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Credential stuffing
Credential stuffing
Credential stuffing
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Credential stuffing is a type of cyberattack in which the attacker collects stolen account credentials, typically consisting of lists of usernames or email addresses and the corresponding passwords (often from a data breach), and then uses the credentials to gain unauthorized access to user accounts on other systems through large-scale automated login requests directed against a web application.[1] Unlike credential cracking, credential stuffing attacks do not attempt to use brute force or guess any passwords – the attacker simply automates the logins for a large number (thousands to millions) of previously discovered credential pairs using standard web automation tools such as Selenium, cURL, PhantomJS or tools designed specifically for these types of attacks, such as Sentry MBA, SNIPR, STORM, Blackbullet and Openbullet.[2][3][4]

Credential stuffing attacks are possible because many users reuse the same username/password combination across multiple sites, with one survey reporting that 81% of users have reused a password across two or more sites and 25% of users use the same passwords across a majority of their accounts.[5] In 2017, the FTC issued an advisory suggesting specific actions companies needed to take against credential stuffing, such as insisting on secure passwords and guarding against attacks.[6] According to former Google click fraud czar Shuman Ghosemajumder, credential stuffing attacks have up to a 2% login success rate, meaning that one million stolen credentials can take over 20,000 accounts.[7] Wired magazine described the best way to protect against credential stuffing is to use unique passwords on accounts, such as those generated automatically by a password manager, enable two-factor authentication, and to have companies detect and stop credential stuffing attacks.[8]

Credential spills

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A credential spill, alternatively referred to as a data breach or leak, arises when unauthorized individuals or groups illicitly obtain access to sensitive user credentials that organizations store. Such credentials frequently comprise usernames, email addresses, and passwords. The repercussions of credential spills can be significant, as they commonly subject users to a range of hazards, including identity theft, financial fraud, and unauthorized account infiltration.[9]

Credential stuffing attacks are considered among the top threats for web and mobile applications as a result of the volume of credential spills. More than three billion credentials were spilled through online data breaches in 2016 alone.[10]

Origin

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The term was coined by Sumit Agarwal, co-founder of Shape Security, who was serving as Deputy Assistant Secretary of Defense at the Pentagon at the time.[11]

Incidents

[edit]

On 20 August 2018, U.K. health and beauty retailer Superdrug was targeted with an attempted blackmail, with hackers showing purported evidence that they had penetrated the company's site and downloaded 20,000 users' records. The evidence was most likely obtained from hacks and spillages and then used as the source for credential stuffing attacks to glean information to create the bogus evidence.[12][13]

In October and November 2016, attackers gained access to a private GitHub repository used by Uber (Uber BV and Uber UK) developers, using employees' usernames and passwords that had been compromised in previous breaches. The hackers claimed to have hijacked 12 employees' user accounts using the credential-stuffing method, as email addresses and passwords had been reused on other platforms. Multi-factor authentication, though available, was not activated for the affected accounts. The hackers located credentials for the company's AWS datastore in the repository files, which they used to obtain access to the records of 32 million non-US users and 3.7 million non-US drivers, as well as other data contained in over 100 S3 buckets. The attackers alerted Uber, demanding payment of $100,000 to agree to delete the data. The company paid through a bug bounty program but did not disclose the incident to affected parties for more than a year. After the breach came to light, the company was fined £385,000 (reduced to £308,000) by the U.K. Information Commissioner's Office.[14]

In 2019 Cybersecurity research firm Knight Lion Security claimed in a report that credential stuffing was favored attack method for GnosticPlayers.[15]

Compromised credential checking

[edit]

Compromised credential checking is a technique enabling users to be notified when passwords are breached by websites, web browsers or password extensions.

