logo
How AI's Greatest Strengths Are Becoming Its Biggest Weaknesses

How AI's Greatest Strengths Are Becoming Its Biggest Weaknesses

Geeky Gadgets03-07-2025
What if the very tools designed to transform communication and decision-making could also be weaponized against us? Large Language Models (LLMs), celebrated for their ability to process and generate human-like text, are increasingly becoming targets for sophisticated cyberattacks. From prompt injection schemes that manipulate outputs to data exfiltration risks that expose sensitive information, the vulnerabilities of LLMs are as expansive as their capabilities. The stakes are high: without robust defenses, these AI systems could inadvertently become conduits for misinformation, harmful content, or even malicious code. The question isn't whether these threats will emerge—it's how prepared we are to confront them.
IBM Technology team provide more insights into the critical strategies needed to secure LLMs against evolving threats. You'll uncover how proxy-based security frameworks act as digital gatekeepers, intercepting and neutralizing risks in real time. We'll explore why training alone is insufficient to safeguard these systems and how integrating AI-driven defenses can elevate your security posture. Whether you're a developer, business leader, or AI enthusiast, this guide offers actionable insights to protect the integrity of LLMs while preserving their immense potential. After all, the future of AI depends not just on innovation but on the strength of the defenses we build today. Securing Large Language Models Key Security Threats Facing LLMs
LLMs face a range of security threats that can undermine their reliability, integrity, and safety. Among the most significant are prompt injection attacks, where malicious actors manipulate input prompts to influence the model's behavior. For example, attackers may bypass safety protocols or inject harmful instructions, leading the model to generate inappropriate or dangerous outputs.
Other critical threats include: Data Exfiltration: Sensitive information, such as customer data or proprietary details, can be unintentionally leaked through model outputs.
Sensitive information, such as customer data or proprietary details, can be unintentionally leaked through model outputs. Harmful Outputs: LLMs may inadvertently generate hate speech, abusive language, or profanity (HAP), which can harm users or damage reputations.
LLMs may inadvertently generate hate speech, abusive language, or profanity (HAP), which can harm users or damage reputations. Malicious Code Generation: Attackers can exploit LLMs to create harmful scripts, embed malicious URLs, or automate cyberattacks.
Attackers can exploit LLMs to create harmful scripts, embed malicious URLs, or automate cyberattacks. Traditional Vulnerabilities: LLMs can be manipulated to expose web vulnerabilities, such as cross-site scripting (XSS) or SQL injection, posing risks to connected systems.
These threats highlight the importance of implementing a comprehensive security framework to protect LLMs and their users from exploitation. How Proxy-Based Security Protects LLMs
A proxy-based security framework serves as a protective intermediary between users and LLMs, intercepting and managing interactions in real time. This approach integrates a policy engine to enforce strict rules governing both inputs and outputs, making sure harmful or unauthorized activity is detected and mitigated.
For instance: If a user attempts to inject malicious code, the proxy can identify and neutralize the threat before it reaches the LLM.
The policy engine can filter inappropriate outputs, preventing the model from generating harmful or damaging content.
This framework is not only effective but also scalable, offering consistent protection across multiple LLMs. Its adaptability ensures that it can evolve alongside emerging threats, making it a reliable solution for safeguarding AI systems. LLM Hacking Defense: Strategies for Secure AI
Watch this video on YouTube.
Advance your skills in Large Language Models (LLMs) by reading more of our detailed content. Using AI for Enhanced Security
To counter increasingly sophisticated attacks, proxy-based systems can incorporate advanced AI models such as LlamaGuard and BERT. These models analyze patterns in user inputs and outputs, identifying potential risks with high precision. By integrating AI into your security framework, you can proactively detect and respond to threats before they escalate.
Centralized monitoring further strengthens this approach by consolidating logs and reports from multiple LLMs into a unified view. This enables you to: Identify trends and recurring vulnerabilities across systems.
Detect anomalies that may indicate an ongoing or imminent attack.
Respond to threats more efficiently, minimizing potential damage.
By combining AI-driven analysis with centralized monitoring, you can maintain a comprehensive and dynamic security posture. Why Training Alone Isn't Enough
While training LLMs to resist attacks is a critical component of security, it has inherent limitations. Training requires significant resources and is challenging to scale across multiple models. Additionally, frequent updates to LLMs necessitate retraining, which can be both time-intensive and costly. These constraints make it clear that training alone cannot provide the comprehensive protection required to address the diverse and evolving threats faced by LLMs.
Instead, training should be viewed as one layer of a broader security strategy, complemented by other measures such as proxy-based systems and policy enforcement. Adopting a Defense in Depth Strategy
To achieve robust security, a defense in depth strategy is essential. This approach combines multiple layers of protection, making sure redundancy and resilience against a wide range of threats. Key components of this strategy include: Model Training: Teaching LLMs to recognize and reject harmful inputs, reducing their vulnerability to manipulation.
Teaching LLMs to recognize and reject harmful inputs, reducing their vulnerability to manipulation. Proxy-Based Systems: Acting as a real-time filter to intercept and neutralize threats before they reach the model.
Acting as a real-time filter to intercept and neutralize threats before they reach the model. Policy Engines: Enforcing strict rules to govern interactions, making sure compliance with security and ethical standards.
Enforcing strict rules to govern interactions, making sure compliance with security and ethical standards. AI Integration: Using advanced models to analyze patterns and detect emerging risks with high accuracy.
By layering these defenses, you can create a robust security framework that addresses both current and future threats. This approach ensures that even if one layer is bypassed, others remain in place to mitigate risks and protect the integrity of your LLMs. Securing the Future of LLMs
In today's rapidly evolving threat landscape, securing LLMs requires a proactive and multi-faceted approach. Understanding the risks they face is the first step toward implementing effective defenses. A proxy-based security framework, supported by policy engines and enhanced with AI-driven analysis, offers a scalable and adaptable solution to protect these advanced systems.
By adopting a defense in depth strategy, you can ensure that LLMs remain secure, reliable, and effective. This layered approach not only safeguards against current threats but also provides the flexibility to address emerging challenges. With the right security measures in place, you can harness the full potential of LLMs while maintaining the highest standards of safety and integrity.
Media Credit: IBM Technology Filed Under: AI, Technology News, Top News
Latest Geeky Gadgets Deals
Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Orange background

