Do you fully grasp the magnitude of sensitive data exposure? It stands as one of the most prevalent and menacing threats to organizational security in 2024.

Picture any information quintessential to an individual's or a company's identity and safety – personal, financial, health, or trade secrets. When such critical data sees the light of day in places it shouldn't, the dominoes start to fall: identity theft, scams, legal battles, tarnished reputations, and steep regulatory penalties. You don't want your company to lose millions of $$$ no matter what through a scam, PCI DSS violation, or exposed Stripe tokens in the wild, right?

In 2024 think Spoutible where hackers could access extensive user data, including names, usernames, bios, email addresses, IP addresses, and phone numbers, or Glow where user data was leaking from Glow’s developer API. What security lessons can we learn there? You must stay vigilant and take care of your data security.

In this blog post, we'll unpack the concept of sensitive data exposure, where we stand in 2024, and, vitally, strategies to protect your organization against it. From best practices to some practical tips, we're here to help you secure your applications against the unauthorized reveal of sensitive information!

What is sensitive data exposure?

Sensitive data exposure is the inadvertent or intentional revelation of confidential or private information to unauthorized individuals or entities. This type of security breach occurs when sensitive data, such as personally identifiable information (PII), payment card information (PCI), electronic protected health information (ePHI), and intellectual property (IP) is accessed, disclosed, or leaked without proper authorization.

Yes, anything from your Social Security numbers to your darkest trade secrets falls into this category because, let's face it, their confidentiality is of utmost importance.

When PII, such as names, addresses, or social security numbers, is exposed, it can lead to identity theft, financial fraud, or other forms of exploitation. Similarly, the disclosure of PCI can result in unauthorized transactions, fraudulent charges, and financial losses for both consumers and businesses. ePHI exposure can compromise patient privacy, violate healthcare regulations, and undermine trust in healthcare providers. Additionally, IP theft can have severe consequences for businesses, including loss of competitive advantage, revenue, and reputation.

Now, you might be thinking, "How does this even happen?" The truth is, it might happen without anyone from your team even knowing about it (hello, Shadow APIs): settings that weren't configured correctly, a simple human blunder, security defenses that were more decorative than useful, or even a targeted strike by hackers. The fallout? Let's just say it ranges from someone stealing your identity to your company taking a serious hit in terms of reputation, not to mention potential legal battles and hefty fines from regulatory bodies for letting the ball drop on data protection.

Sensitive data exposure vs data breach

It's crucial to note that sensitive data exposure and a data breach are distinct concepts, even though we might use these terms interchangeably.

A data breach occurs when there is unauthorized access to sensitive data, leading to its compromise, theft, or misuse. A data breach can result from various security incidents, including hacking attacks, malware infections, insider threats, or physical theft of devices containing sensitive information.

Sensitive data exposure can be considered a precursor to a data breach; it signifies the potential vulnerability of sensitive information to unauthorized access or disclosure. If not addressed promptly, sensitive data exposure can escalate into a full-fledged data breach, with serious repercussions for affected individuals and organizations.

So, keep in mind that just because an exposure exists, doesn't mean will be breached, but, unfortunately, the chances of it are significantly increased.

How sensitive data exposure leads to attacks?

Have you ever paused to consider the domino effect that sensitive data exposure triggers? Once the information falls into the wrong hands, it becomes a tool for lots of harmful actions.

Think identity theft, fraud, phishing, ransomware attacks – the list is as diverse as it is daunting. Picture this: an attacker stumbles upon a cache containing credit card numbers or login credentials. What follows? Unauthorized shopping sprees (and of much bigger magnitude than in your neighborhood mall during Black Friday) or access to sensitive accounts.

But that's just scratching the surface. Exposed data doesn't just invite random acts of cybercrime; it lays the groundwork for highly targeted and skillful attacks. We're talking about spear phishing, business email compromise, API attacks, even intricate social engineering scams.

Imagine attackers getting their hands on personal or confidential data. With such intel, they could masquerade as trusted entities, writing deceptive emails, or building fake websites that look frightfully legitimate, tricking victims into surrendering even more information or taking detrimental actions.

Even large organizations are not exempt: for example, a couple of years ago hackers targeted Netflix users with phishing emails claiming their accounts were on hold and prompting them to update their payment details on a fake website, so even Federal Trade Commission issued warning.

In some cases, you might get lucky though and a security researcher or someone else might disclose sensitive information exposure like it was done in the case of JetBlue on Hackerone. While running through scan some endpoints on Jetblue subdomains were disclosing sensitive information. This issue was found in 2022 but was disclosed just recently in March 2024.

Common ways data is infiltrated

How can data be infiltrated? Well, it's not just about hacking into systems. The moment data infiltration happens, the door to data exfiltration — the act of moving data to a new, unauthorized locale — creaks open.

Understanding the common techniques used by cybercriminals to infiltrate data can provide invaluable insights into identifying vulnerabilities, implementing effective security measures, and mitigating the risk of data breaches.

So, let's take a look:

• Social engineering and phishing attacks: Phishing involves tricking individuals into divulging sensitive information, such as login credentials or financial details, by impersonating trusted entities through deceptive emails, text messages, or websites. Picture this: an email, sleek and convincing, impersonating your bank or a governmental body, arrives in your inbox. Or perhaps, a text message asking you to pay driving fines (even if you're like me and haven't sat behind the wheel for 3 years). Why does it work? Because it targets the most vulnerable link — us, humans.
• Broken access control: Think OWASP Top 10 2023's Broken Object Level Authorization and Broken Function Level Authorization, broken access controls continue to be a significant concern. Unauthorized users exploit vulnerabilities in access controls, bypassing security measures meant to protect data and applications, leading to data infiltration incidents.
• Malware and ransomware attacks: Malware, including viruses, ransomware, and Trojans, can infiltrate systems through malicious email attachments, infected websites, or removable storage devices. Once inside a system, malware can steal sensitive data, disrupt operations, or hold data hostage for ransom. Deploying antivirus software, regularly updating operating systems and applications, and restricting user permissions can help mitigate the risk of malware infections and their associated data infiltration.
• Evolving SQL Injection Attacks: SQL injection attacks persist as a prevalent threat, allowing attackers to inject malicious queries into systems and extract valuable information or compromise databases. Despite efforts to mitigate this risk, SQL injection flaws continue to be exploited by cybercriminals.

