Credential stuffing is a type of cyberattack where attackers use stolen username and password combinations, often obtained from previous data breaches, to gain unauthorized access to multiple online accounts. The attacker automates the process of trying these combinations across various websites, hoping that users have reused the same login details.
Credential Stuffing vs. Password Stuffing: Understanding the Difference
Credential stuffing attacks, sometimes called password stuffing attacks, have become a significant concern in cybersecurity. These attacks are relatively easy for cybercriminals to execute and challenging for security teams to detect. Before we begin, let’s break down the difference between credential stuffing and password stuffing:
- Credential Stuffing: This attack occurs when hackers use stolen username and password combinations, often obtained from previous data breaches, to gain unauthorized access to multiple user accounts across various websites or services. The key element here is the exploitation of reused credentials.
- Password Stuffing: In contrast, password stuffing meaning typically focuses on using lists of common or previously leaked passwords to try against different usernames without necessarily relying on complete username-password pairs from a breach.
How Credential Stuffing Works
Credential stuffing exploits reused usernames and passwords, allowing attackers to automate login attempts across multiple sites to gain unauthorized access.
- Data Collection (Acquiring Stolen Credentials)
- Source of Credentials: The attacker acquires large datasets of stolen usernames and passwords, usually from previous data breaches of various websites and services. These datasets are often available on the dark web or other illicit platforms.
- Automated Attack Setup
- Botnets or Scripts: The attacker uses bots, scripts, or automated software tools (e.g., Sentry MBA or Snipr) to attack. These tools can handle large-scale login attempts by rapidly inputting the stolen credentials into login forms.
- Proxy Networks: To avoid detection, attackers often use proxy servers or VPNs to hide their real IP addresses. This helps bypass rate-limiting mechanisms and prevents the accounts from being blocked after too many failed login attempts.
- Attack Execution
- Mass Login Attempts: The attacker’s bot sends login requests to a website using the stolen username and password combinations one at a time. Since many users reuse passwords across different platforms, the attacker hopes a valid combination will work for different services.
- Credential Variations: Attackers might modify the credentials slightly (e.g., by adding numbers or special characters) to increase their chances of success across multiple sites.
- Volume and Speed: These attacks are designed to be highly efficient, attempting thousands or even millions of logins quickly.
- Post-Attack Activity
- Harvesting Information: Once the attacker has access to an account, they can extract valuable information like credit card numbers, addresses, and other personal details.
- Monetizing the Access: The stolen or compromised credentials/accounts can be sold on the dark web, used to steal money directly, or leveraged for further attacks.
Credential Stuffing vs. Brute Force Attacks
The primary difference between credential stuffing and brute force attacks lies in the attack method, the type of data used, and the target to gain unauthorized access to accounts.
| Category | Credential Stuffing | Brute Force |
| Input | Stolen Credentials: Uses lists of previously stolen or leaked username and password combinations. Reused Credentials: This relies on users reusing the same credentials across platforms. | Guessing Passwords: Systematically tries all possible combinations of characters for a given account. Do not rely on stolen credentials. |
| Attack Method | Automated Login Attempts: Uses scripts or bots to test large sets of stolen credentials across multiple websites rapidly. | Exhaustive Search: Attempts to guess passwords by trying every possible combination, starting with common ones. |
| Attack Target | Targeting Multiple Accounts: This strategy focuses on multiple accounts or websites using the same set of credentials, relying on password reuse. | Single Account or Service: Focuses on a specific account or service, attempting to guess the correct password. |
Real-World Examples and Case Studies
Yahoo (2014-2016)
Overview: Yahoo’s data breach, disclosed in 2016, compromised 3 billion accounts from an attack in 2013, making it the largest breach in history. A separate 2014 breach affected 500 million accounts, with both incidents linked to state-sponsored actors.
Impact: The attackers accessed user accounts by exploiting reused credentials from previous breaches. Many of these accounts were targeted through credential stuffing techniques as users often reused the same credentials across multiple sites.
Outcome: This breach remains one of the largest in history and highlights the risks of password reuse. It significantly damaged Yahoo’s reputation and eventually contributed to Verizon’s decision to acquire Yahoo at a reduced price.
