What is a Data Breach?

A data breach is an incident where sensitive, confidential, or protected information is stolen, accessed, or exposed without authorization. Data breaches can lead to security risks, financial loss, regulatory penalties, and other legal consequences.

While security risks are inherent in the software development lifecycle (SDLC), data breaches are a critical security concern because they can expose source code, leak sensitive information, compromise user data, and create vulnerabilities in entire systems. This inevitably causes reputational and financial damage. According to IBM’s 2024 Cost of a Data Breach Report, the global average cost of a data breach is USD $4.88 million.

Types of data breaches

Data breaches can happen in various ways, often due to manual errors or misconfigurations in digital infrastructure. Below are some of the most common types:

Credential theft and password breaches

Credential theft occurs when attackers gain access to sensitive login details through weak passwords, credential stuffing attacks, or brute-force attempts. Once stolen, these credentials can be used to breach private systems, compromising sensitive data and user accounts.

API and cloud misconfigurations

Publicly exposed APIs and unsecured cloud storage can provide unauthorized access points for attackers. When security measures are not properly configured, cybercriminals can exploit these weaknesses to extract sensitive data and gain control over critical systems.

Malware and ransomware attacks

Malicious software, such as ransomware, is often used to steal, encrypt, or destroy data, demanding payment from victims in exchange for restored access. Supply chain attacks can also introduce vulnerabilities into software, affecting both developers and end-users by distributing compromised code.

Insider threats and human error

Employees or contractors can intentionally or accidentally leak sensitive information, leading to a breach. Common mistakes, such as pushing secrets to public repositories, can expose confidential data to attackers and create security risks.

How do data breaches happen?

Data breaches are often the result of security flaws and targeted attacks. Below are some common causes and attack methods.

Common causes of data breaches

Many data breaches are caused by exploiting security vulnerabilities. Some of the most common vulnerabilities include:

• Poor API security: Unsecured endpoints and lack of authentication security can create vulnerabilities that allow unauthorized individuals to access sensitive data.

• Insecure coding practices: Leaking credentials in the code or failing to encrypt sensitive information can leave software open to exploitation by attackers.

• Weak authentication: The absence of strong authentication, like passkeys or 2FA, allows malicious actors to guess or crack passwords to gain unauthorized access to systems and databases.

• Third-party dependencies: Vulnerable open-source libraries and software components can introduce security risks. Attackers may exploit flaws in these external dependencies to gain access to a system.

Common attack methods used by hackers

Malicious attacks frequently happen through impersonation, injecting malicious code, or intercepting sensitive information. Some common attack methods include:

• Phishing and social engineering: These attacks trick users into revealing sensitive credentials by impersonating trusted entities through fake emails, websites, or messages.

• Malware and ransomware: Attackers inject malicious code into a system to steal, encrypt, or corrupt data, often demanding payment for restoration.

• Man-in-the-Middle (MITM) attacks: Attackers intercept communications between users and systems to steal login credentials or sensitive information.

• Cross-Site Scripting (XSS): Attackers inject malicious scripts into web applications, allowing them to steal session tokens, hijack user accounts, or manipulate website content.

• SQL injection (SQLi): Attackers target vulnerabilities in databases by injecting malicious SQL queries, allowing them to gain unauthorized access to sensitive data. Exploited databases can be manipulated to expose, delete, or modify crucial records, compromising user privacy and business operations.

• Brute force and credential stuffing attacks: Attackers repeatedly attempt different password combinations or use previously leaked credentials to access user accounts. Without strong authentication measures like multi-factor authentication, attackers can successfully infiltrate systems, leading to data breaches and identity theft.

The impact of data breaches

A data breach can have significant consequences for both businesses and individuals, including:

• Financial losses: Companies may incur high costs related to disaster recovery, incident response, regulatory fines, insurance premiums, and lost business due to a decline in customer trust.

• Reputational damage: A breach can erode public confidence in an organization, leading to a decline in customer retention and challenges in acquiring new clients.

• Legal consequences: Many jurisdictions enforce strict data protection laws, and non-compliance can result in penalties, lawsuits, loss of licenses, and other long-term legal obligations.

Reducing these risks involves using strong security measures, keeping a close watch for threats, and having a clear plan to respond to incidents quickly.

Real-world examples of data breaches

Data breaches can wreak havoc on organizations and impact millions of patients or customers, compromise government security, and incur enormous legal and regulatory costs. Here are a few examples or notable data breaches in recent years:

Nvidia data breach

What happened? In 2022, Nvidia, a major chip manufacturer, experienced a cyberattack where up to 1TB of data was stolen, including employee credentials and proprietary information.