Try Our AI Features

Explore what Daily8 AI can do for you:

Comments

No comments yet...

Related Articles

AI-run investment bank OffDeal raises $12 million
AI-run investment bank OffDeal raises $12 million

Finextra

time25 minutes ago

  • Finextra

AI-run investment bank OffDeal raises $12 million

We are excited to announce that OffDeal has raised a $12M Series A led by Radical Ventures to build the world's first AI-native investment bank, bringing our total funding to $17M. 0 Our Series A comes less than 10 months after we announced our Seed. Since then, our small, but mighty team has already launched over 30 sell-side M&A transactions and has delivered numerous life-changing outcomes to our clients. Wall Street's playbook works well, but only for billion-dollar deals - it breaks. Traditional firms run oversized teams on outdated software, making smaller M&A transactions uneconomical. This leaves millions of small business owners with nowhere to turn for the most important sale of their lives… Until now. We're building what Goldman Sachs would have looked like if it was built today - in 2025. Our engineers built software to automate analyst work with AI, so our in-house bankers can focus on dealmaking and delivering life-changing exits to our clients. Our mission is to democratize access to world-class investment banking services so that all entrepreneurs are able to realize the full value of their life's work. We're scaling fast and hiring across all roles - if you or someone you know is interested in building the future of investment banking, we'd love to hear from you! This round was led by Radical Ventures, with participation from Y Combinator, Rebel Fund, and Centre Street Partners. We are also honored to welcome an amazing group of angels joining the round that include current and former execs of leading financial institutions such as Evercore, AllianceBernstein, McKinsey, as well as recognized tech leaders from Cognition, Rogo, Farther, Firsthand, Eight Sleep, Partiful, and many others. We wholeheartedly thank our clients, our world-class team, and our amazing investors for their continued support and vote of confidence in our mission.

Apple is set to unveil its first foldable iPhone next year - with an eye-watering price tag
Apple is set to unveil its first foldable iPhone next year - with an eye-watering price tag

Daily Mail​

time26 minutes ago

  • Daily Mail​

Apple is set to unveil its first foldable iPhone next year - with an eye-watering price tag