In February 2018, British computer scientist Junade Ali created a communication protocol (using k-anonymity and cryptographic hashing) to anonymously verify whether a password was leaked without fully disclosing the searched password.[16][17] This protocol was implemented as a public API and is now consumed by multiple websites and services, including password managers[18][19] and browser extensions.[20][21] This approach was later replicated by Google's Password Checkup feature.[22][23][24] Ali worked with academics at Cornell University to develop new versions of the protocol known as Frequency Smoothing Bucketization (FSB) and Identifier-Based Bucketization (IDB).[25] In March 2020, cryptographic padding was added to the protocol.[26]

Compromised credential checking implementations

[edit]
Protocol Developers Made Public References
k-Anonymity Junade Ali (Cloudflare), Troy Hunt (Have I Been Pwned?) 21 February 2018 [27][28]
Frequency Smoothing Bucketization & Identifier Based Bucketization Cornell University (Lucy Li, Bijeeta Pal, Rahul Chatterjee, Thomas Ristenpart), Cloudflare (Junade Ali, Nick Sullivan) May 2019 [29]
Google Password Checkup (GPC) Google, Stanford University August 2019 [30][31]
Active Credential Stuffing Detection University of North Carolina at Chapel Hill (Ke Coby Wang, Michael K. Reiter) December 2019 [32]
[edit]

23andMe

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In October 2023, 23andMe disclosed that attackers had gained unauthorized access to user accounts through a credential stuffing attack that exploited reused passwords from prior breaches on other platforms. The incident exposed profile data of approximately 6.9 million users, including information on genetic heritage, family connections, and in some cases health-related details.[33][34]

The company later faced multiple class-action lawsuits in the United States, culminating in a proposed US$30 million settlement in 2024.[35] In addition, the UK Information Commissioner’s Office (ICO) fined 23andMe £2.31 million for failing to adequately protect personal data of around 155,000 UK customers.[36]

Dunkin' Donuts

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In September 2020, Dunkin' Brands Group, Inc. reached a settlement with the New York Attorney General over credential stuffing attacks that had compromised tens of thousands of customer DD Perks loyalty accounts between 2015 and 2018. Attackers used reused credentials from other breaches to gain unauthorized access, which in some cases allowed fraudulent use of stored value cards.[37]

Under the terms of the settlement, Dunkin' was required to notify impacted customers, reset affected passwords, provide refunds for unauthorized transactions, and enhance its information security program. The company also agreed to pay $650,000 USD in penalties and costs to New York (state), without admitting wrongdoing.[38][39]

See also

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References

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[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Credential stuffing

View on Grokipedia
from Grokipedia
Credential stuffing is a type of in which attackers use automated tools to inject stolen username and pairs into the forms of websites and online services, attempting to gain unauthorized access to user accounts by exploiting reuse across multiple platforms. This method relies on credentials obtained from prior breaches, where hackers acquire large lists of compromised details from the or other illicit sources and deploy bots to test them at scale against unrelated targets. Unlike brute-force attacks that guess , credential stuffing succeeds because many users reuse the same credentials across different services, with studies showing that up to 51% of are reused across accounts. The attack process typically begins with the collection of credential "combo lists," such as the "Collection #1-5" datasets containing over 2.2 billion unique username-password combinations, which are then automated via scripts and proxy networks to mimic legitimate user traffic and evade detection. Success rates, though low at around 0.1% per credential tested, can still result in significant account takeovers due to the volume of attempts, with credential stuffing accounting for a of 19% of daily requests across monitored environments and up to 44% on peak days. In 2025, compromised credentials served as the initial access vector in 22% of analyzed data breaches, highlighting its role as a persistent fueled by rising infostealer infections, which increased by 84% in 2024 compared to the previous year. The impacts of credential stuffing extend beyond individual account compromises, enabling broader risks such as , financial fraud, and further propagation of or campaigns from hijacked accounts. For organizations, these attacks contribute to severe data breaches, with an of $4.88 million per incident in 2024, driven by factors like lost business and regulatory fines. In sectors like , gaming, and , attackers exploit these vulnerabilities to steal personally identifiable information, details, and other sensitive data, underscoring the need for robust defenses.

Definition and Mechanism

Core Concept

Credential stuffing is an automated in which attackers inject stolen username and pairs into forms on legitimate websites to gain unauthorized access to user accounts. This method exploits credentials previously compromised in data breaches on unrelated sites, relying on users' common practice of reusing across multiple platforms. Attackers typically deploy bots to perform these attempts at high volumes, often millions per day, making the process efficient and low-effort despite low individual success rates. Key characteristics of credential stuffing include its dependence on real, valid credential pairs sourced from external leaks, which differentiates it from guesswork-based methods. It targets the widespread issue of reuse, where a single breached set of credentials can unlock accounts on numerous services. These attacks are bot-driven and scalable, allowing perpetrators to test vast lists of credentials against targeted sites without manual intervention. Unlike brute-force attacks, which involve guessing passwords through repeated trials of random or common combinations, credential stuffing uses pre-obtained, legitimate credentials to bypass with higher efficiency. It also contrasts with , which deceives users into voluntarily revealing credentials, as stuffing directly automates unauthorized logins without user interaction. On a large scale, credential stuffing can result in the of millions of accounts worldwide, as evidenced by the circulation of billions of stolen credentials and over 300 billion attack attempts recorded globally in 2024. Successful breaches often lead to account takeovers, enabling financial through unauthorized transactions and broader by accessing .