Amazon (2018)
Overview: In 2018, it was reported that Amazon had been the target of credential-stuffing attacks, in which cybercriminals attempted to gain unauthorized access to customer accounts by using stolen login credentials from previous breaches.
Impact: Attackers targeted Amazon customer accounts, attempting to make unauthorized purchases or use stored payment information. Credential stuffing attacks were particularly effective due to the many breaches of credentials on the dark web.
Outcome: Amazon responded by enforcing additional security measures, including more robust fraud detection systems and enhanced authentication mechanisms.
Shopify (2020)
Overview: In 2020, Shopify experienced a credential stuffing attack targeting their users’ store accounts. The attackers used a combination of stolen credentials and an enormous scope of user accounts, leveraging the data from previous breaches.
Impact: The attackers gained access to merchant accounts, but Shopify was quick to detect the unauthorized activity. In some cases, the attackers gained access to private data like transaction details or customer information.
Outcome: Shopify responded by immediately suspending affected accounts and implementing enhanced fraud detection protocols to prevent further attacks.
Why Credential Stuffing is on the Rise
Credential stuffing has become a growing concern in recent years, with organizations and individuals facing a surge in these attacks. Understanding the factors driving this increase can help highlight the risks and emphasize the importance of stronger security practices. Below are some primary reasons why credential stuffing has become a growing concern.
Massive Data Breaches
- Exponential Increase in Breached Data: Over the years, the frequency and scale of data breaches have grown dramatically. Cybercriminals can access many stolen usernames and passwords from breaches of companies, websites, and social media platforms. This increases the pool of credentials available for future credential-stuffing attacks.
Password Vulnerabilities
- Human Behavior: Many users continue to reuse passwords across multiple sites. This means that if an attacker obtains a set of login credentials from one breach, they can try those credentials on different services (e.g., email, banking, shopping platforms) with a high chance of success.
- Weak Password Hygiene: People still often choose weak passwords, like simple combinations or default passwords, which are easy to guess. This makes accounts more vulnerable to credential stuffing.
Automation Tools
- Ease of Execution: Credential stuffing attacks are highly automated. Cybercriminals use bots and scripts to quickly test thousands or millions of stolen login credentials across different platforms. These tools make it much easier to scale such attacks.
- High Efficiency: Automation allows attackers to launch these attacks rapidly without manual intervention, increasing the scale and speed at which they can compromise accounts.
- Bot Development: Cybercriminals develop increasingly advanced bots capable of simulating human behavior to evade detection. These bots can solve CAPTCHA challenges, rotate through user agents, and even bypass multi-factor authentication (MFA) in some cases.
Increased Use of Online Services and Remote Work
- More Targeted Accounts: As more services move online, individuals have more accounts that can be targeted, ranging from social media to banking and e-commerce. This broadens the scope for credential stuffing attacks.
- Increased Internet Connectivity: With the growing number of devices connected to the internet (IoT, smart devices), attackers now have access to more points of entry and can use credential stuffing to target accounts on these devices.
The Consequences of Credential Stuffing
Credential stuffing can have far-reaching consequences, affecting both individuals and organizations. Examining the impact of these attacks reveals why they pose such a significant threat to security and trust.
Financial Loss
- Direct Financial Impact: If attackers gain access to financial accounts, they can make fraudulent purchases, transfer funds, or commit other forms of fraud. For e-commerce sites, this could lead to chargebacks or revenue loss.
- Cost of Remediation: Companies may face significant costs to investigate the breach, compensate affected users, and recover from the attack. This can include legal fees, customer support, and cybersecurity measures.
IBM’s 2023 Cost of a Data Breach Report indicated that the average cost of a data breach (which could include credential stuffing attacks) was approximately $4.45 million. Credential stuffing, depending on its scale, can contribute significantly to the overall breach costs.
Identity Theft and Privacy Violations
- Stolen Personal Information: If attackers successfully access personal accounts (email, social media, etc.), they can steal sensitive information such as names, addresses, phone numbers, and payment details, leading to identity theft or fraud.
- Exposure of Sensitive Data: For businesses, compromised accounts might contain personally identifiable information (PII) of customers, which could lead to data breaches, regulatory fines, and public backlash.
