Credential Stuffing Attacks: What are they and how to prevent them?

What Is Credential Stuffing?

Credential stuffing is a massive-scale account takeover. Attackers start with a “combo list” of usernames and passwords stolen in a single breach or phishing attack, then automate logins across multiple other sites. Because people often reuse credentials, the same pair that opened one door may open dozens more.

For example, in August 2020, attackers used credential stuffing against Canada’s federal login systems. They obtained username–password pairs from past breaches and attempted to use them on the GCKey and Canada Revenue Agency (CRA) portals.

Officials reported that 9,041 GCKey accounts had their credentials reused, and approximately 5,500 CRA accounts were targeted; affected logins were disabled while the government investigated. It’s a textbook case of password reuse turning one breach into many.

The process is mechanical mainly: scripts or bots submit those pairs to login forms, rotate through proxies to evade rate limits, and maintain the traffic’s appearance as routine. Every successful hit becomes an account compromise, such as an email, retail, or banking account, without ever cracking a password; it’s simply a matter of reusing the same credentials.

How Does Credential Stuffing Work?

Here’s how credential stuffing works:

1. Gather. The attacker collects username-password pairs from breaches, phishing kits, or public “combo” dumps.
2. Spray. Bots fire those pairs at login pages across various sites, including social platforms, shops, and SaaS apps, often using rotating proxies to appear routine.
3. Catch. Any pair that logs in is flagged as “valid.”
4. Exploit. With access in hand, the attacker can:

• Empty stored balances or place orders
• Lift sensitive data: cards, messages, photos, docs
• Use the account to send spam or phishing from a trusted sender
• Sell the verified credentials to other criminals for reuse

Real-World Examples Of Credential Stuffing Attacks

Here are some real-world examples of credential stuffing attacks:

1. Dunkin’ Donuts

Dunkin’ Donuts disclosed a credential-stuffing incident in which attackers used username-password pairs stolen from other breaches to break into DD Perks rewards accounts.

It’s the company’s second notice within a three-month period. The first was reported at the end of November (the intrusion occurred on October 31), and the latest was reported today for an attack on January 10.

Attackers reused valid credentials, and intruders didn’t crack passwords; they simply logged in. Exposed account data can include a customer’s first and last name, the email address used as the username, a 16-digit DD Perks account number, and the DD Perks QR code.

The program allows customers to earn points for free drinks or discounts, making compromised accounts more attractive for fraud. Dunkin’ says the affected logins were targeted because the same credentials had appeared in other breaches. This is a reminder to stop reusing passwords and enable stronger sign-in protections wherever possible.

2. Ticketfly

In May 2018, Ticketfly was hit by a cyberattack that forced the company to take its services offline. The attacker defaced the homepage with an image from V for Vendetta and a taunt: “Your Security Down, I’m Not Sorry. Next time I will publish the database ‘backstage.’”

The hacker claimed they had warned Ticketfly about a website vulnerability and asked for a ransom of 1 bitcoin to fix it. When the demand wasn’t met, the threat turned into exposure. More than 26 million email addresses were leaked to a public server, along with customers’ names, phone numbers, and physical addresses.

A single reported flaw escalated into a full-scale breach and a highly publicized outage. It’s proof that one weak point can take a platform dark and put customer data at risk.

3. Spotify

In 2020, Spotify experienced a massive credential-stuffing attack that affected millions of accounts. Attackers didn’t “crack” passwords; they reused them.

They took username-password pairs leaked from earlier breaches on other sites and fired them at Spotify logins using automated tools and bots. Because many people recycle the same credentials across services, a pair that worked elsewhere often worked here too.

Once a match was established, the account was vulnerable to takeover. This was one of many credential-stuffing campaigns that year, and it exploited a familiar weakness: password reuse.

The lesson is simple yet stubborn: if one site leaks, every other account using the same combination is suddenly at risk. Unique passwords (or, better yet, passkeys) and multi-factor authentication shut down this kind of attack before it starts.

What’s the Difference Between Credential Stuffing and Brute Force Attacks?

The main difference between them is that credential stuffing reuses known username–password pairs from other breaches. The attacker bets on password reuse. On the other hand, brute force attacks attempt to guess new passwords for a target account or domain. The attacker bets on weak/guessable passwords.

How to Prevent Credential Stuffing

There are several steps that individuals and organizations can take to prevent credential-stuffing attacks:

1. Multi-Factor Authentication (MFA)

Credential stuffing lives on reused passwords. MFA stops it by adding something you have to something you know. A stolen password won’t log in without a phone prompt, hardware key, or approved device. If turning on MFA for everyone isn’t realistic, trigger it when risk is high and pair it with device fingerprinting.