Attack Process

Credential stuffing attacks commence with a preparation phase where attackers acquire large lists of compromised username-password pairs, typically sourced from data breaches or credential spills. These lists increasingly include credentials harvested by infostealer malware, which saw an 84% rise in infections in 2024 compared to 2023. These lists, which can contain billions of entries, are then cleaned and formatted by removing duplicates, standardizing formats, and organizing data for efficient automation. The execution phase follows a structured sequence of steps to maximize success while minimizing detection. First, attackers configure proxy networks and botnets to distribute login requests across numerous IP addresses, thereby evading IP-based blocking mechanisms. Second, they automate the submission of credentials into forms using scripts or browser automation tools, enabling high-volume attempts across multiple target websites simultaneously. Third, to circumvent and behavioral detection, attackers implement IP rotation, introduce randomized delays between requests, and vary user-agent strings to imitate legitimate human browsing patterns. Throughout the attack, success is gauged by monitoring server responses for indicators of valid logins, such as successful redirects or session token issuance. Upon confirmation, attackers capture these tokens to maintain access and may probe for weaknesses in secondary protections like two-factor . Commonly employed tools include open-source frameworks such as Hydra for scripting login attempts and commercial bot kits like Sentry MBA or for scaled, sophisticated operations.

Historical Development

Origins

Credential stuffing began to emerge in the late and early as data breaches became more frequent and underground markets on the began facilitating the trade of stolen credentials. Early cybercrime forums and markets, such as those experimenting with and data sales in the , provided the infrastructure for attackers to acquire and monetize compromised username-password pairs. This period coincided with the growth of anonymous networks like Tor, released in 2002, which enabled hidden services for illicit data exchanges. The attack technique gained initial recognition around 2010-2011, following major breaches like the 2009 incident that exposed 32 million passwords, analyzed by security firm to highlight risks of credential reuse. 's report underscored how such dumps could fuel automated login attempts across sites. The term "credential stuffing" was coined in 2011 by Sumit Agarwal, then Deputy Assistant Secretary of Defense at the U.S. Department of Defense, who observed surges in brute-force attacks on military sites using credentials from unrelated breaches. Key influencing factors included the proliferation of vulnerabilities, a top web since the early that enabled mass credential extractions, and widespread user habits of password reuse across accounts, as evidenced by 's findings that over 50% of breached passwords appeared in multiple lists. Credential spills from these breaches served as early enablers, providing attackers with authentic data to test. Initially described as variants of account takeover attacks, credential stuffing was distinguished from traditional brute-force methods by its reliance on real stolen rather than random or dictionary-based guessing. Precursors traced to 1990s-2000s spam and dictionary bots, which automated trials but lacked the efficiency of breached lists. The term gained wider adoption in cybersecurity reports by the mid-2010s, with firms like Akamai highlighting its scale in analyses of automated threats.

