. What is certain however is that it will annoy users who want to disable it permanently on the computer they are working on. Defender Control is a small Portable freeware which will allow you to disable Microsoft Defender in Windows 10 completely.

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Italian Watchdog Bans OpenAI's ChatGPT Over Data Protection Concerns

The Italian data protection watchdog, Garante per la Protezione dei Dati Personali (aka Garante), has imposed a temporary ban of OpenAI's ChatGPT service in the country, citing data protection concerns.

To that end, it has ordered the company to stop processing users' data with immediate effect, stating it intends to investigate the company over whether it's unlawfully processing such data in violation of the E.U. General Data Protection Regulation (GDPR) laws.

"No information is provided to users and data subjects whose data are collected by Open AI," the Garante noted. "More importantly, there appears to be no legal basis underpinning the massive collection and processing of personal data in order to 'train' the algorithms on which the platform relies."

ChatGPT, which is estimated to have reached over 100 million monthly active users since its release late last year, has not disclosed what it used to train its latest large language model (LLM), GPT-4, or how it trained it.

That said, its predecessor GPT-3 utilizes text sourced from books, Wikipedia, and Common Crawl, the latter of which maintains an "open repository of web crawl data that can be accessed and analyzed by anyone."

The Garante also pointed to the lack of any age verification system to prevent minors from accessing the service, potentially exposing them to "inappropriate" responses. Google's own chatbot, called Bard, is only open to users over the age of 18.

Additionally, the regulator raised questions about the accuracy of the information surfaced by ChatGPT, while also highlighting a data breach the service suffered earlier last month that exposed some users' chat titles and payment-related information.

In response to the order, OpenAI has blocked its generative AI chatbot from being accessed by users with an Italian IP address. It also said it's issuing refunds to subscribers of ChatGPT Plus, in addition to pausing subscription renewals.

The San Francisco-based company further emphasized that it provides ChatGPT in compliance with GDPR and other privacy laws. ChatGPT is already blocked in China, Iran, North Korea, and Russia.

In a statement shared with Reuters, OpenAI said it actively works to "reduce personal data in training our AI systems like ChatGPT because we want our AI to learn about the world, not about private individuals."

OpenAI has 20 days to notify the Garante of the measures it has taken to bring it in compliance, or risk facing fines of up to €20 million or 4% of the total worldwide annual turnover, whichever is higher.

The ban, however, is not expected to impact applications from other companies that employ OpenAI's technology to augment their services, including Microsoft's Bing search engine and its Copilot offerings.

The development also comes as Europol warned that LLMs like ChatGPT are likely to help generate malicious code, facilitate fraud, and "offer criminals new opportunities, especially for crimes involving social engineering, given its abilities to respond to messages in context and adopt a specific writing style."

This is not the first time AI-focused companies have come under the radar. Last year, controversial facial recognition firm Clearview AI was fined by multiple European regulators for scraping users' publicly available photos without consent to train its identity-matching service.

It has also run afoul of privacy laws in Australia, Canada, and the U.S., with several countries ordering the company to delete all of the data it obtained in such a manner.

Clearview AI told the BBC News last week that it has run nearly a million searches for U.S. law enforcement agencies, despite being permanently banned from selling its faceprint database within the country.

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Dump Database Using Sqlmap

 

Introduction:

Sqlmap is an open source penetration testing tool that automates the process of detecting and exploiting SQL injection flaws and taking over of database servers. It comes with a powerful detection engine, many niche features for the ultimate penetration tester and a broad range of switches lasting from database fingerprinting, over data fetching from the database, to accessing the underlying file system and executing commands on the operating system via out-of-band connections.

Features:

Full support for MySQL, Oracle, PostgreSQL, Microsoft SQL Server, Microsoft Access, IBM DB2, SQLite, Firebird, Sybase, SAP MaxDB, Informix, MariaDB, MemSQL, TiDB, CockroachDB, HSQLDB, H2, MonetDB, Apache Derby, Amazon Redshift, Vertica, Mckoi, Presto, Altibase, MimerSQL, CrateDB, Greenplum, Drizzle, Apache Ignite, Cubrid, InterSystems Cache, IRIS, eXtremeDB, FrontBase, Raima Database Manager, YugabyteDB, ClickHouse and Virtuoso database management systems.

Full support for six SQL injection techniques: boolean-based blind, time-based blind, error-based, UNION query-based, stacked queries and out-of-band.