Reputational Damage
- Loss of Trust: Customers may lose trust in a company that experiences a credential stuffing attack, significantly if sensitive data is compromised or if the company is seen as failing to protect user information. This can lead to customer churn and reduced brand loyalty.
- Negative Impact on Partnerships: Businesses that rely on partnerships may see strained relationships or lose credibility with partners if their security is breached. Trust in the company can affect business negotiations and future collaborations.
Exploitation for Further Attacks
- Phishing and Social Engineering: After gaining access to a user’s account, attackers might use it as a launching pad for phishing campaigns. They can impersonate users to trick their contacts into revealing personal or financial information.
- Cross-Service Attacks: If attackers gain access to one account, they might use the same credentials to attempt logins to other services. If the user has reused their password, attackers can access other accounts, further escalating the attack’s impact.
- Credential Sales: Stolen credentials can be sold on the dark web, contributing to a larger cybercrime market. Attackers may exploit this market to launch further campaigns or provide credentials to other malicious actors.
Prevention and Defense Mechanisms
Below are some best practices and methods for mitigating credential stuffing attacks.
Multi-Factor Authentication (MFA)
- Additional Verification: MFA requires users to verify their username and password. This second factor could be something the user knows (like a PIN), something they have (like a smartphone or hardware token), or something they are (biometric data like fingerprints).
- Mitigation of Password Reuse: Since credential stuffing attacks often exploit the fact that users reuse passwords across multiple sites, MFA makes it far more difficult for attackers to gain access, even if they have the correct username and password.
Password Managers
- Individual passwords for each account: As reusing passwords is often a result of password complexity required for online services, users tend to rely on one or only very few complex but memorized passwords. Password Managers support the user by keeping complex passwords and passphrases in a secure container.
- Automatic checks for reuse or compromise: Modern password managers do check the stored password for reuse by the user and verify accounts and password with known compromised account credentials.
CAPTCHA
Requires users to complete a simple task for humans but is difficult for automated bots to replicate.
Text-based CAPTCHA
- Distorted Text: This is the traditional form of CAPTCHA where users are asked to type in distorted letters or numbers from an image. The distortion makes it hard for bots that rely on algorithms to recognize simple patterns and decipher the characters correctly.
Image-based CAPTCHA
- Object Recognition: A modern variation of CAPTCHA asks users to select images that contain specific objects (e.g., “Click all images with traffic lights” or “Select the images with bicycles”). Humans can readily recognize objects, but this task is still difficult for bots, especially if the images are varied or have background noise.
Invisible CAPTCHA (reCAPTCHA v3)
- Behavioral Signals: Invisible CAPTCHA uses machine learning models to analyze patterns, such as how the user scrolls or clicks, which are unique to human behavior and challenging for bots to mimic.
Bot Detection
Bot detection or bot management involves monitoring various behavioral, network, and technical signals to determine if a user is a human or a bot. Various methods are employed to catch bot activity, often in conjunction with CAPTCHA systems.
- Behavioral Analysis. Human users interact with web pages in a way that bots generally cannot replicate, including mouse movements, typing patterns, and page interaction patterns. Bots also tend to fill out forms or perform actions at speeds that are too fast for human users, so analyzing input delays can help identify bots.
- IP Address and Geolocation Analysis. Bot detection systems track IP addresses and their reputations. Known proxies or VPNs often used by bots to mask their actual location can trigger suspicion. If many requests come from the same IP address in a short period, this may be flagged as a bot attack. Bots also try to access services or resources from countries where they don’t have accounts or unusual locations. For example, a user from one country logging in to an account in another country might be flagged as suspicious.
- Browser and OS Anomalies. A bot might use an uncommon or automated browser version or an operating system mismatch, which can be used to identify suspicious activity.
Device Fingerprinting
By tracking unique attributes of a user’s device, such as browser type, operating system, screen resolution, and installed plugins, it helps identify suspicious or anomalous login attempts. Since bots typically do not operate from natural environments or present realistic device fingerprints, this method can quickly distinguish between legitimate users and automated attack attempts. By detecting and blocking these suspicious logins, device fingerprinting adds an additional layer of protection against credential stuffing.
