Category: Insights

Understanding and Responding to Different Types of Social Engineering Threats

Posted on by Nicole Tidwell

Social engineering is a deceptive and manipulative tactic used by cybercriminals to exploit human psychology and gain unauthorized access to sensitive information. In the current digital age, where personal and financial data is at risk, it is crucial to be aware of various social engineering threats and take steps to protect ourselves. 

Today, we’ll take an in-depth look at social engineering, explore some common types of social engineering attacks, and discuss solutions to protect your data from imposters. 

What Is Social Engineering?

At its core, social engineering is an art of deception. Instead of exploiting vulnerabilities in computer systems, social engineers manipulate individuals into divulging confidential information or performing actions that benefit the attacker. By preying on human psychology and trust, they gain access to personal, financial, or sensitive data. 

These types of threats can be particularly difficult to mitigate using traditional security systems because there is no “hole in the code” that can be patched to solve the issue. That’s not to say that there is no solution to social engineering attacks; rather, addressing them in a truly secure way requires a more holistic approach than simply increasing perimeter security. 

While they can vary greatly in tactics, most types of social engineering attacks have common goals. These typically involve gaining access to your systems in order to steal or tamper with valuable information, commit financial fraud, or compromise the security of individuals or organizations. 

Types of Social Engineering Threats

Before we discuss how to keep your data safe, it’s important to understand some of the types of social engineering attacks your data may face. While there is no end to the potential number of ways in which scammers can attempt to gain your confidence, the following are a few of the most common examples you may encounter. 

Phishing

Phishing is one of the most prevalent types of social engineering attacks. These attacks involve impersonating a trustworthy entity, such as a bank or a popular online service, to trick individuals into revealing sensitive information like usernames, passwords, or credit card details. Phishing attacks are typically carried out through emails, text messages, or fake websites designed to resemble legitimate ones.

Common phishing techniques include sending deceptive emails that mimic reputable organizations, creating fake login pages to steal login credentials, and using urgent or alarming language to prompt immediate action without stopping to assess the source of the message more thoroughly. 

Pretexting

Fundamentally similar to phishing, pretexting involves creating a false scenario to deceive individuals into sharing confidential information. The attacker creates a pretext to gain the target’s trust, often assuming a false identity to sell the narrative. They may pose as a co-worker, customer support representative, or contractor to manipulate victims into revealing sensitive data or performing actions that compromise security. 

Pretexting attacks often involve the scammer doing research and playing a slightly longer game to help them establish credibility. This allows them to leverage personal or emotional connections, and create a genuine sense of urgency. 

Baiting

Baiting attacks lure people into taking specific actions with an enticing or appealing offer. Unlike the previous two types of social engineering attacks, which primarily prey on fear, baiting exploits people’s natural curiosity or greed to trick individuals into compromising their security. 

Different forms of baiting attacks include leaving infected USB drives labeled as important files, offering free downloads of pirated software that contains malware, or enticing users with the promise of prizes or rewards in exchange for sensitive information. While this may seem somewhat far-fetched, research has shown that hardware-based baiting scams can be a particularly effective social engineering threat vector. 

Tailgating

Tailgating is an even more physical type of social engineering attack. Also known as piggybacking, these attacks involve an attacker gaining access to secure servers by physically following an authorized person through secured access points. This type of attack exploits the natural human tendency to hold the door open for others or be polite, allowing the attacker to gain unauthorized entry.

Tailgating attacks can occur in various settings, such as office buildings, data centers, or restricted areas. By blending in or exploiting moments of distraction, the attacker bypasses security measures and gains access to sensitive locations or systems.

Impersonation

A more in-depth alternative to tailgating is impersonation, where attackers assume the identity of legitimately authorized parties to gain access to your databases. Attackers may pose as employees, customers, and service providers in order to be let into places where they can then hack into your databases more easily.

Methods employed by impersonators can include using fake email addresses or phone numbers, manipulating caller IDs, or creating realistic social media profiles to establish credibility. 

Quid Pro Quo

Perhaps the most direct form of social engineering attacks, quid pro quo exploits involve an exchange of something valuable in return for sensitive information or access. Rather than tricking targets into unwittingly granting them access, attackers promise a benefit or favor in exchange for personal or confidential data. This type of social engineering attack often targets employees within organizations. 

Examples of quid pro quo schemes can include a scammer posing as an IT support technician offering free technical assistance in exchange for login credentials or an attacker promising a substantial discount or exclusive access to a service in return for sensitive financial information. 

Protecting Against Different Types of Social Engineering Threats

As we mentioned above, addressing social engineering threats requires a fundamentally different approach than other areas of cyber security. Increasing the strength of passwords or introducing measures to prevent software-based attacks such as cache poisoning is completely ineffective when hackers gain access to your databases using legitimate credentials. 

Contrary to popular belief, protecting your data from social engineering attacks also requires more than training. While employee training is a common step used to counter all types of social engineering scams, the human component often remains the weakest link in your security system. To this point, a 2022 study of different types of social engineering attacks concluded that “providing awareness against SE-based cyberattacks is not sufficient.” 

Zero Trust Data Security

The true key to solving all types of social engineering attacks is rethinking our entire approach to cybersecurity. Traditionally, the focus of digital privacy systems has been to keep outsiders from accessing the private networks and stores where data is hosted. While there will always be a place for maintaining this security perimeter, relying on this alone leaves all data within vulnerable to anyone who has already gained access to the servers or data files. 

This is where a Zero Trust framework for self-protecting data can be of the most use. Rather than simply trying to improve on perimeter measures, self-protecting data reimagines the entire approach to security. 

As the name implies, the goal of self-protecting data is not just to keep hackers out of your system but to create truly secure files. Instead of being left accessible to any “trusted” users, self-protecting files themselves are coded with the ability to recognize malicious activity and counter it immediately, regardless of who appears to be performing the action. 

Empower Your Data with Sertainty

Sertainty leverages proprietary and patent processes through its Data Privacy Platform and core technology that enable data to govern, track, and defend itself — whether in flight, in a developer’s sandbox, or in storage. These technology protocols mean that even if systems are compromised by AI tools or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. With the proliferation of human and AI threats, security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be.

How Hackers Use Key Tracking to Access Your Private Data

Posted on by Nicole Tidwell

In today’s digital world, data security is of paramount importance. More than ever before, companies must stay vigilant against constantly evolving cyber threats that can compromise sensitive information. Compared to AI-based threats that have only emerged in recent years, tactics like key tracking continue to fester without much success in curbing them. Recent attacks, including last year’s TikTok inquest, demonstrate that these threats are far from obsolete.

While key tracking attacks have seen a decrease in the media over the past decade, the threat is still very real. Contemporary data show that companies are still very much vulnerable to keystroke logging whilst facing newer, more direct attacks. Today, we’ll delve into the world of key log tracking, its potential dangers, and how to ensure that data remains secure, irrespective.

What Is Key Tracking?

Key tracking is a sophisticated technique used by hackers to gain unauthorized access to a computer or system by monitoring and recording keystrokes. Every time a person types on a keyboard, whether it’s entering passwords, sensitive data, or even simple messages, key tracking software records each keystroke and sends it to a server or device – as would a spyware virus, giving cybercriminals access to valuable information.

This technique is commonly associated with keyloggers, which can be hardware or software-based. Hardware keyloggers are physical devices connected between a keyboard and a computer, while software keyloggers are malicious programs that hide within the operating system, evading detection.

