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Organizations today hold a lot of consumer data. This data can range from their names and email addresses to social security numbers and banking information. Although all of this data can be seen as an asset, there is a serious liability attached to them with respect to protecting this data. Privacy regulations such as the CCPA and GDPR require organizations to protect this data at all costs or risk facing fines for non-compliance.
Before we can dive into Sensitive Data Exposure, let's first look at what sensitive data is.
Personal data is any information that relates to an identified or identifiable natural person, whereas non-personal data includes elements that do not have identifiability and uniqueness to a person. Sensitive Data, on the other hand, is any data that reveals an individuals:
Sensitive data is anything that should not be accessible to unauthorized access, known as sensitive data. Sensitive data may include personally identifiable information (PII), such as Social Security numbers, financial information, or login credentials. Sensitive Data Exposure occurs when an organization unknowingly exposes sensitive data or when a security incident leads to the accidental or unlawful destruction, loss, alteration, or unauthorized disclosure of, or access to sensitive data. Such Data exposure may occur as a result of inadequate protection of a database, misconfigurations when bringing up new instances of datastores, inappropriate usage of data systems, and more.
Sensitive Data Exposure can of the following three types:
Organizations that collect sensitive data are responsible for its protection, and failure to do so can lead to heavy fines and penalties.
Let's take for example, the fines associated with Health Insurance Portability and Accountability Act (HIPAA) and Health Information Technology for Economic and Clinical Health Act (HITECH). HIPAA and HITECH protect a patient's health data, and failure to do so can result in potential violations of up to $1.5 million in a year. Since these fines can continue to accumulate over the course of multiple years, this could accumulate to a large sum which can be disastrous for an organization’s growth plans.
To avoid such exorbitant amounts of fines, organizations must implement appropriate measures to protect the sensitive data of their customers and prevent any breaches.
Data loss is frequently referred to as a data breach or data exposure. Breach and exposure, however, are distinct concepts.
When an authorized individual(s) gains access to a company's or an individual's data, it’s known as a data breach. Frequently, this private information is compromised, stolen, or sold. This is frequently accomplished through security system flaws or human negligence. The most frequent reasons for data security breaches are a human mistake.
Data breaches are possible through various techniques and give malicious actors access to secured data. These assaults may involve malware infections, internal security breaches, brute-force attacks, phishing, and password exploitation.
Data exposure is when sensitive information is lost due to unintentional exposure. This differs from a data breach which occurs when an unauthorized individual or group takes private information during an attack.
Exposure to sensitive data results from a company's action—or lack thereof. This frequently occurs when online data is not adequately protected and encrypted, making it easier to obtain. Data unintentionally uploaded to the wrong database or systems online are typical examples of data exposure.
Data exposure can also refer to data that is easier to obtain due to weak encryption, a lack of encryption, or programming errors. Brand reputation might suffer from data exposure because it is frequently viewed as the business's responsibility.
Data is vulnerable to exposure any time a company lacks security measures. Development and security teams must first have a clear understanding of the ways that data is vulnerable to exposure to improve mitigation techniques for potential application attacks, including:
Data is frequently in motion, transmitting instructions and requests via networks to other servers, programs, or people. Particularly when going across unprotected networks or through the application programming interface (API) that enables apps to communicate with one another, data in transit is extremely sensitive.
A man-in-the-middle (MITM) attack, which intercepts traffic and keeps tabs on communications, is one attack that targets data in transit. Additionally, due to a flaw in SSL protocols, browser-side requests can be modified by code injection attacks like cross-site scripting (XSS).
A system, whether it be a computer or a network, houses data that is at rest. Without the threat of attacks, data at rest is believed to be more valuable but less vulnerable. Attackers use various methods to access stored data, frequently employing malicious software to exploit vulnerabilities and gain access to data at rest.
Attackers might gain access to data stored in files outside of the usual authenticated areas of access if the data is kept on a server. As a result, there is a higher chance of a directory traversal or route traversal attack, in which access is gained to restricted locations on a system.
When a web application does not sufficiently safeguard sensitive information from being exposed to attackers, sensitive data exposure vulnerabilities can appear. Applications hosting information like credit card numbers, medical records, session tokens, or other authentication credentials are the most vulnerable.
It is frequently believed that neglecting to encrypt data is the most frequent error. The submission of a password in cleartext is one illustration of this vulnerability.
Application attacks can expose sensitive data in a variety of ways. These consist of:
The most frequent application attack is SQL injection. A study claimed that application vulnerabilities that might be exploited cause most SQL injection attacks. An SQL injection attack involves hostile actors manipulating SQL requests to perform nefarious commands. Cybercriminals could effectively modify commands to access sensitive data if servers do not have a strong line of defense against identifying modified code.
Attackers may be given continued access to restricted portions of the application and be free to come and go as they want, depending on the severity of the command or request programmable into the malicious code injection.
All information is exposed when a network is compromised, especially when attackers maintain a continued but silent presence, for example, session hijacking.
