The product uses a one-way cryptographic hash against an input that should not be reversible, such as a password, but the product does not also use a salt as part of the input.

This makes it easier for attackers to pre-compute the hash value using dictionary attack techniques such as rainbow tables.
It should be noted that, despite common perceptions, the use of a good salt with a hash does not sufficiently increase the effort for an attacker who is targeting an individual password, or who has a large amount of computing resources available, such as with cloud-based services or specialized, inexpensive hardware. Offline password cracking can still be effective if the hash function is not expensive to compute; many cryptographic functions are designed to be efficient and can be vulnerable to attacks using massive computing resources, even if the hash is cryptographically strong. The use of a salt only slightly increases the computing requirements for an attacker compared to other strategies such as adaptive hash functions. See CWE-916 for more details.

Primary

In cryptography, salt refers to some random addition of data to an input before hashing to make dictionary attacks more difficult.

Implementation
REALIZATION: This weakness is caused during implementation of an architectural security tactic.

Access Control
Bypass Protection Mechanism
Gain Privileges or Assume Identity
If an attacker can gain access to the hashes, then the lack of a salt makes it easier to conduct brute force attacks using techniques such as rainbow tables.

Automated Static Analysis - Binary or Bytecode

According to SOAR [REF-1479], the following detection techniques may be useful:

Cost effective for partial coverage:

Bytecode Weakness Analysis - including disassembler + source code weakness analysis
Binary Weakness Analysis - including disassembler + source code weakness analysis

SOAR Partial

Manual Static Analysis - Binary or Bytecode

According to SOAR [REF-1479], the following detection techniques may be useful:

Cost effective for partial coverage:

Binary / Bytecode disassembler - then use manual analysis for vulnerabilities & anomalies

SOAR Partial

Manual Static Analysis - Source Code

According to SOAR [REF-1479], the following detection techniques may be useful:

Highly cost effective:

Focused Manual Spotcheck - Focused manual analysis of source
Manual Source Code Review (not inspections)

High

Automated Static Analysis - Source Code

According to SOAR [REF-1479], the following detection techniques may be useful:

Highly cost effective:

Source code Weakness Analyzer
Context-configured Source Code Weakness Analyzer

High

Automated Static Analysis

According to SOAR [REF-1479], the following detection techniques may be useful:

Cost effective for partial coverage:

Configuration Checker

SOAR Partial

Architecture or Design Review

According to SOAR [REF-1479], the following detection techniques may be useful:

Highly cost effective:

Formal Methods / Correct-By-Construction

Cost effective for partial coverage:

Inspection (IEEE 1028 standard) (can apply to requirements, design, source code, etc.)

High

Architecture and Design

Use an adaptive hash function that can be configured to change the amount of computational effort needed to compute the hash, such as the number of iterations ("stretching") or the amount of memory required. Some hash functions perform salting automatically. These functions can significantly increase the overhead for a brute force attack compared to intentionally-fast functions such as MD5. For example, rainbow table attacks can become infeasible due to the high computing overhead. Finally, since computing power gets faster and cheaper over time, the technique can be reconfigured to increase the workload without forcing an entire replacement of the algorithm in use.
Some hash functions that have one or more of these desired properties include bcrypt [REF-291], scrypt [REF-292], and PBKDF2 [REF-293]. While there is active debate about which of these is the most effective, they are all stronger than using salts with hash functions with very little computing overhead.
Note that using these functions can have an impact on performance, so they require special consideration to avoid denial-of-service attacks. However, their configurability provides finer control over how much CPU and memory is used, so it could be adjusted to suit the environment's needs.

High

Architecture and Design
If a technique that requires extra computational effort can not be implemented, then for each password that is processed, generate a new random salt using a strong random number generator with unpredictable seeds. Add the salt to the plaintext password before hashing it. When storing the hash, also store the salt. Do not use the same salt for every password.
Limited
Be aware that salts will not reduce the workload of a targeted attack against an individual hash (such as the password for a critical person), and in general they are less effective than other hashing techniques such as increasing the computation time or memory overhead. Without a built-in workload, modern attacks can compute large numbers of hashes, or even exhaust the entire space of all possible passwords, within a very short amount of time, using massively-parallel computing and GPU, ASIC, or FPGA hardware.

Implementation
Architecture and Design
When using industry-approved techniques, use them correctly. Don't cut corners by skipping resource-intensive steps (CWE-325). These steps are often essential for preventing common attacks.

In both of these examples, a user is logged in if their given password matches a stored password:

unsigned char *check_passwd(char *plaintext) {ctext = simple_digest("sha1",plaintext,strlen(plaintext), ... );
//Login if hash matches stored hash
if (equal(ctext, secret_password())) {login_user();}}

String plainText = new String(plainTextIn);MessageDigest encer = MessageDigest.getInstance("SHA");encer.update(plainTextIn);byte[] digest = password.digest();
//Login if hash matches stored hash
if (equal(digest,secret_password())) {login_user();}

This code relies exclusively on a password mechanism (CWE-309) using only one factor of authentication (CWE-308). If an attacker can steal or guess a user's password, they are given full access to their account. Note this code also uses SHA-1, which is a weak hash (CWE-328). It also does not use a salt (CWE-759).

In this example, a new user provides a new username and password to create an account. The program hashes the new user's password then stores it in a database.

def storePassword(userName,Password):hasher = hashlib.new('md5')hasher.update(Password)hashedPassword = hasher.digest()

# UpdateUserLogin returns True on success, False otherwise
return updateUserLogin(userName,hashedPassword)

While it is good to avoid storing a cleartext password, the program does not provide a salt to the hashing function, thus increasing the chances of an attacker being able to reverse the hash and discover the original password if the database is compromised.
Fixing this is as simple as providing a salt to the hashing function on initialization:

def storePassword(userName,Password):hasher = hashlib.new('md5',b'SaltGoesHere')hasher.update(Password)hashedPassword = hasher.digest()

# UpdateUserLogin returns True on success, False otherwise
return updateUserLogin(userName,hashedPassword)

Note that regardless of the usage of a salt, the md5 hash is no longer considered secure, so this example still exhibits CWE-327.

CVE-2008-1526
Router does not use a salt with a hash, making it easier to crack passwords.
https://www.cve.org/CVERecord?id=CVE-2008-1526

CVE-2006-1058
Router does not use a salt with a hash, making it easier to crack passwords.
https://www.cve.org/CVERecord?id=CVE-2006-1058

Allowed
This CWE entry is at the Variant level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities.
Carefully read both the name and description to ensure that this mapping is an appropriate fit. Do not try to 'force' a mapping to a lower-level Base/Variant simply to comply with this preferred level of abstraction.

CWE Content Team
MITRE
2009-03-03
1.3
2009-03-10

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MITRE
2009-10-29
updated Relationships

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MITRE
2010-02-16
updated References

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2011-03-29
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2011-06-01
updated Common_Consequences

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MITRE
2011-06-27
updated Common_Consequences, Demonstrative_Examples, Potential_Mitigations, Related_Attack_Patterns, Relationships

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MITRE
2011-09-13
updated Potential_Mitigations, References, Relationships

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MITRE
2012-05-11
updated References, Related_Attack_Patterns, Relationships

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2012-10-30
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MITRE
2013-02-21
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2014-02-18
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2014-07-30
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2017-01-19
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2017-11-08
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2018-03-27
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2019-06-20
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2020-02-24
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2021-03-15
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2021-10-28
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2023-01-31
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2023-04-27
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2023-06-29
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2024-02-29
4.14
2024-02-29
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2025-09-09
4.18
2025-09-09
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2025-12-11
4.19
2025-12-11
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