Many businesses invest in firewalls, antivirus software, and other security measures, believing their systems are impenetrable. However, employee credentials can be an easy entry point for cybercriminals. Similar to social engineering attacks, key tracking can bypass these defenses – entirely, leaving corporate files exposed to potential data breaches as if the threat came from the inside.

Types of Key Tracking Attacks

Keyloggers make up a significant cybersecurity concern that can be extracted in various forms, client connections, and shared logs. Some keyloggers use hypervisors to remain hidden under the operating system, while others operate at the kernel level, making them difficult to detect. Others can be integrated into hardware components or computer peripherals, acting as keyboard device drivers, accessing and recording all keyboard inputs before they reach the operating system.

Software-Based Keystroke Logging

All keylogging software has two primary components: a Dynamic Link Library (DLL) file and an executable file. The executable file installs and initiates the DDL, which can then begin tracking and recording keystrokes. The specifics, however, can vary significantly. 

API-based keyloggers are particularly tricky to detect since they hook into keyboard APIs – as if they were legitimate applications – and register keystrokes in a covert manner. Form grabbing-based keyloggers – malware that works by retrieving authorization and log-in credentials – target web form submissions whilst recording sensitive data before its transmission over the Internet.

JavaScript-based keyloggers infiltrate web pages through malicious script tags, waiting for key events to record. Memory-injection-based keyloggers, like the notorious Zeus and SpyEye trojans, manipulate memory tables to bypass security mechanisms and gain access to confidential information.

To establish remote communication, keyloggers upload data to websites, databases, or FTP servers. Some opt for periodic emails to predefined addresses, while others use wireless transmission through hardware systems. As obfuscation goes, some keyloggers enable remote logins, allowing unauthorized access to locally stored data on the target machine.

Hardware-Based Keystroke Logging

Hardware-based key tracking is a fundamentally different threat vector, but similar in its outcome. While firmware-based keyloggers can modify BIOS-level firmware to intercept keyboard events while remaining hidden, hardware keyloggers use physical circuits attached between the keyboard and computer or USB connectors to record keystrokes without the need for software installation, making them difficult to detect.

Threats from hardware-based key tracking are especially relevant today when working from home or with a demand for Bring-Your-Own-Device. What this means is that company computers are not necessarily safely locked in an office at all times, even when all corporate policies and rules must be adhered to in that place. 

Moreover, wireless keyboard and mouse sniffers passively collect wireless data packets, requiring decryption for access. This is inducing criminals to employ keyboard overlays on ATMs to capture PINs, appearing as integrated while deceptive to bank customers.

In addition, acoustic keyloggers use sound monitoring to identify keystrokes based on acoustic signatures, requiring a large sampling for accurate mapping. Electromagnetic emissions can also be captured from wired keyboards at a distance, and optical surveillance can be used to observe passwords and PINs via strategically placed cameras. 

Furthermore, physical evidence can be exploited when the keypad’s security code is known, reducing the possibility of a brute-force attack. Smartphone sensors, such as accelerometers, have been used to capture nearby keyboard keystrokes with high accuracy. The most advanced keyloggers will analyze body movements to determine pressed keys and audible signals to identify keystrokes in near real-time. There are methods of key tracking which provide hackers with a way into certain systems. 

Addressing Key Tracking Threats

To combat the threat of key tracking and ensure robust data security, companies need advanced solutions like Sertainty’s self-protecting data technology. Rather than rely on a series of firewalls and trust that those with access are legitimately allowed to be there, Zero Trust security gives data the ability to protect itself. 

Unlike conventional perimeter security, Sertainty data privacy technology empowers data itself to become an active defender against threats. By embedding intelligence directly into data files, self-protecting data can recognize and thwart malicious activities, even in the presence of key-tracking malware. This means that even if a hacker gains access to sensitive information, they will be unable to access or modify sensitive data. 

Truly Secure Data with Sertainty

As the digital landscape evolves, companies need to stay one step ahead of hackers by embracing innovative and proactive data protection strategies. With the right tools and the commitment to data security, businesses can maintain the trust of their customers and protect what matters most — their invaluable data. 

Sertainty leverages proprietary processes through its UXP Technology that enable data to govern, track, and defend itself — whether in flight, in a developer’s sandbox, or in storage. These UXP Technology protocols mean that even if systems are compromised by AI tools or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. With the proliferation of human and AI threats, security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be.

Zero-Day Exploits: What They Are and How You Can Prepare

Posted on by Nicole Tidwell

Zero-day exploits are among the most elusive and dangerous cyber threats in today’s digital landscape. These sophisticated attacks target undisclosed vulnerabilities, leaving organizations defenseless and scrambling for solutions. In this article, we will explore the world of zero-day exploits and their profound impact on data security. 

What Are Zero-Day Exploits?

Zero-day exploits refer to cyberattacks that take advantage of undisclosed software vulnerabilities. The term “zero-day” indicates that organizations and their developers have no time to prepare for these attacks, as the vulnerabilities are exploited before any patch or fix is available to the flaws. These exploits pose significant challenges to cybersecurity, as they leave victims defenseless against unseen threats.

Zero-day attacks emerged around 2006, due to the collaboration between the United States NSA and Israel’s 8200 Unit which berthed a 500Kb computer worm called Stuxnet. This worm featured a design and architecture that were not domain-specific and could be utilized for attacking modern SCADA and PLC systems. This made Stuxnet capable of infecting Iranian nuclear centrifuges that were enriching weapons-grade Uranium as part of its Nuclear program.

It was the first time that a Zero-Day cyber attack was used for military purposes. This opened the floodgates for competition in the cyber arena through en-masse weaponization of zero-day attacks as part of the military doctrine of China, Russia, Iran, and North Korea. Or, as an integral part of the Forward Defense activities of the US, UK, and Israel, to keep the cybersecurity arena from escalating further. 

Thereafter, the potential of zero-day exploits—whether by malicious organizations, nation-states and their proxies, or individual hackers—began to seep into the psyche and operations of the DoD and IT world. The threat of zero-day attacks have underlined the need to mitigate any software security vulnerabilities as soon as they are discovered. 

How Zero-Day Exploits Work

Zero-day exploits follow a well-defined technical process that malicious actors use to infiltrate systems. Attackers tirelessly search for undisclosed vulnerabilities, knowing that these are the keys to high-impact attacks. Once found, they skillfully exploit these weaknesses, gaining unauthorized access to systems, stealing sensitive data, or disrupting critical operations.

Identifying Zero-Day Vulnerabilities

Researchers and hackers use various methods to identify zero-day vulnerabilities. Vulnerability research involves analyzing software code to uncover potential weaknesses. Bug bounty programs encourage ethical hackers to report zero-day vulnerabilities in exchange for rewards. The dark web also plays a role, serving as a marketplace where hackers buy, sell, or trade information about undisclosed vulnerabilities.

The Implications of Zero-Day Exploits

The consequences of zero-day exploits can be devastating. Real-life examples have shown how these attacks compromise the security and privacy of individuals, organizations, and even critical infrastructure. The financial impact can be significant, with remediation costs and potential legal liabilities. Furthermore, the reputational damage resulting from a successful zero-day exploit can tarnish an organization’s image for years to come.

Significant Historical Zero-Day Exploits

While Stuxnet is perhaps the most widely-publicized example of a zero-day exploit, other threats of this nature have only increased in the nearly two decades since it first made waves. In fact, a 2022 report found that a shocking 40% of all zero-day exploits that happened between 2012 and 2021 happened in 2021 alone. 

