Cyber Threat Actors: Exploring Deepfakes, AI, and Synthetic Data

How well are you protected against cyber threat actors? You may think that threat actors aren't looking to target you or your organization. But anyone can fall victim to social engineering, a form of deception used to obtain personal information. This remains a prevalent tactic bad actors use to compromise data security and commit fraud.

And what if these attacks go deeper and become even more sophisticated? According to a 2023 Global Risk Report by the World Economic Forum, cybersecurity is now a top 10 global risk. And with the estimated cost of cybercrime predicted to reach a staggering 13.82 trillion USD by 2028, it's time for individuals and businesses alike to take action against a new breed of threat actors.

The rise of deepfakes, artificial intelligence (AI), and synthetic data has opened new possibilities for cybercriminals to exploit. While these technologies can potentially revolutionize industries and improve our daily lives, threat intelligence reveals that they can be misused for malicious purposes. This poses significant security, privacy, and trust risks.

Here, we will delve into the evolving landscape of digital threats posed by deepfakes, AI, and synthetic data. We'll explore different types of cyber threat actors and their motivations, discuss the dangers of deepfake technology, and examine the role of AI in both facilitating deepfake creation and detection. Finally, we'll address the implications for cybersecurity and privacy and provide strategies to mitigate these risks.

What is a Cyber Threat Actor?

While a threat actor can refer to anyone or anything that poses a risk to an organization's cybersecurity, in this context, we're focusing on individuals or groups who use technology and digital tools for malicious purposes. Cyber threat actors can be hackers, activists, nation-states, organized crime groups, or even disgruntled employees. What sets them apart is their intent to cause harm by exploiting vulnerabilities in digital systems.

The motivations of cyber threat actors can vary. They could range from financial gain to political motives or simply the thrill of causing damage. Some may also have a more nefarious goal, such as disrupting critical infrastructure or stealing sensitive information for espionage purposes.

Regardless of threat actor motives, organizations can use threat intelligence forecasts to anticipate and prepare for potential threats. By analyzing data from various sources, such as social media, the dark web, or public databases, businesses can gain valuable insights into emerging cyber threats and take proactive steps to mitigate them.

What Is an Example of a Cyber Threat Actor?

Cybercriminals are one example of a notable cyber threat actor. These individuals or groups use complex and sophisticated campaigns. And they are aided by the availability of cyber tools and services on dark web markets. They may work alone or collaborate with others from different criminal enterprises.

For example, the Cl0p ransomware group, believed to be linked to Russia, has been active since February 2019. It is mainly known for using ransomware and DDoS attacks against large organizations, explicitly targeting healthcare and technology companies.

In December 2022, a new variant of the Clop ransomware was observed by researchers from SentinelLabs. It targeted Linux servers, previously not known to be at risk for this type of attack. While the flawed encryption used in this variant allows victims to recover their files without paying a ransom, it highlights cybercriminals' evolving tactics and targets.

6 Types of Threat Actors

With about a decade of digital transformation, 41% of chief security officers, 29% of CEOs, and CISOs admit their security initiatives have not kept pace with the changing tech landscape. About 25% said that the advancement of technologies is their biggest security concern. This makes it more crucial than ever to understand and leverage comprehensive threat intelligence solutions to stay ahead of potential threats. Dark web threat intelligence, in particular, can help organizations identify, understand, and mitigate cyber threats from far corners of the internet.

Here are six types of threat actors that businesses and individuals need to be aware of:

1. Script Kiddies

Motivation: Wants to gain recognition or cause damage for personal satisfaction.

Skills: Limited technical skills, mainly using pre-written scripts and tools.

The term "script kiddie" was first used in the 1990s to describe individuals who would download and use tools without understanding how they worked. They often use existing tools and techniques to find vulnerabilities in internet-connected systems. And they are motivated by personal reasons such as seeking attention, causing chaos, or taking revenge.

Script kiddies may also purchase, trade, or use tools and malware developed by more advanced threat actors to carry out their attacks. While their actions may seem random and low-skill, they can still cause significant damage. Usually, they cause issues through Denial of Service (DoS), social engineering, or website defacement attacks.

While you might mistake script kiddies for hackers, the two have significant differences.

2. Hacktivists

Motivation: To promote social or political change through cyber attacks.

Skills: Varying levels of technical skills, often collaborating with others in their campaigns.

Hacktivism is a term used to describe the use of hacking and digital sabotage to support a specific cause, movement, or ideology. Hacktivists can act alone or as part of a larger organization or group. Their activities range from website defacements, data breaches, and DDoS attacks, typically targeting government organizations, corporations, or individuals they see as threats to their cause.