Impact: Hackers demanded Nvidia remove limitations on its GPUs, and internal source code was leaked. The company had to take several security measures to mitigate further damage.

Flagstar bank data breach

What happened? In 2021, hackers accessed 1.5 million customers' sensitive data after a breach of Flagstar Bank’s network.

Impact: The breach exposed Social Security numbers, leading to potential fraud risks. The bank offered affected customers two years of identity protection services.

T-Mobile data breach

What happened? T-Mobile suffered a massive data breach in 2021 that exposed sensitive personal information of over 76 million customers. The hacker exploited a misconfigured internet-exposed router to access customer names, Social Security numbers, driver’s license numbers, and other personal identifiers.

Impact: T-Mobile faced multiple lawsuits, regulatory scrutiny, and had to offer free credit monitoring to affected users. The breach also led to a $350 million settlement. An FCC investigation of repeated cybersecurity issues resulted in a $15.75 million fine, plus an additional $15.75 million investment to improve its security infrastructure.

Best practices for preventing data breaches

Data breach prevention requires a comprehensive, proactive approach. There are several best practices to minimize risk to your organization, including:

• Follow secure coding principles: Writing secure code involves following best practices such as avoiding hardcoded credentials, implementing input validation, and ensuring proper data encryption. By maintaining secure coding standards, your organization can reduce vulnerabilities that attackers might exploit.

• Conduct regular security audits: Conducting penetration testing and threat modeling helps identify weaknesses in your security framework. Routine security assessments help mitigate potential threats before they can be exploited.

• Implement DevSecOps practices: Embedding security into the SDLC ensures security considerations are addressed at every stage of development. By integrating application security testing and practices like shift left testing into software development workflows, organizations can identify and fix vulnerabilities early in the process.

• Create incident response plans: Having a clear incident response plan allows organizations to detect, contain, and mitigate security breaches more efficiently. Well-prepared teams can respond quickly to security incidents, minimizing damage and reducing downtime.

• Seek ongoing security training: Educating development teams on cybersecurity best practices helps them recognize threats and implement secure coding practices. Ongoing training ensures teams stay updated on emerging threats and modern security measures.

How AI-powered security tools can help prevent data breaches

AI-driven security tools and automation play a crucial role in analyzing vulnerabilities and identifying and mitigating cybersecurity threats.

Threat detection and response

AI-powered security tools continuously analyze network traffic and system behavior to identify anomalies that may indicate a cyber threat. By automating threat detection, these systems help security teams respond faster to potential breaches, reducing the risk of data loss or system compromise.

Code scanning for vulnerabilities

AI-enhanced code analysis tools detect security flaws in software before deployment by performing both static and dynamic analysis. This proactive vulnerability scanning approach helps developers identify misconfigurations and insecure coding practices early in the SDLC, minimizing vulnerabilities before they reach production.

Secret scanning and credential protection

Automated security tools help detect and block exposed secrets, such as API keys and passwords, before they can be exploited. These systems not only prevent accidental leaks but also revoke compromised credentials and notify teams in real-time to mitigate risks.

Intelligent access controls and identity protection

AI-powered authentication systems assess user behavior to detect suspicious login attempts and enforce least-privilege access policies. Features like multi-factor authentication (MFA), biometric verification, and adaptive access control enhance security by making unauthorized access significantly more difficult.

Automating security compliance and patch management

AI-driven tools continuously scan for outdated software and automate security updates, ensuring systems remain protected against known vulnerabilities. Automated compliance reporting further helps organizations maintain security standards while reducing the manual workload on security teams.

AI-powered security tools from GitHub

GitHub offers advanced security tools that help teams secure sensitive data, detect vulnerabilities, and automate compliance at every stage of the software development lifecycle. These tools are essential in data breach management, providing real-time security insights and proactive risk mitigation strategies to protect code and confidential information.

• GitHub Code Security in GitHub Advanced Security identifies security flaws in code using CodeQL analysis, helping developers detect and fix vulnerabilities before deployment.

• GitHub Secret Protection detects and prevents the accidental exposure of sensitive credentials such as API keys and passwords, reducing the risk of unauthorized access.

• Dependabot monitors project dependencies, flags vulnerable libraries, and automates security updates.

Security policies and compliance features help organizations adhere to security best practices and data protection regulations across repositories.