Let’s take a look at some significant zero-day exploits from the last decade to better understand how these types of threats can affect your business. 

Yahoo (August 2013)

Though it’s been eight years since the Yahoo attack, this zero-day incident remains one of the most prominent to date. In 2016, the company revealed that more than 3 billion accounts had been accessed by hackers in the attack. In addition to exposing user data, the incident caused Yahoo’s value to drop significantly in the midst of a potential acquisition. 

LinkedIn (June 2021)

Another notable incident occurred in 2021 when LinkedIn reported that it had been hit by a zero-day attack that affected over 90% of its user base (700 million users). In this attack, a hacker scraped data by exploiting the site’s API. Before being taken down by law enforcement, the group responsible for CVE-2021-1879 publicly released a data set of around 500 million users. 

Microsoft (July 2023)

In July of 2023, Microsoft confirmed a shocking 132 security vulnerabilities across its product lines, including six confirmed zero-day exploits. One of these zero-days was remote code execution found within Microsoft Office and Windows HTML that could allow hackers to create Microsoft Office documents enabling them to perform remote code execution in victims’ devices.

While patches for significant exploits like these are typically quickly released, as of July 21st, Microsoft has yet to release a patch for CVE-2023-36884. The company is instead offering mitigation steps for affected users. 

Defense Strategies Against Zero-Day Exploits

Mitigating the risks posed by zero-day exploits requires a proactive approach to cybersecurity. Vulnerability management and prompt patching are essential in reducing the attack surface and limiting the window of opportunity for attackers. However, traditional security measures may not always be enough. 

Leveraging Self-Protecting Data for Zero-Day Exploit Defense

Enter self-protecting data solutions, such as Sertainty’s cutting-edge technology. By embedding intelligence directly into data files, self-protecting data can recognize and counter malicious activities, even in the absence of known vulnerabilities or patches. While firewalls and secure networks are essential elements of any complete information security plan, truly guarding data against all attacks requires Self-Protecting Data. 

As a pioneer of this approach, Sertainty redefines how information is protected to ensure data privacy where perimeters fail. Using cutting-edge protocols and embedding intelligence directly into sensitive data files or datasets, Sertainty leverages patented processes to govern, track, and defend data through the data itself. 

Instead of database security being based on granted privileges to access the network directory where the file currently resides, Sertainty Self-Protecting Data (SPD) technology empowers the files themselves to protect themselves against malicious activity immediately. The Sertainty Data Privacy Platform technology recognizes itself through a Zero-Trust framework that contextualizes the environment, behavior, and action of the intended receiver — whether human, machine, or application. With these protocols, the data remains secure even in situations where systems have been compromised. 

Zero-day exploits represent a constant and formidable challenge to data security. As cyber threats evolve, organizations must stay ahead by adopting proactive defense strategies. Sertainty Self-Protecting Data technology offers a powerful shield against the unseen dangers of zero-day exploits. By embracing innovative solutions and staying vigilant, we can fortify our data defenses and navigate the ever-changing cybersecurity landscape with confidence. Protecting our data is not just a matter of staying one step ahead — it’s a commitment to safeguarding what matters most.

Truly Secure Data with Sertainty

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. Cyber threats may continue to advance, and security perimeter breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be. 

Can Cached Data Undermine Your Company’s Secure Data?

Posted on by Nicole Tidwell

Data Chain Custody Part 2: AI Data Security History, Flaws, and Emerging Solutions

Posted on by Nicole Tidwell

Recently, we discussed emerging open-source AI threat vectors, including the proliferation of potential open-source threats to private servers and data chains. Today, we’ll take a closer look at the history of AI data governance and discuss whether emerging trends in the marketplace can address them. 

When it comes to data security, AI presents a whole new field of dangers. But despite the high-tech nature of the data protection industry, even leading companies and government agencies are burying their heads in the sand and relying on existing security protocols to manage these threats. Regardless of whether or not your organization is on board with AI, these tools are here to stay. Reports have predicted that the AI market will experience a shocking Combined Annual Growth Rate (CAGR) of between 20.1% and 32.9%. As such, data privacy methodologies must pivot to take these AI tools into account.

AI Data Gathering and Security 2013–2023

While the underlying principles of artificial intelligence have existed for a long time, the widespread emergence of usable AI tech is less than a decade old. Depending on your definition, you may consider early algorithms introduced in the 1990s to be a precursor to current machine learning tools, but many experts generally regard 2013 as the origin of usable “deep learning,” as we now know it. 

The primary revolution at this stage was the use of five convolutional layers and three fully-connected linear layers and parallel graphics processing units (GPUs), as well as the introduction of a more efficient rectified linear unit for activation functions. 

The following year, in June 2014, the field of deep learning witnessed another serious advance with the introduction of generative adversarial networks (GANs), a type of neural network capable of generating new data samples similar to a training set. Essentially, two networks are trained simultaneously: (1) a generator network generates fake, or synthetic, samples, and (2) a discriminator network evaluates their authenticity.

2017 saw the introduction of transformer architecture that leverages the concept of self-attention to process sequential input data. This allowed for more efficient processing of long-range dependencies, which had previously been a challenge for traditional RNN architectures. 

Unlike traditional models, which would process words in a fixed order, transformers actually examine all the words at once. They assign something called attention scores to each word based on its relevance to other words in the sentence.

Generative Pretrained Transformer, or GPT-1, was introduced by OpenAI in June 2018. Since then, the program has gone through numerous evolutions. While OpenAI has not disclosed the specifics, it is assumed that the current iteration, GPT-4, has trillions of parameters. 

Emerging Trends in AI Data Security

On the other side of the same coin, some data security companies have already introduced tools utilizing the same AI protocols. These programs utilize the information-gathering and analytical capabilities of machine learning to identify potential threats and suggest courses of action to mitigate them. 

However, it’s important to note that — despite the use of new, powerful machine learning technology — the fundamental premise of this solution is based on a conventional understanding of data security. The system’s proactivity only extends as far as any traditional perimeter security and threat analysis (albeit in a more efficient manner). 

This inherent inadequacy means that even the most sophisticated form of conventionally-minded AI security can (theoretically) be exploited or circumvented by the same means as their predecessors.  

As such, truly addressing all potential threat vectors requires a complete rethink of how secure data governance is handled, rather than applying new technology to existing systems. 

AI-Informed Secure Data Governance 

Though many “leading” commercial tools rely on outdated security structures, a better solution is already available. Unlike traditional data privacy, Zero Trust security provides a proactive method for mitigating attacks. 

The key differentiator between Zero Trust and other, more traditional solutions is letting go of the (incorrect) assumption that sensitive databases can be secured simply by keeping malicious actors out. Rather than rely on a series of firewalls and trust that those with access are legitimately allowed to be there, Zero Trust security gives data the ability to protect itself. 

Following this methodology, Sertainty has redefined how information is protected to ensure data privacy even where firewalls fail. Using cutting-edge protocols and embedding intelligence directly into datasets, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised, data remains secure. 

With specific regard to emerging AI threats, the core Sertainty UXP Technology empowers data chain custodians to opt in or out of the use of Personal Identifying Information (PII) by AIs like ChatGPT. This ensures that organizations exposed to ChatGPT — as well as their employees and clients — maintain privacy, regulatory compliance, and protection in all scenarios. 

Sertainty UXP Technology also allows developers working with open-source AI programs like those from OpenAI to maintain their own privacy commitments by giving data files the ability to protect themselves and generating repositories of those who approve the processing or those who wish to opt out of data sharing.

