Top technology stories: US government launches new AI cybersecurity challenge; China outlines new rules for facial recognition technology; How to make AI more energy efficient.
Countering China and bolstering national security dominated the conversation in a Hilton hotel on Guam, 15 hours before and oceans away from the Milwaukee arena hosting the first Republican primary debate.
Nine members of the GOP-led House committee on natural resources convened in the US-governed Pacific island territory for a rare field hearing – during the summer recess – on countering China’s influence in the region.
At a time when Democrats and Republicans view China as an economic and global security threat, island nations who offer the US military proximity to China in exchange for aid emphasized they are especially vulnerable to Chinese cyber-attacks and economic exploitation as they struggle to recover from the pandemic.
• Encryption and segmentation: These operate on the assumption some fraction of the network is already compromised. Restricting the reach and utility of any captured data and accessible networks will mitigate the damage even on breached systems.
• SBOM documentation: Regulatory compliance can be driven by industry organizations and the government, but it will take time to establish standards. SBOM documentation is an essential foundation for best practices.
If “democracy dies in darkness,” and that includes lies of omission in reporting, then cybersecurity suffers the same fate with backdoors. The corollary is “don’t roll your own crypto” even if well-intentioned. The arguments for weakening encryption to make law enforcement easier falls demonstrably flat, with TETRA just the latest example. Secrets rarely stay that way forever, and sensitive data is more remotely accessible than at any time in history. Privacy and global security affect us all, and the existence of these single points of failure in our cybersecurity efforts are unsustainable and will have unforeseeable consequences. We need to innovate and evolve the internet away from this model to have durable security assurances.
One of the most promising developments in the fight against cybersecurity threats is the use of artificial intelligence (AI). This cutting-edge technology has the potential to revolutionize the way organizations manage cyberthreats, offering unprecedented levels of protection and adaptability. AI is set to be embedded into every security product, enabling organizations to quickly remediate attacks and stay ahead of the threat landscape. However, bad actors are equally interested in unlocking the power of AI to easily launch sophisticated and targeted attacks.
The convergence of AI and cybersecurity will create opportunities and challenges for organizations. In this blog post, we will delve into the transformative impact that AI will have on cybersecurity, explore its potential to empower organizations to stay ahead of threats, and examine the ways bad actors could use it for their own nefarious purposes.
By harnessing the power of AI while remaining vigilant to its potential misuse, organizations can stay ahead of emerging threats and better protect their valuable applications, APIs, and data.
Additionally, iProov reveals a 295 percent yearly increase in biometric attacks that use novel face swaps. Using this technique, attackers generate synthetic images with AI, either replacing the face of the victim with a video of him to bypass liveness checks or with the face of the attacker itself.
But beyond deep fakes and other more rudimentary presentation attacks where identities are spoofed using masks or other presentation techniques, another type of attack is gaining ground: digital injection.
The FBI is warning the public that cyber criminals are embedding malicious code in mobile beta-testing applications (apps) to defraud potential victims. Beta-testing apps are online services for testing of mobile apps prior to official release. The beta apps typically are not subject to mobile operating systems’ review processes.
The malicious apps enable theft of personally identifiable information (PII), financial account access, or device takeover. The apps may appear legitimate by using names, images, or descriptions similar to popular apps. Cyber criminals often use phishing or romance scams to establish communications with the victim, then direct the victim to download a mobile beta-testing app housed within a mobile beta-testing app environment, promising incentives such as large financial payouts.
In this video i will show everyone the Theoretical & Practical side of understanding and learning Reverse-Engineering, to modify Machine-Code/Code overall in the Memory inside Binary Software Files on Systems, and also the Fundamentals about the System Architechture x64/x32-x86 Bit, as how it works in the smallest of Bits/Bytes form on the Memory-Layout Architechture. I will be showing a variety of Techniques like Cracking Games, Manipulating basic “Hello World” compiled C++ code Binary, and overall i will show different kind of Debugging/Reverse-Engineering Techniques on the Tool x64DBG.
- Educational Purposes Only.
If the Video was helpful and useful for learning Reverse-Engineering in a sense to understand Problematic Bugs/Vulnerabilities or Code in a Binary, subscribe for more videos!. Thanks.
Continue reading “Reverse-Engineering — How Do Hackers Debug & Hack System Software/Services” »
So, the bad AI has been arriving. On purpose. It reminds me of when hackers once or a few times checked traffic lights to both green and caused accidents resulting in human harm. That’s sad that such great tools are misused.
ChatGPT has become popular, influencing how people work and what they may find online. Many people, even those who haven’t tried it, are intrigued by the potential of AI chatbots. The prevalence of generative AI models has altered the nature of potential dangers. Evidence of FraudGPT’s emergence can now be seen in recent threads on the Dark Web Forum. Cybercriminals have investigated ways to profit from this trend.
The researchers at Netenrich have uncovered a promising new artificial intelligence tool called “FraudGPT.” This AI bot was built specifically for malicious activities, including sending spear phishing emails, developing cracking tools, doing carding, etc. The product may be purchased on numerous Dark Web marketplaces and the Telegram app.
Continue reading “Meet FraudGPT: The Dark Side Twin of ChatGPT” »
So if I understand this…send a bot to catch a bot?
Israeli tech start-up Cyabra, which worked with Elon Musk to evaluate the presence of bots on Twitter, released a new tool that can detect AI-generated text, images and profiles.
Don’t put anything into an AI tool you wouldn’t want to show up in someone else’s query or give hackers access to. While inputting every bit of information you can think of in an innovation project is tempting, you have to be careful. Oversharing proprietary information on a generative AI is a growing concern for companies. You can fall victim to inconsistent messaging and branding and potentially share information that shouldn’t be available to the public. We’re also seeing increased cyber criminals hacking into generative AI platforms.
Generative AI’s knowledge isn’t up to date. So your query results shouldn’t necessarily be taken at face value. It probably won’t know about recent competitive pivots, legislation or compliance updates. Use your expertise to research AI insight to make sure what you’re getting is accurate. And remember, AI bias is prevalent, so it’s just as essential to cross-check research for that, too. Again, this is where having smart, meticulous people on board will help to refine AI insight. They know your industry and organization better than AI and can use queries as a helpful starting point for something bigger.
The promise of AI in innovation is huge, as it unlocks unprecedented efficiency and head-turning output. We’re only seeing the tip of the iceberg as it relates to the promise the technology holds, so lean into it. But do so with governance—no one wants snake tail for dinner.