IP Blacklisting
In credential stuffing attacks, attackers use automated bots to attempt large volumes of stolen usernames and passwords in order to gain unauthorized access. Since these attacks often originate from a limited set of IP addresses, blacklisting these addresses can be an effective defense mechanism. By blocking the IPs associated with malicious activity, organizations can significantly prevent credential stuffing attacks succeeding, preventing unauthorized access before it happens.
Rate Limiting
By restricting the number of requests an IP address or user can make within a specific time frame, rate limiting helps block automated bots, which often make rapid, repeated login attempts. This technique can significantly slow down or stop credential stuffing attacks, as bots typically exceed the request limits. To enhance security without disrupting legitimate user activity, it’s recommended to apply rate limits to residential IP addresses, providing an additional layer of protection against these malicious attacks.
Passwordless Authentication
Passwordless authentication is a security mechanism that allows users to authenticate without entering a traditional password. Instead, it leverages alternative methods such as biometrics (fingerprints, facial recognition), hardware tokens (e.g., security keys), one-time passcodes (OTPs), or push notifications to verify the user’s identity. This approach significantly enhances security and helps protect against various cyberattacks, including credential stuffing, phishing, and password-based attacks.
Advanced Strategies for Protecting Against Credential Stuffing
As credential-stuffing attacks become more sophisticated, organizations must adopt advanced strategies to stay ahead. Leveraging technologies like AI, machine learning, and obfuscation techniques can provide a deeper level of protection, making it harder for attackers to succeed.
Use of AI and Machine Learning
Modern AI tools are crucial in identifying and preventing credential stuffing attempts by leveraging advanced machine learning and behavioral analysis techniques. These tools can analyze large volumes of data and recognize suspicious patterns in real time, allowing them to detect and block malicious automated login attempts that traditional security systems may miss.
- Behavioral Profiling: AI-powered systems analyze normal user behavior to build a baseline of legitimate login attempts. These systems can then detect deviations from this baseline, such as an unusually high number of login attempts from the same IP address or abnormal patterns in login times or locations.
- Dynamic IP Monitoring: AI systems can track and evaluate the reputation of IP addresses based on their historical activity. If an IP address is associated with malicious behavior or known bot activity (from threat intelligence feeds or historical data), the AI can block or challenge requests from that address.
- Geofencing: AI can also identify suspicious login attempts based on geographic patterns. Suppose an account is accessed from an unusual or unexpected location (especially far from the user’s typical location). In that case, the system may challenge the login attempt with additional verification, such as MFA or CAPTCHA, to block credential stuffing from foreign IP addresses.
Obfuscation Techniques
- Encryption: This converts plain text (readable data) into a coded version (ciphertext) that can only be decrypted back into the original data with the correct key. Encryption can protect passwords during transmission or storage. When a password is sent from a user to a server, encryption ensures that even if the data is intercepted, it remains unreadable to attackers.
- Hashing: This technique is a one-way cryptographic function that takes an input (e.g., a password) and generates a fixed-size string, typically represented in hexadecimal form. This output is called the hash and is unique to the input. Unlike encryption, hashing is one-way, meaning you cannot retrieve the original password from the hash. This is crucial because even if an attacker gains access to the hashed passwords, they cannot reverse the process of recovering the original passwords.
- Salting: This method adds a unique random value, a salt, to each password before hashing. Even if two users have the same password, their hashes will differ due to the unique salt. The salt is stored alongside the hash in the database and protects against rainbow table attacks, which use precomputed hashes for common passwords. By incorporating a random salt, even common passwords generate unique hashes, making it much harder for attackers to exploit.
Continuous Authentication
This advanced security method continuously verifies users’ identities throughout their session rather than just at the time of login. It is a powerful tool to prevent credential stuffing as it helps detect and prevent unauthorized access even after an attacker has successfully used stolen or leaked credentials.
Incident Response Planning
Mitigation and response planning are critical for organizations to prevent, mitigate, and recover from cyberattacks effectively. A well-structured incident response plan outlines a clear set of procedures and roles for responding to security incidents, helping organizations detect, contain, and recover from attacks efficiently.
Best Practices for Users
Users play a crucial role in safeguarding their accounts to stay protected from credential stuffing attacks. By following key best practices, individuals can significantly reduce the risk of compromised credentials being misused.