Even regulators have taken notice of the shortcomings inherent in today’s cybersecurity paradigm and expressed interest in this new way of approaching data privacy. Prompted by both real and potential dangers, including AI threat vectors, an Executive Order titled “Improving The Nation’s Cybersecurity” has outlined the need for US federal agencies to move toward a zero-trust security model. 

Sertainty Data Privacy 

In the current landscape of trendy tech and buzzwords, concrete solutions are more vital than ever. Sertainty Zero Trust technology enables secure data governance and the training of AI models with a tried-and-true multi-layer security solution.

Sertainty leverages proprietary processes through its UXP Technology that enable data to govern, track, and defend itself — whether in flight, in a developer’s sandbox, or in storage. These UXP Technology protocols mean that even if systems are compromised by AI tools or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs.

Secure-by-Design Technology

Posted on by Nicole Tidwell

While the need for total digital security has only increased over the past decades, the technology we rely on every day is often far from as secure as consumers assume. While virtually all devices, networks, and users utilize some form of information security practices, the overwhelming majority of these are separate systems that aim to keep outsiders from accessing vulnerable networks and data stores rather than improvements to the intrinsic security of the technology. 

While this may seem sufficient for some cases, the reality is that most security solutions are woefully inadequate when it comes to addressing the inherent flaws and vulnerabilities of cybersecurity technology. 

This issue has not escaped the notice of major regulatory agencies either. Earlier this year, Jen Easterly, director of the US Cybersecurity and Infrastructure Security Agency (CISA), criticized tech companies for their failure to prioritize the safety and privacy of consumers. This indictment is particularly potent coming from Easterly, who heads the United States’ national effort to understand, manage, and reduce risk to digital and physical infrastructure. 

The Burden of Safety

In many critical industries, a combination of legislation and presumed ethical responsibility mandate designers and manufacturers to account for the safe, secure usage of all new products from the outset. The world of technology, however, lacks many of these safeguards. 

The reasons for this are manifold. For one, the tech industry, as we currently know it, is still relatively young. For example, it was more than 80 years from the time automobiles were introduced until the US federal government mandated that all new cars being sold must have built-in seatbelts. 

Another reason that new technology pertaining to the cybersecurity space often lacks the oversight present in other industries relates to the nature of the threats in question. While the potential for accidental user-caused data breaches certainly exists to some extent, the majority of modern data threats come from malicious actors. This is the current industry dynamics that make it easier for tech companies to pass off the burden of safety, making it the responsibility of customers to protect themselves from attackers. 

While it is still up for debate on whether or not tech companies should be held responsible for the safety of their products, CISA Director Easterly was clear in her Carnegie Mellon University talk on where her organization stands regarding where the burden of security lies. 

“We find ourselves blaming the user for unsafe technology. In place of building-in effective security from the start, technology manufacturers are using us, the users, as their crash test dummies — and we’re feeling the effects of those crashes every day with real-world consequences,” she said. “This situation is not sustainable. We need a new model.” 

Information Security Legislation

Despite the lack of regulation surrounding the creation and distribution of software and Data-Centric technologies, the information stored and transferred using these tools is often bound by strict legislation. For instance, in the United States, all information related to individual health is protected under the Health Insurance Portability and Accountability Act of 1996 (HIPAA). Compliance with HIPAA regulations is dictated by the US Department of Health and Human Services and enforced by the Office for Civil Rights. 

Moreover, it should also be noted that non-compliance with privacy laws such as HIPAA for health-related data, CCPA legislation in California, or the GDPR (pertaining to EU subjects) is prone to penalization. 

Secure-by-Design Technology

Critical security concerns surrounding data that relies on digital privacy measures highlight the need for a better data protection paradigm than most individuals and organizations currently use. This is where “secure-by-design” technology is urgently needed. 

In the current system, tech companies create and sell technology that leaves users to contend with suboptimal solutions to their own security needs. However, as the name suggests, secure-by-design technology is created with privacy and security and embedded into a data-file from its origination to its expiration. 

CISA Director Easterly noted the importance of this approach in her address, pointing out that “… ultimately, such a transition to secure-by-default and secure-by-design products will help both organizations and technology providers: it will mean less time fixing problems, more time focusing on innovation and growth, and importantly, it will make life much harder for our adversaries.”

For now, the vast majority of ubiquitous security solutions are simply bandages over the inherent flaws of digital networks. However, a better, more fundamental type of cybersecurity does exist. 

Self-Protecting Data and Zero-Trust Security

Whether or not new regulations will compel the technology industry to create fundamentally more secure systems in the future, sensitive data — currently stored in digital spaces — already faces more threats than ever before. 

To date, the concept of perimeter security has been the de facto standard for data security. With the advent of the internet, securing networks has become a greater priority, and reliance on tools such as IP address verification and multi-factor authentication has only increased. Although relatively mature, these methods still serve as the primary ways in which most companies attempt to ensure that private information stays private. 

While perimeter security continues to serve an important purpose in protecting secure files, this form of traditional data protection is fundamentally flawed. When an organization’s defense relies purely on perimeter security, identifying and addressing vulnerabilities becomes a game of whack-a-mole between hackers and network administrators. 

Both conceptually and in practice, Zero-Trust security is a revolution. Rather than rely on a series of firewalls and trust that those with access are legitimately allowed to be there, Zero-Trust security protects data by demanding continuous authentication from users. Meanwhile, self-protecting data protocols — unlike perimeter security — are designed to give data files the ability to protect themselves from creation. 

Sertainty

As a leader in self-protecting data, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. Open-source security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be. 

Protecting Critical Infrastructure from Cyberattacks

Posted on by Nicole Tidwell

The last few years have seen a rise in the sophistication and frequency of attacks targeting many vital industries. In addition to the rise of international tensions bringing to light new threats aimed at critical infrastructure, advancing technologies have opened new doors for attackers. The increasing capabilities of artificial intelligence-enabled threats have been a popular topic of discussion, but many other vectors of attack pose equally dangerous threats to public safety. 

Another major driver of new cyber threats came with the discovery of a modular malware toolkit capable of targeting tens of thousands of industrial control systems (ICS) across different industry verticals. These attacks pose a serious threat to critical infrastructure, such as power grids, water treatment facilities, and manufacturing plants, many of which rely on ICS to operate. 

Some of the most potentially devastating and escalating new cybersecurity dangers have been aimed at critical infrastructure systems and public works worldwide. For example, in April 2023, Iranian state-linked hackers targeted critical infrastructure in the US and other countries in a series of novel dropper malware attacks. While not as devastating as other incidents, the previously-unheard of nature of the malware made this attack particularly concerning. 

Other attacks on other areas of critical infrastructure in recent years have raised similar fears. In late 2022, the Danish State Railways’ network was temporarily shut down by hackers. Other breaches affecting essential industries continue to be reported frequently, with a ransomware attack affecting manufacturing, communications, public and private healthcare, and education being reported by the Cybersecurity & Infrastructure Security Agency (CISA) as recently as March 2023. 

Attacks targeting public infrastructure that have the potential to take out essential systems — such as hospitals, water facilities, electricity, and energy production — are even sometimes referred to as “killware” for their ability to cause disruption leading to real-life deaths. 

ICS and Critical Infrastructure

One reason for the increase in these attacks is the growing interconnectedness of ICS with other systems and networks. While this allows systems to benefit from the “network effect” and introduce new functionality, it also introduces new potential entry points for hackers to exploit. 