Evolution Over Time

Credential stuffing attacks experienced substantial growth throughout the 2010s, particularly following high-profile data breaches that flooded underground markets with stolen credentials. The 2012 breach, which exposed over 117 million email addresses and hashed passwords, and the 2013-2014 Yahoo breaches affecting more than 3 billion accounts, provided attackers with vast datasets to fuel automated login attempts across multiple platforms. This surge marked a shift from isolated incidents to widespread exploitation, with annual credential spill incidents nearly doubling between 2016 and 2020 according to F5 Labs analysis. Attackers increasingly integrated these credentials with botnets to achieve massive scale, enabling campaigns that launched millions of login attempts per hour; for instance, Akamai documented a single facing over 55 million malicious attempts in one operation. By the end of the decade, global credential stuffing attacks reached 193 billion in 2020 alone, transforming the technique from rudimentary scripts into a core component of operations. In the , credential stuffing evolved toward greater sophistication and targeting of high-value sectors, driven by advancements in and regulatory changes. Attackers adopted algorithms to enhance evasion tactics, such as adaptive timing that mimics by spacing attempts over hours or days to avoid rate-limiting detection. This led to a rise in targeted campaigns against financial institutions like banks, where credential stuffing emerged as a leading due to the monetary incentives of account takeovers. Regulations such as the EU's GDPR, implemented in 2018, amplified visibility by mandating breach reporting, which in turn highlighted the prevalence of credential stuffing and prompted increased scrutiny from authorities like the UK's . Web attack volumes, including credential stuffing, rose 65% from early 2023 to late 2024, with enduring over 79 billion incidents in that period. Statistical trends underscore the transition from sporadic, opportunistic attacks to structured, organized models resembling crime-as-a-service (CaaS). By 2023, F5 Labs reported that credential stuffing accounted for an average of 19.4% of unmitigated across sectors, escalating to over 80% during attack spikes in areas like SaaS platforms. This professionalization is evident in ecosystems where tools, credential lists, and botnets are commoditized on marketplaces, enabling even low-skill actors to participate. Attacker sophistication further advanced through the adoption of cloud-based infrastructures and residential proxies, providing resilience against IP blocking and distributing attempts across global networks to sustain prolonged campaigns. These developments have solidified credential stuffing as a persistent, high-impact in the cybersecurity landscape.

Data Sources for Attacks

Credential Spills

Credential spills are large-scale leaks of username-password pairs originating from data breaches, where sensitive information is exposed and disseminated, either accidentally or maliciously. These incidents typically involve the unauthorized release of from compromised systems, providing attackers with raw material for subsequent cyber threats. Common causes of credential spills include hacking exploits, insider threats, and misconfigurations such as unencrypted database storage or inadequate access controls. For instance, vulnerabilities in database systems often lead to exposures of vast troves of user data when security protocols fail to protect stored . As of 2025, breaches have collectively exposed over 17 billion accounts containing usernames and passwords since tracking began, underscoring the escalating scale of these events. Once leaked, these credentials gain accessibility through distribution on forums, where they are sold or shared among cybercriminals as foundational resources for attacks. Attackers frequently employ de-hashing techniques, including rainbow tables, dictionary attacks, and brute-force methods, to reverse-engineer hashed passwords into form, particularly when weak hashing algorithms like are used. The critical role of credential spills in enabling stuffing attacks stems from widespread password reuse practices, with studies indicating that 50-70% of users recycle the same passwords across multiple online services. This behavioral pattern amplifies the value of spilled credentials, as a single compromised pair can unlock accounts on unrelated platforms without requiring additional breaches.

Underground Markets

Underground markets for stolen credentials form a vital component of the ecosystem, enabling the commercialization and distribution of data harvested primarily from credential spills. These markets operate across platforms, Telegram channels, and specialized forums, where actors buy, sell, and exchange vast quantities of compromised usernames, passwords, and associated personal information. Prominent examples include the Russian Market, a dedicated hub for credential logs, and Telegram channels that facilitate rapid, encrypted trading of stealer logs containing millions of records. Historically, open forums like served as central marketplaces until its shutdown by law enforcement in 2022, after which successors such as emerged but faced repeated disruptions, including takedowns in 2023, 2024, and 2025. Services in these markets extend beyond simple sales to include bundled packages of credentials paired with exploitation tools, such as automated scripts, and "checking services" that verify the validity of stolen before purchase. Checking services employ specialized software to test credentials against target websites, filtering out invalid pairs and increasing their value for buyers; for instance, account checkers for platforms like or confirm live access, often at an additional fee. Pricing varies by freshness, quality, and target service, with bulk credential lists typically sold for $1 to $10 per 1,000 entries, while premium logs from recent infostealer campaigns command higher rates, such as $10 per individual log file containing multiple credentials. The evolution of these markets reflects adaptations to intensified pressure, with a marked shift toward invite-only access and private networks following major takedowns between 2021 and 2025, including the seizures of in 2022 and multiple iterations. This has led to more fragmented, resilient operations, including deeper integration with groups that supply fresh credential spills from victim networks and use markets to monetize access brokers' services. Post-takedown, Telegram has surged in popularity for its anonymity and ease, hosting channels that repost and resell aggregated data from sources. Predominantly operated by Russian and Chinese cybercriminals, these markets exhibit a global reach but with concentrated activity in and , where linguistic barriers and jurisdictional challenges hinder enforcement. By 2024, an estimated 15 to 17 billion stolen credentials were circulating across these platforms, underscoring the scale of the threat and the ongoing challenge of disrupting supply chains fueled by infostealer and breaches.