A session is a period during which users are logged in and are identified by a unique session ID. Attackers who gain access to this ID have access to cookies that save user activity and login information across numerous websites. Bad actors can start assaults using an exploitable vulnerability, leaving little signs of exposure. Users risk having their sensitive data exposed or their identities stolen if cybercriminals are allowed to operate unnoticed.
Applications and networks already have restrictions on what users can and cannot access. When this access is breached, users can gain authentication to locations outside these boundaries, some of which contain sensitive data.
A form of virus known as ransomware encrypts files on the affected system. This malicious software is frequently integrated onto devices using an attachment or link that consumers assume to be from a reliable source. After clicking, ransomware downloads and decrypts data into unreadable code that hackers use to demand a ransom.
Attackers send emails requesting money or information in exchange for the decryption key they control. Attackers have access to all information stored on the computer system and are free to do with it whatever they want because they possess the decryption key.
Phishing attacks frequently dupe users into thinking they are accessing or accessing a reliable website. Attackers disguise themselves as reputable businesses and frequently contact targets via email or text message.
Targets are tricked into divulging private information that criminals exploit to access their accounts and take their credit card information and other sensitive data.
Since insider threats typically include a current or former employee, they represent a danger that all firms must contend with. Anyone working for the organization with access to private information could start a data breach by breaking in and taking confidential data.
As businesses often stay occupied with attacks from outside sources and devote little time to establishing defenses against internal attacks, insider threat attacks and misuse of access frequently go unchecked.
In order to protect their consumers data, organizations need to make sure they keep track of all the data stored within their systems and perform an audit. This will give them a clear picture of owners, locations, security, and governance measures enabled on the data.
Assess Risks Associated to Data
In order to protect data, organizations need to have a clear understanding of the data risk and allocate budgets & resources for risk mitigation activities accordingly. The more sensitive the data is, the higher the risk of harm will be. Even a small amount of highly sensitive data can have a high impact on data subjects.
Appropriate security controls
Organizations must have appropriate security controls in place to avoid the occurrence of sensitive data exposures as well as to limit their impacts on data subjects.
Organizations must have an effective breach response mechanism in place to immediately respond to sensitive data exposure.
Attacks that obtain access to a system and are allowed to snoop around in illegal locations unnoticed can do great harm and jeopardize an organization's integrity.
When an organization experiences a data breach, it attracts criticism. Even after security breaches are fixed, users start to see them as unreliable or unsafe, which makes them less likely to accept personal information from them.
Media attention is drawn to a data breach once it has affected millions of people and grown significantly. Media coverage and unfavorable brand security connections might tarnish a company's reputation for years to come. This costs the organization a great deal of money they might never recover financially.
Another significant issue that raises costs is the time it takes to find a breach. Costs increase as detection and containment times lengthen. Faster detection times may result in significant financial savings and potentially the recovery of certain private client information.
Business operations cease when harmful activity is discovered within a company. Any halt in network and business activities may result in losses. Getting the website back up and running causes clients to lose interest or confidence.
For organizations, violating regulations can have some of the worst repercussions, including heavy fines. For instance, major GDPR violations can result in fines of up to €20 million, or 4% of an organization's annual global turnover (whichever is higher). Another example is the CCPA, which levies civil penalties of up to $7,500 for each deliberate violation and a maximum of $2,500 per violation.
As the world becomes more digital, organizations all around the world have started to collect more and more personal data. The collection and processing of personal data help organizations to not only understand their consumers better and increase consumer satisfaction but also generate revenue. That being said, most organizations have limited visibility into personal data due to the large volume of personal data they collect and their spread across heterogeneous systems. Personal data is distributed across a large number of platforms and systems, such as on-premises, hybrid, and multi-cloud data assets.
Sensitive Data Intelligence helps organizations overcome these challenges by creating visibility into personal and sensitive data across all structures of the organization. This visibility helps organizations classify datasets as per their sensitivity, assign risk scores to datasets depending on how much security a particular type of dataset needs, and link data to its correct owners (data subjects). All of this is achieved by streamlined workflows and policy-based automation.
Sensitive Data Intelligence (SDI) is a class of solutions that help organizations discover, analyze, and protect large datasets. These solutions are purpose-built and fully automated for handling petabyte-scale of data across cloud-native & non-native assets, both on-premises and multi-cloud, in structured and unstructured formats.
Securiti’s SDI solution offers the following functionalities:
Securiti can enable organizations to improve their command on the sensitive data they hold, in turn making them more compliant with global privacy regulations and a trustworthy brand amongst their customers.
Request a demo today to see how it works and can help your organization!
An example of sensitive data exposure is when a healthcare organization's patient records, including medical history and social security numbers, are inadvertently made publicly accessible online.
Insecure storage, misconfigured databases, inadequate access controls, data breaches, and accidental publishing can cause sensitive data exposure.
Data exposure refers to situations where the personal information of data subjects, including sensitive or confidential information, becomes accessible to unauthorized individuals, whether intentionally or unintentionally.
Risks of sensitive data exposure include identity theft, financial fraud, reputation damage, regulatory penalties, and loss of trust among customers or clients.