Similarly, the rise of the Industrial Internet of Things (IIoT) has led to an increase in the number of devices and sensors connected to ICS, making it more difficult to secure the systems. 

Industrial control systems are designed to control and monitor a wide range of physical devices and processes. This can include things like valves, motors, and sensors to ensure that they operate efficiently and safely. 

Programmable logic controllers, distributed control systems, and supervisory control and data acquisition systems are all also enabled by the use of ICS. These devices and systems can be distributed across multiple locations and may be connected to other networks, such as corporate networks or the Internet. 

Because of their integral role in managing physical processes, securing ICS and IIoT environments is essential to ensure the safe and efficient operation of critical industrial systems. But securing these environments can be challenging due to their inherent complexity, as well as the widespread use of outdated legacy systems and proprietary protocols. As a result, specialized security tools and techniques are required to protect ICS in IIoT environments from cyberattacks and other security threats. 

Cyber Threats to Critical Infrastructure

While the number of potential attack vectors is virtually endless in today’s complex, interconnected systems, there are a number of particularly concerning threats to critical infrastructure that have emerged. 

Advanced persistent threats (APTs) are a type of cyberattack specifically designed to target and compromise IIoT environments. APTs are typically carried out by highly skilled and organized threat actors using sophisticated and stealthy techniques to gain unauthorized access to vital systems and remain undetected for extended periods of time. 

APTs targeting ICS in IIoT environments typically involve multiple stages. Hackers begin by conducting extensive reconnaissance to identify vulnerabilities and weaknesses in the target environment. They may use various techniques — such as social engineering, spear-phishing, and network scanning — to gather information about the target organization. 

Attackers are adept at identifying openings, and unpatched software vulnerabilities, stolen credentials, and compromised third-party suppliers are all potential open doors. Once inside, attackers are free to unleash zero-day exploits, custom-designed malware, or other malicious programs to gain control of the connected systems. 

Addressing APT and Other Cyberattacks

APTs and other common forms of attack can exploit a wide variety of openings to access a system, including using legitimate credentials. As such, they are particularly devastating when turned on systems that rely on conventional perimeter security. Once they get past the firewall or other perimeter security measures, they essentially have free rein to steal data or cripple internal systems.

This does not mean that vulnerable critical infrastructure cannot be protected, however. Self-protecting data can be an effective defense against APT attacks targeting IIoT environments by providing an additional layer of protection that directly addresses the greatest weaknesses in traditional network security. 

Self-protecting data works by using encryption, access controls, and other security measures to protect data throughout its lifecycle, from creation to disposal. In a Zero-Trust system, files themselves are coded with the ability to recognize malicious activity and counter it immediately, regardless of who performed the action. 

This means that even if an attacker gains access to the data, they will be unable to read or modify it without the appropriate decryption keys or credentials. Likewise, approved users are blocked from accessing or performing harmful actions, whether on purpose or by accident. 

Zero-Trust Security in Infrastructure IIoT Applications 

In an IIoT environment, self-protecting data can be used to protect sensitive information, such as configuration data, operational data, and customer data. For example, self-protecting data can be used to encrypt configuration files for ICS devices, making it more difficult for an attacker to modify the settings of these devices. Similarly, self-protecting data can be used to encrypt customer data, such as personally identifiable information (PII) or financial information, making it more difficult for an attacker to steal.

Additionally, self-protecting data can help organizations detect and respond to APT attacks by providing visibility into how data is being accessed and used within critical ICS. By monitoring access logs and other data-related activities, security teams can detect suspicious behavior and take appropriate action to mitigate the threat. 

Sertainty

Sertainty’s foray into the Transient World is manifested in multiple Bi-National Research and Development (BIRD) Proposals\Submissions. These innovative solutions have the potential to aid government agencies such as Homeland Security as well as companies in the transportation and energy industries. 

As a leader in self-protecting data, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. Security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be. 

What Is the CISA Zero Trust Maturity Model?

Posted on by Nicole Tidwell

In recent months, the federal government has renewed its focus on digital security. The Cybersecurity and Infrastructure Security Agency (CISA) has been applying pressure on both the private and public sectors to increase commitment to digital security and Secure-by-Design Technology. 

While there is an eminent need for improved security protocols across the board, the technology to fill these needs in both government and civilian applications has already been successfully introduced in many industries. Rather than reinventing the wheel, the CISA Zero-Trust Maturity Model prompts federal agencies to introduce these tools to mitigate the weaknesses noted. 

The Need for Increased Cybersecurity

The world of cybersecurity is evolving rapidly. Yet, despite the constant emergence of new threat vectors, data protection in many critical areas is fundamentally lacking. From major social media platforms to federal agencies, conventional perimeter security remains the de rigueur.

While perimeter security will always be an essential element of a comprehensive data security plan, even the most sophisticated perimeter systems are vulnerable to attackers that have found ways to breach the layers of exterior security. Likewise, insider threats often go unmitigated by perimeter-based security measures, as malicious actors may already have legitimate access credentials.

These weaknesses mean that securing data behind firewalls and “secure” servers is essentially an arms race between network administrators and people attempting to break in. This is particularly problematic when the systems in use have been around for an extended period of time, such as in the relatively outdated systems that many government agencies continue to use. 

In recent months, these threat vectors have been highlighted by increasing AI-enabled threats. Even mainstream artificial intelligence programs can be used to exploit weaknesses in security perimeters. For example, hackers have already begun using programs such as ChatGPT to generate more effective social engineering attacks, exacerbating the extant threat to validated user credentials. 

Addressing Weaknesses in Conventional Data Security

In spite of the vital nature of private data in government hands, many federal agencies continue to rely on outdated legacy systems to collect, store, and access their information. The implicit trust built into these systems is based on perimeter security protocols, where access and authorization are infrequently assessed based on fixed attributes. 

To address the above (and other) weaknesses, a full rethink of how to secure data is required. Fortunately for the vulnerabilities plaguing many critical sectors, an entirely new generation of cybersecurity does exist: Self-Protecting-Data. 

As a pioneer of this approach, Sertainty redefines how information is protected to ensure data privacy where perimeters fail. Using cutting-edge protocols and embedding intelligence directly into a Data-File or Datasets, Sertainty leverages patented processes to govern, track, and defend data by the data itself. 

Instead of the file’s security being based on granted privileges to access the network directory where the file currently resides, Sertainry Self-Protecting Data files protect themselves against malicious activity immediately.  With these protocols, the data remains secure even when systems are compromised. 

Prompted by the now-exposed cybersecurity realities, regulators recognized the shortcomings inherent to the state-of-the-art cybersecurity protocols. A 2021 Executive Order titled “Improving The Nation’s Cybersecurity” outlined the need for US federal agencies to move on to something better – a Zero-Trust Architecture.

Executive Order 14028 and the CISA Zero Trust Maturity Model

In April 2023, CISA published what is known as the Zero Trust Maturity Model (ZTMM). This security model is designed to overcome many of the inherent assumptions built into modern networks, contributing to their cybersecurity weaknesses. 

This new focus is not simply a function of natural evolution but an answer to federal demands for better security. Executive Order 14028, “Improving the Nation’s Cybersecurity,” requires all federal agencies to develop a plan to implement a Zero-Trust Architecture to address real shortcomings in current sensitive data storage. 