• Insider threats: Sometimes, the enemy is within. These are the attacks executed by individuals who're already a part of your organization — employees, contractors, or partners who have legitimate access to the sensitive data. What might drive their actions? A wide spectrum of motives ranging from greed, revenge, curiosity, or blackmail. Their methods might include copying data onto external devices, transferring it to personal accounts, or outright leaking to external entities.

Where do we stand in 2024?

In 2024, sensitive data exposure remains a critical concern. We all know that cyberattacks are getting more advanced. In addition to that, vast amounts of sensitive information are generated, stored, and transmitted across various platforms and devices, and in the upcoming years, these amounts will only increase exponentially.

Advances in technology, including artificial intelligence (AI), machine learning (ML), blockchain, and digital twins, bring both opportunities and challenges in dealing with sensitive data exposure. AI and ML-powered solutions can boost threat detection, incident response, and risk management by analyzing large data sets and spotting unusual patterns. Moreover, digital twins, which are virtual replicas of physical assets or processes, can provide valuable insights for improving cybersecurity measures.

A digital twin is a digital copy of something that exists in the real world. So an example of this would be, let's say, critical infrastructure. You know, we have some kind of critical infrastructure system, and we could create a digital twin, so basically a digital copy of this system device. Even though it's a digital copy, it is getting data from the real system. And then all of this data is being used to basically simulate what this system is. So that if we were to, let's say, attack it, we can attack the digital twin and see what would the system do if it is attacked in some way, how would it respond? And sometimes you use AI for that because you need AI to analyze all of this data. So I think this is one of the trends that stands out. – Anmol Agarwal, Security Reseacher at Nokia at the Elephant in AppSec podcast

However, these technologies also come with potential risks like algorithmic bias, data poisoning, and adversarial attacks, which could worsen sensitive data exposure if not handled properly. Therefore, while leveraging these innovations can enhance cybersecurity efforts, organizations must also remain vigilant and implement best practices and robust protection measures to mitigate associated risks effectively.

How to prevent sensitive data exposure?

To prevent sensitive data exposure effectively:

1. Implement robust access controls: Use role-based access controls (RBAC) and encryption to limit access to sensitive data only to authorized users.
2. Employ data loss prevention (DLP) solutions (see the best solutions on Gartner): Deploy DLP tools to monitor, detect, and prevent unauthorized transmission or use of sensitive data.
3. Build a proper inventory of all your applications: You can't secure what you can't see. So, building a comprehensive inventory of all your applications first and avoiding sprawl is paramount.
4. Conduct regular automated security testing: Employ automated security testing tools like Escape to identify vulnerabilities and weaknesses in software applications and infrastructure. As the world continues to accelerate development cycles, organizations should never compromise security.
5. Enforce Least Privilege Principle: Limit user access rights to the minimum necessary for their job function to reduce the risk of unauthorized data exposure.
6. Educate all internal teams, not only developers: Provide comprehensive security training and guidance to all internal teams to ensure secure coding practices and awareness of potential data exposure risks. Inspire internal teams to bring security solutions:

   The QA team were normally very shy, very quiet people, who just sort of did their job. They had not only signed up and done their training, all on their own, but they then organized a presentation and made all of the developers and the senior leaders come and then told them why they were all doing security wrong and how they were going to help them fix it. And so they'd gone on this adventure from nothing to deciding to do some training, to working together to then plan how they were gonna make things better, and then engaging their whole senior team to make that happen. – Laura Bell Main on the Elephant in AppSec podcast

7. Establish incident response procedures: Develop and regularly test incident response plans to effectively respond to and mitigate the impact of data exposure incidents.
8. Secure data transmission: Use secure protocols such as TLS/SSL for data transmission to prevent interception and unauthorized access during transit.
9. Regularly update and patch systems: Keep software, operating systems, and applications up-to-date with the latest security patches to address known vulnerabilities and reduce the risk of exploitation.
10. Monitor and audit data access: Implement robust logging and monitoring mechanisms to track data access and detect suspicious activities in real-time.
11. Implement Multi-factor Authentication (MFA): Require multiple forms of authentication to access sensitive data or systems, enhancing security against unauthorized access.

So, what have you learned?

Throughout this deep dive, you might have discovered what sensitive data exposure really means, its differentiation from data breaches, the common infiltration methods, and the sensitive data exposure state in 2024. But, we didn't just stop there. We also provided you the best practices how to secure your organization – think data encryption, stringent access controls, and the do's and don'ts of storing sensitive data.

And if you need an automated way to protect your APIs from sensitive data exposure, we at Escape are here for you. Reach out to our team to get your free API exposure and API security assessment!

💡 Want to learn more?

Check out the following articles:

• How to secure your API secret keys from being exposed?
• How to avoid data breaches with GraphQL?
• What is a Shadow API? Understanding the risks and strategies to prevent their sprawl
• How to secure gRPC APIs

*** This is a Security Bloggers Network syndicated blog from Escape - The API Security Blog authored by Alexandra Charikova. Read the original post at: https://escape.tech/blog/sensitive-data-exposure/