Hacktivists often justify their actions as a form of protest or civil disobedience against those in power. They may also collaborate with other threat actors, such as cybercriminals or nation-state actors, to achieve their objectives.

One notable example is the Lapsus$, which first gained attention in December 2021 when they hacked into the Brazilian Ministry of Health's systems and leaked sensitive COVID-19 vaccination data. The group is believed to have members from Portugal and Latin America. They had a highly communicative presence on Telegram and using multiple languages in their recruitment efforts. Their tactics include social engineering, credential theft, and bribery of employees or business partners of target organizations.

3. Nation-State Cyber Threat Actors

Motivation: Espionage, political manipulation, or economic gain.

Skills: Highly sophisticated and well-resourced, able to create custom tools and techniques.

Nation-state actors are cyber threat actors that operate on behalf of a particular country's government or intelligence agency. They often have significant resources and are highly skilled in developing advanced tools and techniques for their attacks.

Nation-state actors typically target critical infrastructure and government organizations. However, they may also go after private companies for sensitive information or intellectual property theft. These actors may also have close ties with their respective governments' military and intelligence apparatus. And they can have a high level of technical expertise. They may also recruit individuals with specific language, cultural, or social media skills to engage in espionage and disinformation campaigns.

With no fear of legal retribution and resources at their disposal, these threat actors can be highly persistent and challenging to detect. They may use false flags to mislead attribution efforts by cybersecurity experts. Unlike other threat actors, nation-state actors rarely claim credit for their actions.

4. Terrorist Groups

Motivation: To spread fear and violence through cyber attacks.

Skills: Varying levels of technical skills, often collaborating with others in their campaigns.

Cyberterrorism and terrorist groups use the internet to spread propaganda, recruit members, plan attacks, and coordinate their operations. They can target critical infrastructure systems such as power grids, transportation networks, and healthcare systems. Here, they aim to disrupt government operations or cause harm to civilians. They may also engage in financial crimes, such as stealing money from banks or using ransomware attacks to fund their activities. Deepfake technology and AI can also help terrorists spread false information and manipulate public opinion for their benefit.

For example, Amazon, eBay, Yahoo, and other well-known companies were targets of DoS attacks in February 2000. On October 22, 2002, the Washington Post reported that "the heart of the Internet network sustained its largest and most sophisticated attack ever." A DoS attack struck thirteen "root servers" for internet communications worldwide. However, due to built-in safeguards, no slowdowns or outages occurred. But with more prolonged and more extensive attacks, they could have caused significant damage.

5. Insiders

Motivation: To cause harm from within an organization, financial gain through fraud, or revenge against the organization.

Skills: Varying technical skills, insider access to networks and systems, and knowledge of an organization's operations.

Insider threats are individuals within an organization who have or have access to sensitive information, systems, or physical assets and use that access to harm the organization intentionally or unintentionally. Some of the common types of insider threats include

Unintentional Threat:

• Negligence – These are types of insiders who expose an organization to a threat through carelessness. They may be familiar with security and/or IT policies but ignore them, creating risks for the organization. For example, Robinhood, a trading platform, experienced a data security incident in which an unauthorized party accessed a limited amount of personal information for some of their customers. This breach was caused by a customer support employee who was socially engineered by phone and obtained access to specific customer support systems.
• Accidental – These are individuals who cause an unintended risk to an organization. This can include filling out sensitive information on a website, sending an email with confidential data to the wrong recipient, or falling for a phishing scam.

Intentional Threats or Malicious Insiders: These individuals deliberately harm the organization or act on a personal grievance. This type of threat can be motivated by various factors, including financial gain, revenge, or ideology. Often, disgruntled employees may leak sensitive information to competitors or engage in cyberattacks to cause harm to the organization.

6. Cybercriminals

Motivation: Financial gain, extortion, theft of sensitive information, political reasons, or personal gratification

Skills: High level of technical expertise and ability to exploit vulnerabilities in systems and networks.

Cybercriminals are individuals, groups, or organizations that maliciously use technology and the internet. They often use techniques such as social engineering, malware, phishing, and ransomware to target individuals, organizations, or networks.

Cybercriminals have access to sophisticated tools and techniques that can evade traditional security measures. This can make it challenging for organizations to protect themselves. These malicious actors also take advantage of the anonymity and global reach of the internet, making it difficult for law enforcement to track and prosecute them.