Already, some agencies have been proactive in introducing a Zero Trust concept. In 2021, Representative Dr. Mark Green (R-TN) of the House Committee on Armed Services successfully incorporated the Sertainty language regarding data security into the Department of Defense 2020 DoD Strategy. Rather than calling for generic security measures, the language of the DoD Strategy favors the functionality that Sertainty technology can offer. 

Private Sector Application of the Zero Trust Maturity Model 

Regarding growing threats to data security, the private sector has not escaped direct scrutiny, either. This year, CISA director Jen Easterly criticized tech companies for their failure to prioritize the safety and privacy of consumers. While Director Easterly’s criticism was aimed primarily at technology companies, organizations in all industries are in need of enhanced data security. 

While the CISA ZTMM model was specifically developed for federal agencies, many in the private sector took notice. The model provides an approach for any organization to achieve continued modernization efforts related to zero trust — which is crucial in a rapidly evolving technology landscape.

This need for Secure-By-Design technology goes hand-in-hand with the ability to create files with self-protecting abilities. Tools such as the Sertainty Data Privacy Platform allow developers to utilize cutting-edge methods and protocols in their applications from the outset, as well as apply them to existing systems. 

Sertainty Data Privacy

As a leader in self-protecting data, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. Cyber threats may continue to advance, and security perimeter breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be.

Could Zero Trust Security Have Prevented the Recent Pentagon Breach?

Posted on by Joseph Studios

While data security breaches are a common occurrence, some attract more attention than others. Earlier this year, the US Special Operations Command (USSOCOM) confirmed that hundreds of sensitive Department of Defense documents were leaked over a period of two weeks. 

The Senate defense appropriations subcommittee demanded answers for how a single individual could have taken and distributed classified information without being detected, in which top security experts were quick to note that insider attacks such as this one are prevalent. 

Insider attacks have been a primary motive behind many ongoing efforts to increase federal data security, including a shift to Zero Trust methods. In fact, the US Navy Chief Technology Officer Dan Yeske said in a recent interview that, had the Pentagon already adopted a Zero Trust data security model, the military would have recognized and responded to breaches like this one sooner. 

The Current State of Federal Data Security

When considering security for sensitive data, the common perception may be that confidential military or government data is fundamentally more protected than information stored by private companies. However, the reality is that many of the same threats apply to both. 

This is why the Zero Trust paradigm has been gaining attention and traction across industries, including the governmental sector. As it stands, the Pentagon already has a plan in place to introduce a Zero Trust security model into effect, by 2027. 

This plan by the US government aims to shore up other cybersecurity efforts for all federal agencies. In April 2023, the Cybersecurity and Infrastructure Security Agency (CISA) published what is known as the Zero Trust Maturity Model (ZTMM) in response to an Executive Order (14028) calling for “Improving the Nation’s Cybersecurity.” Order 14028 requires all federal agencies to develop a plan to implement a Zero Trust architecture to address the shortcomings in the current data protection constructs. 

It should be noted, that the Zero Trust Framework has already been successfully introduced in many industries. Rather than reinventing the wheel, the US Government has mandated Federal Agencies to adopt the CISA Zero-Trust Maturity Model into existing tools to mitigate network weaknesses.

While the CISA ZTMM model was specifically developed for federal agencies, many in the private sector have also taken notice. The model provides an approach for any organization to achieve continued modernization efforts related to Zero Trust — which is a criticality within a rapidly evolving technology landscape.

The Role of Zero Trust in Securing Pentagon Data

The US Navy CTO  – Yeske –  has been stating very poignantly time and again that Zero Trust security could have empowered a faster and more effective response to breaches and Pentagon data leaks. While this highlights some of Zero-Trust’s key benefits thereof, there is a game-changing potential in utilizing Self-Protecting-Data that go beyond simple protection.  

It is also important to note that in addition to the benefits mentioned by CTO Yeske, the true value of Self-Protecting-Data files is in preventing a rogue agent from accessing or sharing the files, to begin with. To fully realize the benefits of Self-Protecting- Data, agencies need to set their sights even higher than the military’s current plans.

While it is certainly true that a Zero Trust system would have allowed the Pentagon to recognize the breach far sooner than the six months that it took, properly implemented Zero Trust protocols could have stopped a rogue actor instantly when attempting to access unauthorized files.

This is true in the vast majority of information leaks, Zero Trust could have prevented many breaches in both the public and private sectors. As it stands, insider threats persist as the most ubiquitous threats to private data in all sectors. According to a 2022 report, insider threat incidents have been on an incline, and rose by 44% over the two previous years, with the cost per incident rising by an average of more than 30% year-over-year. 

The perception that the primary benefit of adopting a Zero-Trust posture entails identifying and responding to leaks is rooted in a conventional understanding of information security. Traditional digital security is fundamentally reactive. This means that, in many cases, Zero Trust is used as an enhanced form of traditional data privacy systems, and remains dependent on networks and demarcations. While this is an improvement, effectuating the implementation of Self-Protecting-Data will atone for existing vulnerabilities within a Security Perimeter in which the data transverses and is consumed. 

In all, perimeter security will always be an essential element of a comprehensive data security plan. Most sophisticated layered Perimeters are vulnerable to cyberattacks. Threats often go unmitigated, due to insiders with legitimate access credentials, as was the case in the most recent Pentagon breach. 

Zero Trust seeks to address weaknesses in ensuring data privacy. A Zero-Trust-Architecture at the Data-Layer untethers reliance on security Perimeters and Identity Access Management systems, to enable data files to protect themselves independently through an embedded trust-cycle. 

Truly Secure Data with Sertainty

Sertainty has redefined how information is protected to ensure data privacy even where firewalls fail. Using cutting-edge protocols and embedding intelligence directly into data files and datasets, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that the data remains secure even if systems are compromised. 

At Sertainty, we know that data is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing Self-Protecting Data solutions that evolve and grow to defend your crown jewels. Instead of focusing on your network’s inherent shortcomings, we enable you to safely and confidently embrace the potential of a new online-oriented world. Our self-protecting Zero Trust protocols mean that even if systems are compromised, data remains secure.

Addressing Primary Open-Source Security Challenges

Posted on by Nicole Tidwell

In the modern era of computing and data storage, the most critical element of any system is the software on which it runs. While hardware is still important, devices have developed to the point where the differences between compromised and secure networks, databases, and files come down to code, not physical security measures. 

One thing that has not changed since the earliest days of computing, however, is the rapid rate at which technology develops. Likewise, the importance of keeping up is a major factor for any business that hopes to stay relevant or secure. Due to this, as well as the high cost of proprietary software tools, open-source software (OSS) has come to dominate the world of coding. 

What Is Open-Source Software?

In the world of software development, the term “open-source” refers to any software with accessible source code that anyone can modify and share freely. Protocols, algorithms, and even fully-developed programs and games can be created with open-source coding. 

In most cases, open-source code is adapted and integrated into programs where it can be useful. Because source code is the part of the software that users don’t see or interact with, common open-source code is, at times, worked on by hundreds or even thousands of independent parties that can be used seamlessly without any outwardly-recognizable signs. 

In the early days of computing, there were very few dedicated professional programmers, and so the early internet was almost entirely made up of open-source code. The efforts of enthusiasts and professionals alike were aided by the network effect as the internet grew in popularity, allowing more people to contribute and refine the very protocols that were connecting them. 

Today,  many companies employ in-house software engineers; however, much of the code that we still use relies on the efforts of open-source developers. In fact, a 2019 report by Gartner found that 96% of codebases contain at least some open-source code. 