It's one of the biggest tech firms in the world. But Apple is one of the few companies yet to unveil a foldable device. However, that may be soon about to change, because Apple is allegedly readying its first foldable iPhone – following in the footsteps of Samsung, Huawei and Motorola. According to JP Morgan analyst, Samik Chatterjee, Apple is set to launch its first foldable iPhone in September 2026. If Apple continues with its traditional iPhone naming system, this suggests the iPhone 18 could be a flip phone. 'With the upgrades to the iPhone 17 series to be released this fall expected to be fairly limited, investor focus has already turned to the 2026 fall launches with Apple expected to launch its first foldable iPhone as part of the iPhone 18 lineup in September 2026, featuring a book-style fold similar to Samsung's Galaxy Z Fold series,' Mr Chatterjee said in a note to clients, seen by CNBC. Unsurprisingly, the foldable iPhone is likely to come with a hefty price tag. Mr Chatterjee predicts that the device will retail at a whopping $1,999 - $1,000 more than the current iPhone 16 Pro. The device, which is rumoured to be called the 'iPhone Fold', is expected to feature a 7.8-inch inner display and a 5.5-inch outer screen. For comparison, Samsung's Galaxy Z Fold 7, which was released last week, features an 8-inch inner display, and a 6.5-inch outer screen. One of the biggest bugbears with Samsung's foldable is the 'crease' - a visible line running down the centre of the phone. However, Apple's version is said to be crease-free, although how the tech giant is able to achieve this remains unclear. In terms of price, the iPhone Fold is expected to be Apple's most expensive smartphone yet. If the device really does start at $1,999 as Mr Chatterjee predicts, that would be $400 more than Apple's current most expensive smartphone - the 1TB version of the iPhone 16 Pro Max ($1,599). However, it's comparable to the Samsung Galaxy Z Fold, which is priced at $1,999 - $2,419, depending on storage. Mr Chatterjee predicts the new device will generate a whopping $65 billion in revenue for Apple, leading to a 'high-single-digit' earnings boost over the medium term. As for shipments, the experts expects volumes to start in the 'low teens' of millions when the phone is released in 2027, This will then climb to the 'mid-40s of millions' by 2029, he added. Back in 2022, YouTubers in China created an impressive prototype of what the first foldable iPhone could look like. The prototype, called iPhone V, folds down a central hinge in the screen and features silver iPhone lettering on the hinge, plus the iconic Apple icon on the back. It was built by the engineers over more than 200 days using an iPhone X and the folding mechanism from Motorola's Razr. MailOnline has contacted Apple for comment. THE TRILLION DOLLAR RISE OF APPLE 1976: Founders Steve Jobs, Steve Wozniak and Ronald Wayne created the company on April 1 1976 as they set about selling computer kits to hobbyists, each of which was built by Wozniak. The first product was the Apple I. 1977: Apple released the Apple II in June, which was the first PC made for the mass market. 1981: Jobs became chairman. 1984: The Macintosh was introduced during an ad break for the Super Bowl and later officially unveiled during a launch event. It was discontinued a year later and Jobs left the firm. 1987: Apple released the Macintosh II, the first colour Mac. 1997: Apple announces it will acquire NeXT software in a $400 million deal that involves Jobs returning to Apple as interim CEO. He officially took the role in 2000. 2001: Apple introduced iTunes, OS X and the first-generation iPod. The first iPod MP3 music player was released on October 23, 2001, at an event in Cupertino and was able to hold up to 1,000 songs. 2007: Apple unveils the iPhone. 2010: The first iPad was unveiled. 2011: Jobs resigned in 2011 due to illness, handing the CEO title to Tim Cook. Jobs died in October from pancreatic cancer. 2014: Apple unveiled the Apple Watch. It also unveiled its first larger iPhones - the 6 and 6 Plus. 2015: After purchasing Beats from Dr Dre, Apple launched Apple Music to compete with Spotify and other music streaming services. 2016: Apple returned to its roots and announced the 4-inch iPhone SE. Meanwhile, the firm is embroiled in a legal battle with the FBI, involving the agency demanding access to the locked phone used by Syed Farook, who died in a shootout after carrying out a deadly December attack in San Bernardino, California with his wife. The court order was dropped on March 28 after the FBI said a third party was able to unlock the device. 2017: Apple introduces the iPhone X, which removes the home button to make way for a futuristic edge-to-edge screen design and a new FaceID system that uses advanced sensors and lasers to unlock phones with just the owner's face. Apple CEO Steve Jobs speaks at an Apple event at Apple headquarters in Cupertino, Calif. 2018: In a first for the company, Apple introduces new features in its latest operating system, iOS 12, that encourage users to manage and spend less time on their devices. The move was spawned by a strongly worded letter from shareholders that urged the firm to address the growing problem of smartphone addiction among kids and teenagers. 2019: In January, Apple reports its first decline in revenues and profits in a decade. CEO Tim Cook partly blamed steep declines in revenue from China. 2020: In March, Apple closes all its bricks and mortar retail stores outside of China in response to coronavirus. 2021: In an online virtual event in April CEO Tim Cook declared Apple's goal of becoming carbon neutral for Earth Day. Later in the year the iPhone 13 was announced. 2022: In September the iPhone 14 was announced. One of the new features included a new sensor to detect if a user had been in a car crash as well as an improved camera system. 2023: Apple brought back its 'Home Pod' after the first generation was discontinued. The 'Home Pod' can be seen as an alternative to Amazon's Alexa or Google Home as it is powered by voice commands.

Sainsbury's blames Visa card issues for online payment failure
Sainsbury's blames Visa card issues for online payment failure

Sky News

timean hour ago

  • Sky News

Sainsbury's blames Visa card issues for online payment failure

J Sainsbury, the supermarket chain, was on Wednesday racing to resolve an issue with the card payments giant Visa which was impacting customers' ability to pay for their online grocery orders. Sky News understands that Sainsbury's is working with Visa to address the issue after a number of shoppers reported that their card payments had failed. The retailer ruled out the possibility of a cyberattack and said its website and app were functioning normally, with no direct impact on customers. The issue nevertheless illustrates the extent to which the industry is on high alert for cybersecurity-related incidents after a spate of attacks which have raised concerns about the sector's resilience. In recent months, major British retailers including Marks & Spencer, the Co-op and Harrods have been the victim of cyberattacks, with the impact on M&S particularly acute. M&S has said the attack on its systems would cost it at least £300m and forced it to suspend online orders for months. The Co-op saw in-store availability of thousands of products disrupted for several weeks. A Sainsbury's spokesperson said, "We're working with one of our payment providers to resolve a temporary issue processing some payments for our Groceries Online service.

DOWNLOAD THE APP

Get Started Now: Download the App

Ready to dive into a world of global content with local flavor? Download Daily8 app today from your preferred app store and start exploring.
app-storeplay-store