Password Cracking: Understanding the Time Factor

Password security remains a cornerstone of digital defense, yet many users and even developers underestimate the actual time it takes for a determined attacker to “crack” a password. This isn’t merely about guessing a few common words; it involves sophisticated techniques and immense computational power. Understanding the factors that influence password cracking time is crucial for implementing robust security measures and safeguarding sensitive data. This article will delve into the mechanics of password cracking, explore the variables that dictate its speed, and outline modern best practices for creating passwords that can withstand even the most advanced attacks.

The Fundamentals of Password Cracking

At its core, password cracking is an attempt to discover a password, typically by systematically trying different combinations or exploiting known vulnerabilities. The primary methods include:

Brute-Force Attacks: This is the most straightforward but computationally intensive method. An attacker tries every possible combination of characters until the correct password is found. The time it takes is directly proportional to the password’s complexity and length.
Dictionary Attacks: Instead of trying random combinations, attackers use lists of common words, phrases, and previously leaked passwords. These attacks are significantly faster if the target password is weak or commonly used.
Rainbow Table Attacks: These precomputed tables store hashes of a vast number of potential passwords. If an attacker gains access to a password hash (e.g., from a data breach), they can quickly look up the original password in a rainbow table without needing to perform the hashing operation for each guess. Modern password hashing algorithms mitigate this by using “salts.”
Credential Stuffing: This isn’t a cracking method per se, but an attack that leverages cracked credentials. Attackers take username/password pairs obtained from a data breach on one service and try them across many other services, exploiting the common user habit of reusing passwords.

The success and speed of these attacks hinge on several key concepts, including entropy, character sets, and length. Entropy measures the randomness and unpredictability of a password, expressed in bits. Higher entropy means a more secure password. The character set refers to the pool of characters available (e.g., lowercase letters, uppercase letters, numbers, symbols). A larger character set increases the number of possible combinations. Length is perhaps the most significant factor, as its impact on cracking time is exponential.

Calculating Cracking Time: The Exponential Factor

The theoretical time it takes to brute-force a password can be estimated using a simple formula:

Time = (Character_Set_Size ^ Length) / Guesses_Per_Second

Let’s break down the components and their impact:

Character Set Size:
- Lowercase letters (a-z): 26 characters
- Lowercase + Uppercase letters (a-zA-Z): 52 characters
- Lowercase + Uppercase + Numbers (a-zA-Z0-9): 62 characters
- Lowercase + Uppercase + Numbers + Symbols (!@#$%^&*…): ~94 characters (depending on the specific symbols considered)
Even a small increase in the character set dramatically increases the number of possibilities. For example, a 10-character password using only lowercase letters has 26^10 combinations, while adding uppercase letters increases it to 52^10 combinations.
Length: This is the most critical variable. Each additional character exponentially increases the cracking time. Consider a character set of 94 characters:
- 8 characters: 94^8 combinations
- 9 characters: 94^9 combinations (94 times harder than 8 characters)
- 12 characters: 94^12 combinations
Guesses Per Second: This represents the attacker’s computational power. Modern GPUs, specialized hardware (like FPGAs or ASICs), and distributed cloud computing environments can achieve billions or even trillions of guesses per second. For instance, a single high-end GPU can test hundreds of billions of simple hashes per second.

Digital padlock with binary code overlay — Photo by FlyD on Unsplash

To illustrate, consider a password with only lowercase letters. If an attacker can make 100 billion guesses per second:

A 6-character password (26^6 = 308,915,776 combinations) would take milliseconds to crack.
An 8-character password (26^8 = 208,827,064,576 combinations) would take approximately 2 seconds.
A 10-character password (26^10 = 14,116,709,567,808 combinations) would take roughly 2 minutes.

Now, if we increase the character set to include lowercase, uppercase, numbers, and symbols (94 characters):

A 10-character password (94^10 = ~5.4 x 10^19 combinations) would take over 17 years.
A 12-character password (94^12 = ~4.8 x 10^23 combinations) would take over 150,000 years.

These numbers highlight the exponential power of length and character set. Even with immense computational power, sufficiently long and complex passwords remain practically uncrackable via brute force alone.