Advantages of Open-Source Software

There are many reasons why open-source coding is still so common. When compared to private development, open-source programs have many advantages. By giving programmers direct access to a program’s source code, the software can be continuously improved and expanded. This allows developers to add new features and fix bugs as they arise, rather than having to rely on the software’s original developer to address these concerns. 

The ability to grow and adapt quickly is essential to success in today’s increasingly fast-paced work environment. Organizations attempting to stay on top (or simply keep up with the market) have needs that evolve rapidly. Because of this, many companies look for solutions with the least amount of friction between development and implementation. 

Dangers of Open-Source Software

For all of the advantages that open-source software brings, there are a number of very significant risks stemming from the very aspects that make it so adaptable. And as prevalent as open-source coding is, a staggering number of organizations lack the structure to address these risks. A 2022 report by the Linux Foundation found that less than half of businesses had an open-source security policy in place for OSS development or usage. 

This lack of preparation can open the door to a wide variety of cyberattacks. Because anyone can access the source code of these programs, any flaws or vulnerabilities could quickly become public knowledge. Malicious actors can also freely examine the code that underlies any programs utilizing a piece of open-source software. 

The exploitation of these vulnerabilities can have wide-ranging negative impacts on all sorts of businesses. Everything from proprietary business data to private medical records can be compromised by attacks utilizing loopholes in open-source code. 

On a more sophisticated level, there are numerous ways in which open-source code can be compromised by hackers, causing anyone who then uses it to fall into their hands. For instance, if a code is compromised before it is used, any flaws built into it will remain there unless specifically eliminated. This may sound simple, but the reality is far more challenging. Unless security experts know precisely what to look for and where to look for it, detecting malicious lines of code can be virtually impossible. Even attempting to do so requires knowledge of whether the code has been compromised to begin with. In most cases, however, vulnerabilities do not become known until they have already been exploited. 

Types of Open-Source Security Risks

To better understand how the aforementioned attacks can occur, let’s examine some of the most common methods that hackers use to inject malicious code into open-source programs. 

Upstream Server Attacks 

In upstream server attacks, malicious entities infect a system “upstream” as it is uploaded onto a computer system or device. To accomplish this, malicious code is added to the software at its source, often through a malicious update, infecting all users “downstream” as they download it. 

Midstream Attacks 

Midstream attacks are fundamentally similar to upstream attacks, but instead of tampering with code at its initial source, they target intermediary elements. These include software development tools and updates that pass on the malicious code from there. 

CI/CD Infrastructure Attacks 

Another variation of the upstream attack model, CI/CD infrastructure attacks introduce malware into the development automation infrastructure of an open-source code requiring “continuous integration” or “continuous delivery” steps. 

Dependency Confusion Attacks 

Unlike the previous three types of attacks, Dependency Confusion Attacks exploit private, internally-created software dependencies by registering a new dependency with the same name in a public repository with a higher version number. The malicious code is then optimally placed to be pulled into software builds in place of the latest legitimate version of the software. 

Case Study: Log4Shell

Regardless of whether hackers compromise open-source code by one of the above methods or learn of a genuine loophole from an open hacking forum, once a door has been opened, any and all data within the compromised system is immediately vulnerable. Some measures can be taken to avoid some of these, but even the biggest companies have fallen prey. 

One of the most dangerous and well-publicized instances of open-source software falling vulnerable to attack came in 2021 when a code-execution vulnerability exploit for Log4j was released. At the time, Log4j was a virtually ubiquitous open-source utility used in countless popular applications, including Microsoft, Amazon, and Twitter servers. 

Referred to as “Log4Shell,” the vulnerability was first reported in November of that year after being identified in the popular game Minecraft. The code exploit was also published in a tweet a few weeks later, leading to numerous forums warning users that hackers could execute malicious code on servers or clients running the Java version of Minecraft. 

Millions of servers were left vulnerable by the exploit. The Apache Software Foundation assigned Log4Shell the highest-possible severity rating in the Common Vulnerability Scoring System (CVSS), and the director of the US Cybersecurity and Infrastructure Security Agency (CISA) called the exploit a “critical” threat. Using Log4Shell, attackers were able to install blockchain crypto, steal system credentials, and access sensitive data before a patch was released. 

Truly Secure Data with Sertainty 

The simultaneously derivative and interconnected nature of the modern internet makes avoiding open-source code a practical impossibility. For this and other reasons, traditional perimeter security falls notably short when it comes to keeping malicious actors out of your system. 

Because of this omnipresent threat, Sertainty leverages proprietary processes through its UXP Technology that enable data to govern, track, and defend itself – whether in flight, in a developer’s sandbox, or in storage. These UXP Technology protocols mean that even if systems are compromised or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that data is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and future-proof approach to cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. Open-source security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be. 

AI Optimization and Anonymization

Posted on by Nicole Tidwell

Today, artificial intelligence is no longer the far-off dream it once was. Tools like Midjourney, ChatGPT, and others have taken off in the last year, bringing with them a barrage of questions.  Many cybersecurity experts, and those entrusted with handling sensitive information, have pegged data privacy as the likeliest potential threat that these programs pose to organizations. 

The capabilities of AI are surmounting daily. Cybersecurity risks are mounting in step. From the first moment an AI Engine is optimized, it starts processing datasets. Partly because of this, effective data anonymization has become critical due to various compliance regimes and consumer protection laws. Companies hoping to utilize the power of artificial intelligence must factor in which datasets, audiences, and business problems it seeks to ascertain their predictions. 

What Is AI Optimization? 

Before testing an AI program, it must be optimized for its intended application. While, by definition, these programs are always learning, the initial training and optimization stage – which is defined by Volume, Variety, and Variance, is an essential step in the AI development process. 

There are two modes of AI training: supervised and unsupervised. The main difference is that the former uses labeled data to help predict outcomes, while the latter does not. 

The amount of data available to AI dictates whether developers can extract inputs to generate a significant and nuanced prediction in a controlled environment. Depending on data accuracy, developers will intervene and recast an existing outcome into a general output and reiterate the unsupervised processing w for better quality control and outcome. 

Supervised Learning

In this context, labeled data refers to data points that have been given pre-assigned values or parameters by a human. These human-created points are then used as references by the algorithm to refine and validate its conclusions. Datasets are designed to train or “supervise” algorithms to classify data or predict outcomes accurately. 

Unsupervised Learning

While no machine learning can accurately occur without any human oversight, unsupervised learning uses machine learning algorithms to analyze and cluster unlabeled data sets. These algorithms discover hidden patterns in data without the need for human intervention, making them “unsupervised.” 

While more independent than supervised learning, unsupervised learning still requires some human intervention. This comes in the form of validating output variables and interpreting factors that the machine would not be able to recognize. 

Data Anonymization in Machine Learning

The majority of machine learning advances of the past three decades have been made by continuously refining programs and algorithms by providing them with huge volumes of data to train on. ChatGPT, one of the most popular AI platforms today, is an open-source chatbot that learns by trolling through massive amounts of information from the internet. 

For all of their impressive capabilities, however, AI programs like ChatGPT collect data indiscriminately. While this means that the programs can learn very quickly and provide comprehensively detailed information, they do not fundamentally regard personal or private information as off-limits. For example, family connections, vital information, location, and other personal data points are all perceived by AIs as potential sources of valuable information. 

These concerns are not exclusive to ChatGPT or any other specific program. The ingestion of large volumes of data by AI engines magnifies the need to protect sensitive data. 

