A dictionary attack is a systematic, brute-force technique during which attackers will run common words and phrases, along with their simple variations, to guess passwords.

Unlike brute-force attacks, which attempt every possible combination of characters, a dictionary attack narrows the focus to commonly used passwords and variations, making it more efficient in terms of time and computational resources.

Dictionary attacks are based on the principle that many users tend to choose easily guessable passwords, such as common words, names, or simple phrases. By using a dictionary that contains these common words, an attacker can rapidly test multiple potential passwords in a short amount of time, increasing the chances of a successful compromise.

How a Dictionary Attack Works

A dictionary attack works by attempting to match a target’s password or encryption key against a list of possible candidates. The steps involved in executing a dictionary attack are as follows:

  1. Acquiring the Target’s Encrypted Data: The attacker first needs to obtain the encrypted data, typically a hashed version of the password. This might be collected from a breached database, intercepted transmission, or other sources where password data is stored.
  2. Using a Dictionary File: The attacker then uses a dictionary file, which is a list of words or phrases that are common in passwords. These lists can contain simple words (like “password” or “123456”), combinations of words, or even commonly used substitutions (like replacing “o” with “0” or “a” with “@”). Dictionary files can range from small, containing only basic words, to very large ones that include millions of entries, sometimes built from leaks or common password databases.
  3. Hash Comparison: The attacker hashes each word in the dictionary using the same hashing algorithm that was used to store the original password (e.g., MD5, SHA-1, or bcrypt). The attacker then compares the resulting hash with the target password’s hash. If a match is found, the attacker has successfully cracked the password.
  4. Refining the Attack: In some cases, dictionary attacks are extended with techniques like “brute-forcing” additional characters, appending common numbers (e.g., “1234”) or symbols (e.g., “!”), or applying common password variations such as capitalizing the first letter or adding a common suffix (e.g., “password1”).

Types of Dictionary Attacks

  1. Basic Dictionary Attack
    This attack uses a static list of commonly used words or phrases. These could be simple English words, frequently used phrases, or common passwords that people tend to choose. The dictionary attack is faster than a traditional brute-force attack, as it focuses on a predefined list of likely passwords, rather than trying every possible combination.
  2. Hybrid Dictionary Attack
    In a hybrid dictionary attack, the attacker combines a dictionary with additional transformations to account for common password patterns. These could include replacing characters with numbers or symbols (e.g., replacing “a” with “@”), adding digits to the end of words, or capitalizing the first letter. Hybrid dictionary attacks increase the range of possible passwords and improve the chances of success, particularly when users employ simple substitutions or slight variations.
  3. Rainbow Table Attack
    A rainbow table is a precomputed table of hash values for all possible plaintext passwords in a given dictionary. Rather than computing the hash for each word in real-time, an attacker can look up the hash in the rainbow table to quickly find the corresponding plaintext password. This method significantly speeds up the cracking process, but requires substantial storage and time to generate the rainbow table. The use of salts in password hashing (random data added to the password before hashing) can mitigate this type of attack.

Effectiveness of Dictionary Attacks

The effectiveness of a dictionary attack depends on several factors:

  1. Weak Passwords
    The primary advantage of dictionary attacks is that many users choose weak passwords that are simple, predictable, or based on common words. Passwords like “password,” “123456,” and “qwerty” are frequently found in dictionary files and are easy targets for attackers.
  2. Password Complexity
    A strong, complex password that includes a mix of upper and lower case letters, numbers, and special characters is harder to guess through a dictionary attack. Additionally, longer passwords with random characters are less likely to be found in a precompiled dictionary, making them more secure.
  3. Hashing Algorithm Used
    The strength of the hashing algorithm used to store the password also plays a role in how vulnerable a password is to a dictionary attack. Older or weak hashing algorithms, like MD5 or SHA-1, are faster to crack, making them more susceptible to dictionary attacks. Modern algorithms like bcrypt, scrypt, or Argon2, which involve salting and key stretching, are much harder to crack, even when using large dictionaries.
  4. Salting
    Salting is a security measure in which a random string of characters is added to the password before hashing. Salts prevent attackers from using precomputed dictionary or rainbow tables, as the hash will be unique even for identical passwords. Salting greatly enhances the security of stored passwords, making dictionary attacks significantly more difficult to carry out.

Defense Against Dictionary Attacks

To defend against dictionary attacks, both individuals and organizations must adopt best practices for securing passwords:

  1. Use Strong Passwords
    Users should create complex passwords that are long, random, and contain a mixture of letters, numbers, and special characters. Avoiding common words or easily guessable patterns can significantly reduce the likelihood of success for a dictionary attack.
  2. Enable Multi-Factor Authentication (MFA)
    MFA adds an extra layer of security by requiring a second form of verification (e.g., a code sent to a mobile device or an authentication app) in addition to the password. Even if an attacker successfully cracks a password using a dictionary attack, they would still need the second factor to access the account.
  3. Use Salting and Strong Hashing
    Storing passwords with strong hashing algorithms and a unique salt for each password makes dictionary attacks much more difficult. Modern cryptographic practices like bcrypt, Argon2, and PBKDF2 provide strong protections against these types of attacks.
  4. Implement Account Lockouts and Rate Limiting
    To prevent automated dictionary attacks, organizations can implement account lockout mechanisms after a certain number of failed login attempts. Additionally, rate limiting can slow down an attack by introducing delays between login attempts.
  5. Educate Users
    Training users to create strong, unique passwords and avoid reusing passwords across multiple sites can significantly reduce the effectiveness of dictionary attacks. Password managers can help users generate and store complex passwords without the need to remember them.

Conclusion

A dictionary attack is a powerful and efficient method of cracking passwords by exploiting commonly used words and phrases. While it is more efficient than brute-force attacks, it can still be highly effective against weak passwords or poorly configured systems.

By using strong password policies, multi-factor authentication, salting, and modern cryptographic algorithms, individuals and organizations can significantly reduce their vulnerability to dictionary attacks and better protect sensitive data from unauthorized access.

About BlackFog

BlackFog is the leader in on-device data privacy, data security and ransomware prevention. Our behavioral analysis and anti data exfiltration (ADX) technology stops hackers before they even get started. Our cyberthreat prevention software prevents ransomware, spyware, malware, phishing, unauthorized data collection and profiling and mitigates the risks associated with data breaches and insider threats. BlackFog blocks threats across mobile and desktop endpoints, protecting organizations data and privacy, and strengthening regulatory compliance.