Notable Incidents

Key Historical Cases

One of the early prominent examples of credential stuffing occurred in 2014 against , where attackers leveraged credentials from the 2012 breach to attempt unauthorized access to user accounts. The assault involved automated login attempts using stolen username-password pairs, resulting in approximately 7 million probes against accounts over several days. 's security measures, including and , blocked the majority of these attempts, preventing widespread compromise, though a small number of accounts were accessed due to password reuse. In response, accelerated the rollout of two-factor authentication (2FA) and notified affected users to change their passwords, marking a significant push toward enhanced account protection practices. In 2016, faced credential stuffing attacks fueled by the massive Yahoo data breach earlier that year, which exposed for over 500 million accounts. Attackers used these leaked pairs to target logins, affecting thousands of users and enabling unauthorized access to profiles for activities like spam dissemination. The incident highlighted the ripple effects of large-scale spills, prompting to initiate widespread password reset campaigns and strengthen login monitoring to mitigate further risks. This case underscored the vulnerability of platforms to cross-site reuse, with success rates for such attacks estimated at 0.1% to 2% of attempted logins. In 2011, Sony Pictures Entertainment suffered a major breach where attackers used credentials stolen from a prior breach to access accounts. Approximately two-thirds of the affected users had reused passwords from the incident, leading to widespread account takeovers. This event amplified damage across services and highlighted the dangers of password reuse, prompting to enhance security measures including . Another key case was the 2014 JPMorgan Chase breach, where attackers used stolen credentials from a third-party site to target bank accounts via credential stuffing. The attack compromised contact information for 76 million households and 7 million small businesses, though core financial data remained secure due to additional protections. It resulted in regulatory scrutiny and accelerated adoption of advanced authentication in the financial sector. These historical cases commonly resulted in account compromises that facilitated spam campaigns, financial fraud, and , with average annual costs to affected businesses reaching $6 million excluding fraud-related expenses (as reported in 2020). Regulatory bodies like the (FTC) investigated such incidents, emphasizing failures in security practices and pushing for better consumer protections through enforcement actions.

Recent Examples

In April 2021, a significant data exposure affected 533 million users across 106 countries, leaking personal details such as phone numbers, full names, addresses, and locations from a exploited in 2019. This spill, posted on a hacking forum, increased risks of , targeted social engineering, and by providing attackers with detailed user profiles, though it did not include passwords for direct credential stuffing. The incident sparked widespread concerns and prompted multiple class-action lawsuits against Meta, highlighting the long-term dangers of unpatched vulnerabilities in large-scale services. The 2023 cyberattack on involved social engineering tactics, where the threat group used vishing () to obtain initial employee credentials for the identity platform before deploying and attempting broader system compromises. This approach disrupted operations at MGM properties for nearly two weeks, leading to canceled shows, halted bookings, and estimated financial losses exceeding $100 million in recovery and lost revenue. The breach underscored how credentials obtained via social engineering can fuel campaigns, affecting both corporate and customer accounts. From 2024 to 2025, credential stuffing attacks increasingly targeted exchanges, with a June 2025 leak exposing 16 billion login credentials linked to platforms like wallets and trading services, including probes against major exchanges such as . These incidents, often enabled by underground markets trading combo lists, resulted in heightened scrutiny and user advisories for enhanced security measures like two-factor authentication. Concurrently, the rise of AI-assisted targeting has transformed attacks, with AI agents automating credential testing at scale to evade detection and adapt to defenses in real-time. Broader impacts of these recent campaigns include a growing emphasis on vulnerabilities, where third-party spills propagate stuffing risks across ecosystems, projected to affect 45% of organizations by 2025. Reports indicate success rates of 0.2-2% in targeted campaigns leveraging high-quality leaked , contributing to account takeovers in 31% of overall breaches during this period. Such trends have driven regulatory pushes for stronger monitoring and adoption to curb the escalating scale of automated threats.