Support to directly connect to the database without passing via a SQL injection, by providing DBMS credentials, IP address, port and database name.

Support to enumerate users, password hashes, privileges, roles, databases, tables and columns.

Automatic recognition of password hash formats and support for cracking them using a dictionary-based attack.

Support to dump database tables entirely, a range of entries or specific columns as per user's choice. The user can also choose to dump only a range of characters from each column's entry.

Support to search for specific database names, specific tables across all databases or specific columns across all databases' tables. This is useful, for instance, to identify tables containing custom application credentials where relevant columns' names contain string like name and pass.

Support to download and upload any file from the database server underlying file system when the database software is MySQL, PostgreSQL or Microsoft SQL Server.

Support to execute arbitrary commands and retrieve their standard output on the database server underlying operating system when the database software is MySQL, PostgreSQL or Microsoft SQL Server.

Support to establish an out-of-band stateful TCP connection between the attacker machine and the database server underlying operating system. This channel can be an interactive command prompt, a Meterpreter session or a graphical user interface (VNC) session as per user's choice.

Support for database process' user privilege escalation via Metasploit's Meterpreter getsystem command.

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Exploit Android Using Metasploit

 

In this article, we will cover payload(virus) creation for android, establishing meterpreter connection and learning about basics of metasploit. Now, sit back, relax and enjoy the show.

The Metasploit Project is a computer security project that provides information about security vulnerabilities and aids in penetration testing and IDS signature development.

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Artificial intelligence is now being created using real brain cells

 

Machine-learning models like the one that powers ChatGPT are generating essays, short stories, and entire podcasts. But scientists are looking into another way of computing that could be just as efficient and powerful, and it’s in our brains.

In a new article published on Tuesday in Frontiers, a large international collaboration led by researchers at John Hopkins University (JHU) details how brain-machine technologies are the newest frontier in biocomputing, and provides a roadmap as to how to make it a reality.

As the paper explains, organoid intelligence (OI) is an emerging field where researchers are developing biological computing using 3D cultures of human brain cells (brain organoids) and brain-machine interface technologies. These organoids share aspects of brain structure and function that play a key role in cognitive functions like learning and memory. They would essentially serve as biological hardware, and  could one day be even more efficient than current computers running AI programs.

“The vision of OI is to use the power of the biological system to advance the field of live sciences, bioengineering, and computer science,” Lena Smirnova, a researcher at JHU and an author on the paper, wrote in an email to Motherboard. "If we look at how efficiently the human brain operates in processing of information, learning etc, it is tempting to translate and model that to have a system which will work faster and more efficiently [than] current computers.”

For example, the human brain has an incredible capacity to store information: the average noggin can store an estimated 2,500 terabytes, according to the paper. The researchers envision complex 3D cell structures that would be connected to AI and machine learning systems.

“We’re reaching the physical limits of silicon computers because we cannot pack more transistors into a tiny chip,” Thomas Hartung, a researcher at JHU and one of the study’s authors, said in a press release. “But the brain is wired completely differently. It has about 100 [billion] neurons linked through over 1015 connection points. It’s an enormous power difference compared to our current technology.”

Researchers have previously combined the biological and synthetic to teach brain cells how to play Pong––a proof of concept that was conducted by some of the same scientists involved in this initiative.  That project involved the creation of a DishBrain system, where researchers created a brain-computer interface, providing neurons with simple electrical sensory input and feedback that allowed them to “learn” the game.

However, the new paper sees even bigger applications than getting cells to play video games. For one, brain organoids could have applications in medicine. The authors write that OI research will allow for the exploration of inter-individual neurodevelopmental and neurodegenerative disorders, and revolutionize drug testing research. 

Just as with artificial intelligence, there are ethical concerns, and the researchers acknowledge that. To ensure OI develops in an ethically and socially responsive manner, they propose an ‘embedded ethics’ approach, where “interdisciplinary and representative teams of ethicists, researchers, and members of the public identify, discuss, and analyze ethical issues and feed these back to inform future research and work.”

This technology is not exactly ready to be deployed tomorrow. However, the researchers position the papers as being a jumping-off point for more research.

“We have functional brain organoids already, since we have an electrophysiological active system, which has synchronous electrical activity and is responsive to chemical and electrical stimuli,” Smirnova wrote. “The next step we are working on is to characterize and optimize the system further by demonstrating key molecular and cellular aspects of learning in particular [to] develop a model of long-term learning.”

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