How to do it (clear steps)

• Pick strong factors first. Prefer passkeys/WebAuthn or hardware security keys; use authenticator apps (TOTP) over SMS for two-factor authentication.
• Roll out by risk. Start with admins, finance, and high-value customer tiers; then expand.
• Go adaptive. Require MFA on new devices, unfamiliar IP addresses/ASNs, for impossible travel, or high login velocity.
• Use device fingerprinting. “Remember” trusted devices; step up MFA when the fingerprint or cookie changes.
• Protect sensitive actions. Step-up MFA for payouts, password/email changes, and API key creation.
• Harden recovery. Offer backup codes or verified email/phone recovery with cooldowns and alerts.
• Limit abuse. Rate-limit MFA attempts per account/device/IP; block known bad networks and automate lockouts.
• Monitor & tune. Track prompts, failures, and bypasses. Reduce fatigue and adjust rules where users struggle.

2. Stronger Password Policies

Stronger passwords reduce both guessing attacks and the fallout from reused credentials. Length and uniqueness do most of the heavy lifting, supported by sensible checks and safe storage.

How to do it

• Require at least 14 to 16 characters and allow long secrets up to 64
• Encourage passphrases with spaces so users can remember them without shortcuts
• Check new passwords against breached and weak lists and block common patterns
• Provide a strength meter, such as zxcvbn, and give live guidance that improves choices
• Prevent reuse of recent passwords and flag reuse across internal systems where possible
• Avoid forced frequent resets and rotate only after compromise or role change
• Support password managers and allow pasting in login and signup fields
• Store passwords with Argon2id using per-user salt and tuned parameters
• Throttle guessing with progressive delays or temporary lockouts, and use IP and device reputation
• Secure recovery with multifactor prompts, cooldowns, and user alert,s and drop weak security questions

3. Device Fingerprinting

Device fingerprinting helps spot automated logins by creating a stable ID for each session. JavaScript and server headers collect signals such as operating system, browser, version, language, time zone, screen size, user agent, and network traits.

When the same fingerprint attempts multiple logins or hops across accounts in quick succession, it indicates brute force or credential stuffing.

How to do it

• Decide which signals to collect, prioritizing low-variance traits such as OS, browser family and version, language, time zone, screen size, user agent, and ASN.
• Collect signals in the browser with JavaScript and enrich on the server with headers and IP metadata.
• Normalize values so minor changes do not create a brand-new fingerprint and handle missing fields gracefully
• Hash the concatenated signals with a server-side salt and avoid storing raw identifiers
• Set a lifespan for each fingerprint and refresh it when stable attributes change slowly over time
• Track login attempts per account and per fingerprint, and flag rapid retries or many accounts touched by one fingerprint
• Trigger step-up checks, such as MFA or CAPTCH,A when risk rise,s and throttle or block when thresholds are crossed
• Score similarity so minor variations still map to the same devic,e and use thresholds to control false positives

4. Use a CAPTCHA

CAPTCHA helps distinguish humans from bots by requiring a small proof of interaction. It can slow credential stuffing and scripted logins, but it is not a silver bullet. Attackers can route traffic through headless browsers, farms, or solver services.

Treat CAPTCHA as one layer in a broader defense and trigger it only when risk is high to keep friction low.

How to do it

• Deploy modern challenges with server-side verification and per-session tokens
• Trigger adaptively on risk signals such as new device, unfamiliar IP or ASN, rapid retries, or impossible travel
• Protect more than login, including signup, password reset, payment, gift card balance, and high-value actions
• Pair with MFA, device fingerprinting, velocity limits, and IP or device reputation
• Detect automation by checking for headless browsers, missing APIs, or inconsistent timing and mouse movement patterns
• Bind the challenge to the user session and recent intent to prevent token reuse
• Rotate challenge types and increase difficulty after repeated failures, while allowing low-friction flows for known good users
• Add invisible traps, such as honeypot fields and JavaScript integrity checks, to raise the cost for bots

5. IP Blacklisting

Blocking or sandboxing suspicious IP addresses can slow down credential stuffing, as attackers often cycle through a limited address pool.

Track where logins originate, look for IPs associated with multiple accounts, and compare a flagged IP against the recent history for each account to minimize false positives. Use blocking sparingly and prefer stepped responses such as challenges and rate limits.