Detection and Mitigation

Compromised Credential Checking

Compromised credential checking is a proactive measure that involves scanning user-submitted or stored credentials against databases of known compromised from past breaches to identify potential vulnerabilities to credential stuffing attacks. This process allows organizations to detect if a username-password pair matches entries in breach compilations, enabling early intervention to protect accounts. The primary purpose of compromised checking is to pinpoint at-risk accounts either prior to attempts or in real time during logins, thereby blocking access attempts that utilize stolen pairs and mitigating the risk of unauthorized account takeovers. By integrating these checks into workflows, services can proactively notify users of exposed or enforce password changes, reducing the overall exposure to reuse across platforms. These databases are typically sourced from spills documented in major data breaches. Core methods for compromised checking rely on hash-based matching to compare credentials securely without transmitting data. For instance, protocols using enable clients to query breach databases by sending only a truncated portion of a hashed (e.g., the first 5 characters of a hash), retrieving a set of matching hashes for local verification while obscuring the exact input. Services like facilitate this through APIs that support such anonymized lookups. Checks can occur in real-time, evaluating each attempt against the database, or in batch mode, periodically scanning stored user credentials to flag and remediate issues. These approaches offer substantial benefits, including a reported reduction in credential stuffing and related attack success rates by up to 94% through enhanced detection of leaked or similar passwords. However, they also present limitations, particularly privacy concerns arising from the need to handle hashed credentials, which could potentially be deanonymized or exploited if not implemented with robust protections like . To address these, privacy-preserving protocols emphasize client-side processing and minimal data exposure during queries.

Implementation Approaches

Compromised credential checking can be integrated into authentication systems through API calls to external services during user registration or login processes. For instance, services like (HIBP) provide a free that allows developers to hash a user's password client-side using and query only the first five characters of the hash (prefix) to retrieve a list of matching suffixes, enabling a privacy-preserving check without transmitting the full credential. This model ensures that the service cannot link the query to the exact password, reducing privacy risks while confirming if the credential appears in known breaches. Large enterprises often opt for on-premises databases to maintain control over breach data and avoid reliance on external APIs. Solutions such as Microsoft's Entra Password Protection enable deployment of custom banned lists, including breached credentials, on local servers, allowing real-time checks during changes without dependency. Similarly, Intercede's Breach Database offers an on-premises repository of over 10 billion compromised credentials, integrated into enterprise identity systems for offline validation. Technical implementation requires secure hashing to query breach databases effectively, typically using for compatibility with common breach formats, though or other algorithms may be applied if the target breach data includes salted hashes. False positives can arise when querying salted or variably hashed breaches, necessitating fallback mechanisms like user notifications for resets rather than outright denials, and prioritizing checks against unsalted plain-text dumps which constitute the majority of credential stuffing sources. Notable examples include Google's Password Checkup, launched in 2019 as a browser extension that uses a similar prefix-based protocol to alert users to compromised credentials across sites, protecting over 650,000 users within 20 days by scanning against Google's breach database. Open-source tools like the Pwned Passwords API facilitate easy integration into applications, with libraries available in multiple languages for developers to embed checks without building from scratch. Deployment faces challenges in scalability for high-traffic sites, where frequent queries could introduce latency; involves local caching of hash ranges or hybrid on-premises setups to handle peak loads without service disruptions. Compliance with data protection regulations, such as GDPR, demands strict avoidance of plain-text storage, relying instead on ephemeral, hashed queries to prevent retention of sensitive and ensure auditability.