Likewise, in supervised machine learning environments, anonymization for any labeled data points containing personal identifiable information (PII) is key. Aside from general concerns, many AI platforms are bound by privacy laws such as HIPAA for health-related data, CCPA legislation in California, or the GDPR for any data in the EU. 

Failing to protect the anonymity of data impacted by these laws can result in steep legal and financial penalties, making it crucial that anonymization is properly implemented in the realm of AI and Machine Learning. 

Pseudonymization vs. Anonymization

When discussing data privacy, the word anonymization is almost always used, but in reality, there are two ways of separating validated data points from any associated PII. In many cases, rather than completely anonymizing all data files individually, PII is replaced with non-identifiable tags (in essence, pseudonyms). 

Perhaps the most famous large-scale example of this is blockchain technology. While personal data such as real names or other PII are not used, in order for the record-keeping chain to function, all data for each user must be linked under the same pseudonym. While some people consider this to be sufficiently anonymous for their purposes, it’s not as secure as true anonymization. If a pseudonym is compromised for any reason, all associated data is essentially free for the taking. 

True anonymization, on the other hand, disassociates all identifying information from files, meaning that the individual points cannot be linked to each other, let alone to a particular person or parent file. 

Because of this, many security experts prefer to avoid the half-measure of pseudonymization whenever possible. Even if pseudonymous users are not exposed by error or doxxing, pseudonymized data is still vulnerable in ways that fully anonymized data is not. 

Already, some AIs are becoming so sophisticated that they may be able to deduce identities from the patterns within pseudonymized datasets, suggesting that this practice is not a secure replacement for thorough anonymization. The more data algorithms are trained on, the better they get at detecting patterns and identifying digital “fingerprints.” 

Other AI-Driven Anonymization Scenarios

In the current landscape of ever-more-capable machine learning, the value of proper data anonymization is greater than ever. Aside from the vulnerabilities within AI-driven frameworks, external threats driven by digital intelligence present new challenges, as well. 

For one thing, artificial intelligence is able to exploit technical loopholes more effectively than human hackers. But beyond that, AI is also increasing threats targeted at social engineering. Recently, users found that ChatGPT was able to generate phishing emails that were notably more convincing than many human-generated attempts. This will undoubtedly lead to increasingly sophisticated attempts to access private data. As such, new tactics must be employed to properly secure and anonymize data before it becomes exposed to artificial intelligence.

Anonymized Smart Data with Sertainty

Sertainty’s core UXP Technology enables Data as a Self-Protecting Endpoint that ensures the wishes of its owner are enforced. Sertainty’s core UXP Technology will also enable developers working within AI environments such as ChatGPT to maintain ethical and legal privacy with self-protecting data. Rather than attempting to hide PII and other sensitive data behind firewalls, Sertainty Self-Protecting Data files are empowered to recognize and thwart attacks, even from the inside. 

As a leader in self-protecting data, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself in today’s digital world. These protocols mean that if systems are externally compromised or even accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. With the proliferation of human and AI threats, security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be.

How Self-Protecting Data Creates Truly Secure Files

Posted on by Nicole Tidwell

Technology has taken leaps and bounds forward in the last few decades. This growth has expanded our capabilities and access to computing power. As data applications have become more widespread and versatile, our reliance on secure files has also increased. 

Cybercrime has been quick to interject itself with the exponential growth of unstructured data files. Network computing today, whilst truly innovative, is replete with major attacks aimed at shutting it down. The motivation behind these breaches has ranged from simple thievery and greed to catastrophic acts of global cyberterrorism. Moreover, the Dark Web continues to be populated with tools and malware that make this onslaught continuous and dire. 

As much as both private companies and government agencies work to secure files and networks, hackers are never far behind. Often, the tools that make sensitive networks so accessible and valuable are also their Achilles heels. 

The Limits of Traditional Security

The vast majority of the most complex security systems operate on the same basic principle: to keep malicious actors or programs out of your secure files. Marketing claims notwithstanding, most of these systems approach cyber security issues with a similar method, almost invariably using some form of perimeter security. 

To date, the concept of perimeter security has been the de facto standard for data security, even predating the firewall. Even the earliest computers that operated on closed networks kept themselves secure by restricting who could use the computer terminal. This then advanced to dedicated user accounts and passwords. With the advent of the internet, securing networks became an even greater priority. Reliance on tools such as an IP address and verification and multi-factor authentication serve as the primary ways to ensure that private information stays private. 

While perimeter security continues to serve an important purpose in protecting secure files, this form of traditional data protection is fundamentally flawed. When an organization’s defense relies purely on perimeter security, identifying and addressing vulnerabilities becomes a game of whack-a-mole between hackers and network administrators. 

Irrespective of how good your administrators are, ways into a system will always exist. Once a private system’s perimeter has been breached, users can do as they please. This means that not only are compromised credentials a threat, but conventional perimeter security systems are exceedingly vulnerable to inside attacks. 

How Does Self-Protecting Data Work?

Rather than simply trying to improve on inherently flawed concepts, self-protecting data is the result of rethinking our security fabric. As the name implies, the goal of self-protecting data is not simply to keep hackers out of your system but to create truly secure files. 

While the mechanisms of self-protecting data are extremely intricate, the fundamental concept is fairly straightforward. Instead of being left accessible to “approved” users, the files themselves are coded with the ability to recognize malicious activity and counter it immediately, regardless of who performed the action. 

Operating on a Zero-Trust basis connotes that basic perimeter security like password-protected logins becomes a first layer of defense rather than the sole source of protection for your files. Enhancing your defenses with the Sertainty Self-Protecting-Data (SPD) not only stops an outside actor who has infiltrated the system from wreaking havoc, but it also prevents insiders from creating chaos. 

Types of Threats to Secure Files

To better understand how SPD creates truly secure files, we must consider what attackers are attempting to accomplish. Let’s take a look at some types of attacks and see how SPD identifies and negates \ mitigates them. 

Ransomware

In ransomware attacks, hackers will create a program that has the ability to block access to secure files or a system, usually threatening to delete data if an organization does not comply with a specific set of demands. In a conventional security system, a user or program that has gained the ability to execute code within your network has the power to deploy malware in a system to exact ransomware. 

SPD files, however, are given the ability to recognize when a malicious program is attempting to gain control over it and block access to it whilst alerting system admins by themselves. Not only does this prevent the ransomware from harming secured files, but it can also provide valuable metadata about the attempt, giving insights needed to strengthen an organization’s security system further and factor continuity of operations to maintain resiliency. 

Social Engineering

Unlike “direct attacks,” where malicious programs are created to exploit a specific weakness in a security system, social engineering attacks attempt to trick employees or other legitimate users into compromising their credentials. These can come in the form of phishing emails or phone calls, malicious links, key tracking software, and other forms of trickery. 

Once they have captured the appropriate login credentials, hackers are free to do as they please within your system until you catch them and lock them out again. Because Sertainty SPD embeds a Zero-Trust framework within files, malicious actions are blocked and reported, even if they’re taken by a party with valid credentials but out of context and geographical location.  

Insider Attacks

Because insider attacks come from parties who already have legitimate access to a system, any form of perimeter security is, by definition, useless. But with the Sertainty SPD, even fully legitimate and “trusted” members of your organization are defended against by the files themselves. This not only prevents rogue parties from stealing or destroying valuable data, but it also protects against accidental actions that can harm your secure files. 

Truly Secure Data with Sertainty

As a leader in self-protecting data, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. Open-source security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be.