The product uses a one-way cryptographic hash against an input that should not be reversible, such as a password, but the product uses a predictable 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, effectively disabling the protection that an unpredictable salt would provide.
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

Automated Static Analysis
Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, 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

Implementation
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.

CVE-2008-4905
Blogging software uses a hard-coded salt when calculating a password hash.
https://www.cve.org/CVERecord?id=CVE-2008-4905

CVE-2002-1657
Database server uses the username for a salt when encrypting passwords, simplifying brute force attacks.
https://www.cve.org/CVERecord?id=CVE-2002-1657

CVE-2001-0967
Server uses a constant salt when encrypting passwords, simplifying brute force attacks.
https://www.cve.org/CVERecord?id=CVE-2001-0967

CVE-2005-0408
chain: product generates predictable MD5 hashes using a constant value combined with username, allowing authentication bypass.
https://www.cve.org/CVERecord?id=CVE-2005-0408

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.

As of CWE 4.5, terminology related to randomness, entropy, and
predictability can vary widely. Within the developer and other
communities, "randomness" is used heavily. However, within
cryptography, "entropy" is distinct, typically implied as a
measurement. There are no commonly-used definitions, even within
standards documents and cryptography papers. Future versions of
CWE will attempt to define these terms and, if necessary,
distinguish between them in ways that are appropriate for
different communities but do not reduce the usability of CWE for
mapping, understanding, or other scenarios.

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

CWE Content Team
MITRE
2009-10-29
updated Observed_Examples, Relationships

CWE Content Team
MITRE
2010-02-16
updated References

CWE Content Team
MITRE
2011-03-29
updated Observed_Examples

CWE Content Team
MITRE
2011-06-01
updated Common_Consequences

CWE Content Team
MITRE
2012-05-11
updated References, Relationships

CWE Content Team
MITRE
2012-10-30
updated Potential_Mitigations, References

CWE Content Team
MITRE
2013-02-21
updated Description, Potential_Mitigations, References, Relationships, Type

CWE Content Team
MITRE
2014-02-18
updated Potential_Mitigations, References

CWE Content Team
MITRE
2014-07-30
updated Relationships

CWE Content Team
MITRE
2017-01-19
updated Relationships

CWE Content Team
MITRE
2017-11-08
updated Modes_of_Introduction, References, Relationships

CWE Content Team
MITRE
2018-03-27
updated References

CWE Content Team
MITRE
2019-06-20
updated Type

CWE Content Team
MITRE
2020-02-24
updated Relationships

CWE Content Team
MITRE
2021-07-20
updated Maintenance_Notes

CWE Content Team
MITRE
2021-10-28
updated Relationships

CWE Content Team
MITRE
2023-01-31
updated Description

CWE Content Team
MITRE
2023-04-27
updated Detection_Factors, References, Relationships

CWE Content Team
MITRE
2023-06-29
updated Mapping_Notes

CWE Content Team
MITRE
2025-09-09
4.18
2025-09-09
updated References

CWE Content Team
MITRE
2025-12-11
4.19
2025-12-11
updated Applicable_Platforms, Relationships, Weakness_Ordinalities