Prevention Strategies

Technical Defenses

Technical defenses against credential stuffing primarily involve implementing barriers that detect and disrupt automated, high-volume login attempts using stolen credentials. is a foundational technique that throttles the number of requests from a single , device, or user account within a defined timeframe, effectively slowing or blocking bot-driven attacks that attempt thousands of logins per minute. For instance, services like recommend configuring rate limits on login endpoints to trigger challenges, such as CAPTCHAs, after a threshold of failed attempts, which has been shown to mitigate the scale of credential stuffing by increasing the time and resources required for attackers. Complementing this, IP monitoring uses threat intelligence feeds to identify and block traffic from known malicious IPs, proxies, or regions associated with abuse, often through graduated responses like temporary bans or geofencing for location-specific applications. Behavioral analysis enhances these measures by examining patterns such as rapid request bursts or unnatural timing, assigning risk scores to flag potential bot activity before it overwhelms the system. Multi-factor authentication (MFA) adds a critical layer of protection by requiring a second verification factor—such as , hardware tokens, or one-time codes—beyond just the username and password, rendering stolen credentials insufficient for access. According to , MFA blocks over 99.9% of account compromise attempts, including credential stuffing, by verifying user identity through additional signals that automated tools cannot easily replicate. Device fingerprinting further strengthens MFA by collecting unique attributes like browser type, screen resolution, installed plugins, and HTTP headers to create a device profile; mismatches during login, such as attempts from unfamiliar devices, can trigger step-up authentication or blocks. This approach, detailed in guidelines, helps detect anomalies in credential stuffing campaigns where attackers use distributed proxies to simulate legitimate traffic. Web application firewalls (WAFs) serve as a frontline defense by inspecting incoming HTTP traffic and applying rules to filter out automated patterns indicative of credential stuffing, such as repetitive requests to login pages from non-human sources. Modern WAFs, like those from , incorporate models to classify traffic in real-time, learning from baseline behaviors to distinguish legitimate users from bots based on factors like request velocity and payload anomalies, thereby reducing false positives while blocking malicious attempts. These systems can integrate with broader security stacks to enforce policies that challenge or deny suspicious sessions, providing scalable protection for high-traffic s. Emerging technologies shift away from credential dependency altogether, with zero-trust models enforcing continuous verification of every access request regardless of origin, using contextual signals like device health and user behavior to deny unauthorized logins. , exemplified by FIDO2 standards, replaces passwords with where authenticators generate unique keys per service, stored securely on devices and resistant to phishing or reuse in stuffing attacks. The highlights that such passkeys inherently prevent credential stuffing by eliminating shareable secrets, promoting adoption in zero-trust architectures for enhanced security without user friction. Complementary to these, compromised credential checking tools can proactively scan for breached passwords during registration or resets, though they work best alongside the above defenses.

User and Organizational Practices

Users are advised to employ unique passwords for each online account to mitigate the risks associated with credential reuse, a primary enabler of credential stuffing attacks. Enabling (MFA) wherever available adds a critical layer of protection, as it requires additional verification beyond stolen credentials. Regularly monitoring personal accounts through services like (HIBP) allows individuals to detect if their email addresses or passwords have appeared in data breaches, enabling timely password changes. Organizations should implement policies mandating the use of password managers to facilitate the creation and storage of strong, unique credentials across accounts, reducing the likelihood of reuse. Conducting regular security audits helps identify vulnerabilities in systems and ensures compliance with evolving threat landscapes. Developing and maintaining incident response plans specifically tailored to credential stuffing incidents is essential, outlining steps for detection, containment, user notification, and recovery to minimize damage from successful attacks. Education campaigns play a vital role in raising awareness about credential stuffing by informing users on the importance of responding promptly to breach notifications and changing affected passwords. These initiatives also promote the adoption of passkeys as a passwordless alternative, which use to bind credentials to specific domains, thereby preventing their reuse in stuffing attempts. Studies demonstrate the effectiveness of these practices; for instance, MFA adoption can reduce the risk of account compromise, including from credential stuffing, by up to 99.9%. Such measures align with NIST guidelines, which emphasize MFA and secure credential management as key components for compliance in frameworks.