How to do it

• Collect IP metadata such as ASN, geolocation, known proxy or TOR status, and reputation scores
• Keep rolling counters per IP and per subnet for login attempts, failures, and the number of distinct accounts touched
• Maintain per-account IP history and flag logins that do not match recent patterns or create impossible travel
• Set a response ladder starting with rate limiting, then CAPTCHA or MFA, then a  temporary block for repeat abuse
• Correlate IP signals with device fingerprint and cookie stability to separate real users from bots
• Use reputation feeds and your own denylists while auto-expiring entries to prevent long-term overblocking
• Treat residential proxies and VPNs carefully by sandboxing with step-up checks instead of permanent blocks
• Apply sliding-window thresholds that adapt to traffic spikes and seasonality
• Integrate controls with your WAF or CDN so rules deploy close to the edge and reduce origin load
• Log actions and review weekly so you can tune thresholds, reduce false positives, and unblock mistaken entries

6. Use a Password Manager

A password manager creates and stores long, unique passwords for every account, so you do not reuse credentials or rely on memory. It reduces the risk of credential stuffing and guessing attacks while keeping sign-in fast and consistent across devices.

How to do it

• Select a reputable, zero-knowledge manager that utilizes strong encryption and has a proven security history.
• Set a long, memorable master password and enable MFA for the manager itself.
• Generate unique passwords of at least 16 characters for every site and let the manager save them.
• Enable secure sync so passwords are available on phone and laptop, and lock the app when idle.
• Use autofill carefully and require a prompt before filling on unfamiliar sites.
• Run the built-in security checkup to find reused or weak passwords and fix them.
• Turn on breach monitoring so you are alerted if any saved accounts appear in a leak.
• Back up recovery keys or emergency access so you can get in if you lose a device.
• Keep the manager and browser extensions up to date with the latest version.
• Do not store MFA backup codes in the same place; keep them in a separate secure location.

7. Implement Rate Limiting

Rate limiting slows attackers by capping the number of login attempts that can occur within a specified time window. It blunts credential stuffing and brute-force runs, protects your auth endpoints under load, and gives you room to trigger extra checks when risk spikes.

How to do it

• Set thresholds per account per IP and per device fingerprint rather than one global counter
• Use sliding-window or token-bucket algorithms so limits feel fair during regular bursts
• Apply limits to all sensitive flows, including login, signup, password rese,t MFA verification, and API tokens
• Add a response ladder, start with minor delays then CAPTCHA or MF,A then temporary blocks for repeat abuse
• Track velocity signals attempts per minute, distinct accounts touched by one IP ASN or device
• Separate counters for success and failure tighten limits on repeated failures while allowing normal successes
• Return generic errors and avoid revealing whether the username or password was correct

8. Implement Bot Detection

Bots scrape content, drain loyalty points, scalp inventory, abuse mobile APIs, and flood apps with automated actions. A dedicated bot detection layer separates human traffic from automated traffic in real-time, cutting off account takeovers, payment fraud, and app-layer disruptions.

Group-IB Fraud Protection detects and blocks malicious bots at scale, identifies sophisticated automation that mimics users, and protects web, mobile, and API channels, safeguarding over 130 million users daily. It utilizes behavior analysis, device profiling, IP intelligence, malware indicators, and passive biometrics to prevent attacks without introducing friction, such as constant CAPTCHA.

How To Prevent Credential Stuffing Attacks With Group-IB?

Credential stuffing turns one breach into many by exploiting password reuse and automation. Bots cycle through stolen username-password pairs, blend into regular traffic, and move fast across web, mobile, and API channels.

Defeating it requires early warning on exposed credentials, real-time bot defense, and strict controls around high-risk sessions and actions.

How Group-IB helps

• Threat Intelligence. Monitors cybercriminal forums, dark web, marketplaces, and closed communities in real time to surface compromised credentials, stolen cards, fresh malware samples, and offers of access to corporate networks. This allows you to identify exposed accounts early and take action before further damage is done.
• Fraud Protection (bot defense). Detects and blocks malicious bot activity behind credential-stuffing runs, even when attackers rotate IP addresses or device identifiers to appear as legitimate users, thereby protecting your website, applications, and APIs.
• Behavior, device, and IP intelligence. Uses device fingerprinting and behavior analysis to distinguish real users from automation, plus IP intelligence (e.g., TOR, proxies, hosting providers) to flag risky sources and reduce false positives without heavy user friction.