Real-World Factors and Advanced Defensive Measures

While theoretical cracking times are informative, real-world scenarios introduce complexities. Attackers rarely rely solely on pure brute force for long, especially against well-secured systems.

Password Hashing and Salting

Most modern systems do not store passwords in plaintext. Instead, they store a hash of the password. When a user attempts to log in, the entered password is hashed, and the resulting hash is compared to the stored hash. This prevents attackers from directly accessing passwords even if they compromise the database.

However, simple hashing is vulnerable to rainbow table attacks. To counter this, systems employ salting. A unique, random string (the “salt”) is added to the password before it’s hashed. This means that even if two users have the same password, their stored hashes will be different because of their unique salts. This effectively renders rainbow tables useless, as each password now has a unique hash.

Password Stretching (Key Derivation Functions)

Beyond salting, modern best practices dictate the use of password stretching or key derivation functions (KDFs). These algorithms are intentionally designed to be computationally expensive and slow down the hashing process. This “slowness” is negligible for a single legitimate login attempt but becomes a significant hurdle for attackers trying to crack billions of hashes.

Popular KDFs include:

bcrypt: Widely adopted and designed to be resistant to GPU-based attacks by being memory-hard.
scrypt: Similar to bcrypt but even more memory-hard, making it resource-intensive for attackers.
Argon2: The winner of the Password Hashing Competition, offering configurable memory, time, and parallelism parameters, making it highly adaptable and secure against various attack types.

Using a strong KDF like Argon2 with appropriate parameters can increase the effective cracking time for a single password hash from milliseconds to potentially seconds or even minutes, drastically slowing down large-scale attacks.

Best Practices for Robust Passwords

Given the evolving threat landscape, adopting current best practices for password creation and management is non-negotiable.

Prioritize Length Over Arbitrary Complexity: While character set diversity is good, length is paramount. Many security experts now recommend passphrases – long sequences of random, unrelated words – over short, complex character strings. A 16-character passphrase like “correct horse battery staple” is far more secure and memorable than an 8-character “P@$$w0rd!”.
Utilize Password Managers: Tools like Bitwarden, LastPass, or 1Password generate and store unique, strong passwords for each service, eliminating the need for users to remember complex strings and preventing password reuse. This significantly reduces the risk of credential stuffing attacks.
Enable Multi-Factor Authentication (MFA): MFA adds a crucial layer of security by requiring a second form of verification (e.g., a code from a mobile app, a physical security key) in addition to the password. Even if an attacker cracks your password, they cannot access your account without the second factor. This is arguably the most effective single measure against compromised passwords.
Avoid Personal Information: Do not use easily guessable information like birthdays, pet names, or common dictionary words.
Regular Software Updates: Keep operating systems, browsers, and applications updated to patch vulnerabilities that attackers could exploit to steal passwords or hashes.

Conclusion

The time it takes to crack a password is a dynamic calculation influenced by its inherent complexity, the attacker’s computational resources, and the defensive measures employed by the service storing the password. While brute-force attacks against short, simple passwords can be executed in milliseconds, well-constructed, long passwords (especially passphrases) combined with robust hashing algorithms (like Argon2 with salting and stretching) can effectively push cracking times into the realm of geological ages. However, the most effective defense against modern password attacks lies in a layered approach: strong, unique passwords, managed by a password manager, and protected by multi-factor authentication. By embracing these practices, individuals and organizations can significantly enhance their digital security posture and make their credentials virtually uncrackable by even the most persistent adversaries.

References

NVIDIA. (2023). Accelerating Cybersecurity with GPUs. Available at: [URL not available] National Institute of Standards and Technology (NIST). (2020). NIST Special Publication 800-63B: Digital Identity Guidelines. Available at: https://pages.nist.gov/800-63-3/sp800-63b.html Biryukov, A., Dinu, D., & Khovratovich, D. (2015). Argon2: New Generation of Password Hashing and Key Derivation Function. Available at: https://www.iacr.org/archive/fse2016/092/092.pdf PassGAN. (2017). PassGAN: A Deep Learning Approach for Password Guessing. Available at: https://arxiv.org/pdf/1709.00494 Troy Hunt. (2024). Have I Been Pwned?. Available at: https://haveibeenpwned.com/