References

  1. https://owasp.org/www-community/attacks/Credential_stuffing
  2. https://www.imperva.com/learn/application-security/credential-stuffing/
  3. https://www.verizon.com/business/resources/articles/credential-stuffing-attacks-2025-dbir-research/
  4. https://www.ibm.com/thought-leadership/institute-business-value/en-us/report/2025-threat-intelligence-index
  5. https://www.humansecurity.com/learn/blog/credential-stuffing-and-account-takeover-attacks-remain-nagging-business-problems/
  6. https://www.nsa.gov/Press-Room/News-Highlights/Article/Article/1719167/cybersecurity-what-is-credential-stuffing/
  7. https://www.akamai.com/site/en/documents/state-of-the-internet/soti-security-web-attacks-and-gaming-abuse-report-2019.pdf
  8. https://www.cloudflare.com/learning/bots/what-is-credential-stuffing/
  9. https://www.akamai.com/glossary/what-is-credential-stuffing
  10. https://www.akamai.com/blog/trends/keeping-up-with-the-botnets
  11. https://www.akamai.com/site/en/documents/state-of-the-internet/2024/securing-apps-report.pdf
  12. https://www.kaspersky.com/blog/what-is-credential-stuffing/51199/
  13. https://www.akamai.com/site/en/documents/white-paper/2021/credential-stuffing-how-to-keep-criminals-from-impacting-your-customers.pdf
  14. https://www.identityiq.com/articles/the-origins-and-history-of-the-dark-web
  15. https://www.imperva.com/company/press_releases/imperva-releases-detailed-analysis-of-32-million-breached-consumer-passwords/
  16. https://portswigger.net/daily-swig/credential-stuffing-attacks-how-to-protect-your-accounts-from-being-compromised
  17. https://www.f5.com/company/blog/data-privacy-requires-protection-against-credential-stuffing
  18. https://www.proofpoint.com/us/threat-reference/credential-stuffing
  19. https://www.akamai.com/newsroom/press-release/akamai-credential-stuffing-report-shows-financial-services-industry-under-constant-attack-from-automated-account-takeover-tools
  20. https://krebsonsecurity.com/2016/05/as-scope-of-2012-breach-expands-linkedin-to-again-reset-passwords-for-some-users/
  21. https://www.cnet.com/news/privacy/yahoo-500-million-accounts-hacked-data-breach/
  22. https://www.reuters.com/article/technology/yahoo-says-all-three-billion-accounts-hacked-in-2013-data-theft-idUSKCN1C82NV/
  23. https://www.f5.com/labs/articles/2021-credential-stuffing-report
  24. https://blog.castle.io/credential-stuffing-attacks-anatomy-detection-and-defense/
  25. https://www.akamai.com/content/dam/site/en/documents/state-of-the-internet/2025/akamai-web-application-attacks-and-api-attacks-report.pdf
  26. https://www.gtlaw-dataprivacydish.com/2021/02/do-credential-stuffing-attacks-need-to-be-reported-under-the-gdpr/
  27. https://www.simmons-simmons.com/en/publications/cl57pxkk911480a26o4ljjjex/ico-issues-a-warning-on-credential-stuffing-attacks
  28. https://www.f5.com/labs/articles/2023-identity-threat-report-executive-summary
  29. https://www.paloaltonetworks.com/cyberpedia/credential-stuffing
  30. https://www.kasada.io/exposing-the-credential-stuffing-ecosystem/
  31. https://www.cequence.ai/blog/bot-management/credential-stuffing-attack-residential-proxy-bulletin-lacking-in-detail/
  32. https://www.ic3.gov/CSA/2022/220818.pdf
  33. https://www.enzoic.com/blog/what-is-credential-stuffing/
  34. https://haveibeenpwned.com/PwnedWebsites
  35. https://www.mimecast.com/content/password-cracking/
  36. https://www.enzoic.com/blog/8-stats-on-password-reuse/
  37. https://www.recordedfuture.com/blog/credential-markets-dark-web
  38. https://krebsonsecurity.com/2022/03/justice-dept-seizes-raidforums-hacking-site/
  39. https://www.trustwave.com/en-us/resources/blogs/trustwave-blog/how-prices-are-set-on-the-dark-web-exploring-the-economics-of-cybercrime/
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  41. https://blog.dropbox.com/topics/company/dropbox-wasnt-hacked
  42. https://thehackernews.com/2014/10/nearly-7-million-dropbox-account.html
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  45. https://news.bloomberglaw.com/tech-and-telecom-law/cybersecurity-enforcers-wake-up-to-unauthorized-computer-access-via-credential-stuffing
  46. https://www.npr.org/2021/04/09/986005820/after-data-breach-exposes-530-million-facebook-says-it-will-not-notify-users
  47. https://www.cnn.com/2021/04/06/tech/facebook-data-leaked-what-to-do
  48. https://www.strongdm.com/what-is/facebook-data-breach
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  50. https://netwrix.com/en/resources/blog/mgm-cyber-attack
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  53. https://www.binance.com/en/square/post/21479679034025
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