- Avoid and discourage password reuse across multiple sites or identities. This is one of the most effective practices to avoid credential stuffing attacks because it renders breached credential databases virtually useless.
- Use a Password Manager. A password manager securely stores passwords for all your accounts and helps generate unique, strong passwords. This way, you don’t have to remember each password, and you can ensure they’re unique and complex. Suggest enabling MFA wherever possible.
- Beware of Phishing Attempts. Many attacks start with phishing attempts. Users should be cautious of unsolicited emails or links asking them to log in to an account or update their password.
How Netwrix Can Help
Netwrix offers several products designed to help organizations defend against credential stuffing attacks:
Netwrix Threat Manager. This advanced threat detection software utilizes machine learning and user behavior analytics to identify and respond to suspicious activities in real-time, enabling rapid containment of potential threats.
Netwrix Threat Prevention. This tool leverages a comprehensive dictionary of over half a million known compromised passwords to help prevent the use of weak or stolen passwords, thereby reducing the risk of credential-based attacks.
Netwrix Password Policy Enforcer. This solution allows organizations to enforce strong, customizable password policies across Active Directory, mitigating the risk of credential stuffing, dictionary attacks, and other brute-force methods.
Netwrix Password Secure. Offering real-time alerts and comprehensive reporting, this tool enables organizations to identify and address password vulnerabilities proactively, enhancing overall password security.
Netwrix GroupID Password Management. Empowering users to reset their own passwords in Microsoft Entra ID (formerly Azure AD) and Active Directory, so they can get right back to work and IT teams can focus on more strategic tasks. For additional security, seamlessly require MFA or manager approval before allowing password resets.
Netwrix Enterprise Auditor for AD/EntraID. Pinpoint and remediate critical security threats like weak passwords or identify suspicious logon events that might have occurred.
Conclusion
Understanding and preventing credential stuffing is essential in safeguarding our digital lives. These attacks can compromise multiple accounts with a single set of stolen credentials, leading to severe consequences like identity theft, financial loss, and unauthorized access to personal information. Users must stay vigilant and proactive—by using unique passwords, enabling multi-factor authentication, and regularly updating their security practices, we can significantly reduce the risk of falling victim to such attacks. We encourage you to continue learning about the evolving cybersecurity threats and the steps you can take to protect yourself. Stay informed, stay secure, and take action to defend your online presence today!
FAQ
What is a credential stuffing attack?
Credential stuffing occurs when hackers use stolen username and password combinations, often obtained from previous data breaches, to gain unauthorized access to multiple user accounts across various websites or services. The key element here is the exploitation of reused credentials.
What is the best solution to credential stuffing?
The best solution to credential stuffing involves a multi-layered approach that combines technical defenses, user education, and ongoing monitoring. Here are the most effective strategies to prevent and mitigate credential stuffing attacks:
- Multi-Factor Authentication (MFA)
- Strong Password Policies
- Rate Limiting and Account Lockouts
- CAPTCHA and Bot Detection
- Continuous Authentication
- Device Fingerprinting and IP Blocklisting
- Monitoring and Real-Time Threat Detection
- User Education and Awareness
What is the difference between stuffing and password spraying?
Credential stuffing and password spraying are both types of brute force attacks aimed at compromising user accounts by attempting multiple login attempts with stolen or weak credentials. However, they differ in how the attacks are executed and the methods used by attackers.
In credential stuffing, attackers use large volumes of username-password pairs (often obtained from previous data breaches) and try them across many different websites or applications, relying on the user’s tendency to reuse the same password.
In password spraying, attackers try a small set of commonly used passwords (e.g., “123456,” “password,” “qwerty”) across a large number of usernames or accounts.
Is credential stuffing DDoS?
No, credential stuffing differs from a Distributed Denial-of-Service (DDoS) attack. However, they share some similarities, such as involving large-scale requests that may overwhelm systems.
What is the primary objective of credential stuffing?
The primary objective of credential stuffing is to gain unauthorized access to user accounts by exploiting stolen username and password combinations. Once an attacker gains access, they could take over the account, use it to collect sensitive information, gain access to finances, or perform privilege escalation as part of a larger attack chain.
What is password stuffing?
Password stuffing uses lists of common or previously leaked passwords to try against different usernames without necessarily relying on complete username-password pairs from a breach.
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