Deepfakes have become a popular tool for cybercriminals as they can use them to manipulate individuals or organizations into giving up sensitive information or money. For example, in 2019, a UK energy company was scammed out of $243,000 by cybercriminals who used deepfake audio technology to impersonate the CEO and convince an employee to transfer funds.

What are Deepfakes & How Do They Pose a Threat?

From a narrow perspective, deepfakes stem from the combination of deep learning and fake media. Deep learning is a subset of machine learning that utilizes artificial neural networks to analyze large data sets and perform tasks such as image recognition, speech recognition, and natural language processing. Fake media refers to manipulated images or videos that can make people believe something that is not true.

Deepfakes use deep learning algorithms to manipulate existing video or audio footage and create fake content that appears natural. These techniques can include facial mapping, voice synthesis, and image editing to create highly realistic videos that are difficult to detect as fake.

The potential dangers of deepfakes are numerous. One of the most significant threats is the spread of misinformation on a large scale. Deepfake technology allows for the creation of fake news articles, videos, and images that can quickly go viral and deceive people into believing false information. This can severely affect political events, stock markets, or public safety.

Deepfakes also pose a threat to privacy as they can be used to manipulate personal information and images of individuals without their consent. They can also enable cybercriminals to impersonate others and potentially steal identities or sensitive information.

To add to the challenge, deepfakes can be created and shared quickly, making it difficult for authorities to trace the source or stop their spread. This poses a significant threat to trust in the digital age, as people may have trouble distinguishing between real and fake. As deepfake technology improves and becomes more accessible, its risks also increase.

The Role of AI in Facilitating Deepfake Creation and Detection

Artificial Intelligence plays a dual role in the world of deepfakes. One, it enables cybercriminals to create more sophisticated and convincing fake media through techniques such as generative adversarial networks (GANs) and deep reinforcement learning. These technologies allow for the creation of deepfakes that are almost indistinguishable from real videos.

On the other hand, AI is also being leveraged to develop tools and techniques to detect deepfakes. Researchers and experts are using machine learning algorithms to analyze videos and identify discrepancies or patterns that indicate the presence of a deepfake. This includes analyzing facial movements, audio waveforms, and other digital artifacts.

However, detecting deepfakes created by advanced algorithms becomes more challenging as AI evolves. This makes an ongoing cat-and-mouse game between fraudsters and security professionals, each trying to outsmart the other. This highlights the need for constant innovation and advancement in AI technology to stay ahead of cybercriminals.

Synthetic Data: What It Is and Why It Matters

Synthetic data is generated using algorithm-based or mathematical models to solve a specific data-related task. It can take several forms, including deep learning models, agent-based models, or stochastic differential equations. According to Gartner, generative AI will significantly alter 70% of design and development efforts for new mobile and web applications by 2026.

Synthetic data has legitimate uses in research, training AI models, and testing algorithms. It allows for the creating of vast amounts of data that would be challenging or impossible to collect in the real world. For example, autonomous vehicle companies use synthetic data to train their AI algorithms for safe driving scenarios. Collecting this data manually would be time-consuming, costly, and could slow the development process.

It also helps label and interpret data consistently, reducing human error and increasing efficiency. However, synthetic data can also be misused in the cyber domain. Cybercriminals can use it to train their AI algorithms for malicious purposes, such as generating fake identities or mimicking behavior patterns.

The use of synthetic data raises ethical and privacy concerns. Because, it involves creating and using information without the consent or knowledge of individuals. As more organizations utilize synthetic data for various purposes, regulations and guidelines must be established to ensure responsible and ethical use.

The Implications on Cybersecurity and Privacy

While deepfakes, AI, and synthetic data have legitimate uses, they have opened up new avenues for cybercriminals to exploit. Cyber threat actors constantly find new ways to use these technologies for malicious purposes, from sophisticated phishing scams to manipulating biometric security systems. This poses a significant challenge for cybersecurity measures and raises concerns about privacy in the digital age.

IT decision-makers and security professionals must adapt to this evolving landscape of digital threats by implementing robust cybersecurity measures. This includes staying updated on the latest technologies and techniques cybercriminals use, conducting regular vulnerability assessments, and educating employees on identifying and preventing attacks.

Organizations must also prioritize data privacy and implement strategies to protect sensitive information. This can include implementing multi-factor authentication, using encryption for data at rest and in transit, and having robust incident response plans in place.

Strategies to Mitigate the Risks of Cyber Threat Actors

As technology advances and the cyber threat landscape changes, organizations must keep up and stay ahead of potential risks. A robust physical and digital security infrastructure is crucial to mitigating the executive protection risks posed by deepfakes, AI, and synthetic data. This includes implementing robust authentication processes, ensuring secure data storage and transmission, and regularly updating security protocols.

Organizations can also benefit from partnering with cybersecurity experts like ZeroFox to implement a comprehensive risk management strategy. ZeroFox offers advanced AI-driven solutions that help organizations detect and mitigate cyber threats across digital channels. Our platform combines machine learning algorithms, natural language processing, and computer vision techniques to monitor and analyze social media, digital ads, and other online platforms for potential threats.

Below are some key strategies that can help organizations protect against cyber threats:

1. Deepfake Detection and Authentication Techniques

Deepfake detection and authentication techniques aim to identify and verify the authenticity of media content by analyzing various data points. These techniques use advanced algorithms to analyze facial expressions, voice patterns, and other digital signatures to determine if a video is a deepfake.

Additionally, there are various tools and technologies available that can help authenticate media content. This includes:

• Forensic analysis: An authentication technique examines digital artifacts, such as metadata and file structure, for any anomalies or inconsistencies indicating manipulation. For example, poor video quality or mismatched audio can be signs of a deepfake.
• Reverse image and video search: Using image or video recognition software to compare a given media file with the internet's vast database for potential matches. These tools can help verify if the content has been used before or altered in any way.
• Media content provenance: It is a verification process that traces the origin of digital media, providing crucial details on its creation time and location. Various organizations are working towards establishing an industry-wide standard for recording and verifying media content's origin to combat deepfakes.
• Blockchain technology: Blockchain technology offers a decentralized and tamper-proof system for verifying the authenticity of images and videos. Several organizations, such as Proof of Humanity, are leveraging blockchain to create reliable digital ledgers that validate users' identities.

2. Cybersecurity Infrastructure Against AI-Driven Attacks

The urgency for strengthening cybersecurity infrastructure against the weaponization of AI-driven attacks is critical. Organizations must have a robust cybersecurity framework to detect and prevent malicious activities powered by AI algorithms. Some key steps organizations can take to strengthen their cybersecurity infrastructure include:

• Conducting real-time threat assessments: Organizations must continuously monitor their networks for potential threats and vulnerabilities. This includes conducting regular vulnerability assessments, penetration testing, and leveraging cyber threat intelligence platforms to stay updated on the latest attack techniques and trends.
• Implementing a layered security approach: A single layer of defense is no longer enough to protect against advanced cyber threats like deepfakes or AI-driven attacks. Organizations must implement a multi-layered security approach that includes firewalls, intrusion detection systems, antivirus software, data encryption, and more.
• Investing in employee education and training: According to a recent study, cybersecurity awareness and training programs reduce an organization's risk of phishing by 75%. Employees are the first line of defense against social engineering attacks. Therefore, it is crucial to provide them with the necessary skills and knowledge to identify and prevent potential cyber threats.
• Partnering with third-party experts: Organizations should consider partnering with cybersecurity experts like ZeroFox to implement advanced threat detection and mitigation solutions. These experts can help organizations stay updated on the latest attack techniques, guide them on implementing robust security protocols, and offer 24/7 support to respond to any potential threats.

3. Implementing Robust Verification Processes

Identity verification is a critical component of cybersecurity infrastructure. Organizations must establish strong verification processes to ensure that only authorized individuals can access sensitive information. This involves implementing multi-factor authentication (MFA) and continuously monitoring user activity.

MFA requires users to provide multiple forms of identification, such as a password, biometric scan, or security token, before accessing data. It significantly reduces the risk of unauthorized access if one layer is compromised.

Continuous monitoring involves analyzing user activity in real-time and flagging suspicious behavior or unauthorized access attempts. This allows organizations to take immediate action. Such as, revoking access or initiating a security incident response plan, before significant damage can occur.

Some best practices for implementing robust verification processes include:

• Regularly assess and update access controls: Organizations must periodically review and update their access controls to ensure that only authorized individuals have the necessary permissions.
• Use reliable identity verification software: With advancements in AI technology, several identity verification solutions use facial or voice recognition to authenticate users. Organizations should invest in these tools to establish a secure and seamless verification process.
• Train employees on proper password management: Weak or reused passwords are a common vulnerability that threat actors exploit. Organizations should educate employees on the importance of creating and regularly changing strong, unique passwords.

Tags: Artificial Intelligence, Cyber Trends