CVE Vulnerabilities

CVE-2024-3183

Use of Password Hash With Insufficient Computational Effort

Published: Jun 12, 2024 | Modified: Sep 25, 2024
CVSS 3.x
8.1
HIGH
Source:
NVD
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N
CVSS 2.x
RedHat/V2
RedHat/V3
8.1 IMPORTANT
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N
Ubuntu
MEDIUM

A vulnerability was found in FreeIPA in a way when a Kerberos TGS-REQ is encrypted using the client’s session key. This key is different for each new session, which protects it from brute force attacks. However, the ticket it contains is encrypted using the target principal key directly. For user principals, this key is a hash of a public per-principal randomly-generated salt and the user’s password.

If a principal is compromised it means the attacker would be able to retrieve tickets encrypted to any principal, all of them being encrypted by their own key directly. By taking these tickets and salts offline, the attacker could run brute force attacks to find character strings able to decrypt tickets when combined to a principal salt (i.e. find the principal’s password).

Weakness

The product generates a hash for a password, but it uses a scheme that does not provide a sufficient level of computational effort that would make password cracking attacks infeasible or expensive.

Affected Software

Name Vendor Start Version End Version
Enterprise_linux Redhat 7.0 (including) 7.0 (including)
Enterprise_linux Redhat 8.0 (including) 8.0 (including)
Enterprise_linux_aus Redhat 8.2 (including) 8.2 (including)
Enterprise_linux_aus Redhat 8.4 (including) 8.4 (including)
Enterprise_linux_aus Redhat 8.6 (including) 8.6 (including)
Enterprise_linux_eus Redhat 8.8 (including) 8.8 (including)
Enterprise_linux_tus Redhat 8.4 (including) 8.4 (including)
Enterprise_linux_tus Redhat 8.6 (including) 8.6 (including)
Enterprise_linux_update_services_for_sap_solutions Redhat 8.4 (including) 8.4 (including)
Enterprise_linux_update_services_for_sap_solutions Redhat 8.6 (including) 8.6 (including)
Red Hat Enterprise Linux 7 RedHat ipa-0:4.6.8-5.el7_9.17 *
Red Hat Enterprise Linux 8 RedHat idm:DL1-8100020240528133707.823393f5 *
Red Hat Enterprise Linux 8.2 Advanced Update Support RedHat idm:DL1-8020020240530191103.792f4060 *
Red Hat Enterprise Linux 8.4 Advanced Mission Critical Update Support RedHat idm:DL1-8040020240528055121.5b01ab7e *
Red Hat Enterprise Linux 8.4 Telecommunications Update Service RedHat idm:DL1-8040020240528055121.5b01ab7e *
Red Hat Enterprise Linux 8.4 Update Services for SAP Solutions RedHat idm:DL1-8040020240528055121.5b01ab7e *
Red Hat Enterprise Linux 8.6 Advanced Mission Critical Update Support RedHat idm:DL1-8060020240530061719.ada582f1 *
Red Hat Enterprise Linux 8.6 Telecommunications Update Service RedHat idm:DL1-8060020240530061719.ada582f1 *
Red Hat Enterprise Linux 8.6 Update Services for SAP Solutions RedHat idm:DL1-8060020240530061719.ada582f1 *
Red Hat Enterprise Linux 8.8 Extended Update Support RedHat idm:DL1-8080020240530051744.b0a6ceea *
Red Hat Enterprise Linux 9 RedHat ipa-0:4.11.0-15.el9_4 *
Red Hat Enterprise Linux 9.0 Extended Update Support RedHat ipa-0:4.9.8-11.el9_0.3 *
Red Hat Enterprise Linux 9.2 Extended Update Support RedHat ipa-0:4.10.1-12.el9_2.2 *
Freeipa Ubuntu mantic *

Extended Description

Many password storage mechanisms compute a hash and store the hash, instead of storing the original password in plaintext. In this design, authentication involves accepting an incoming password, computing its hash, and comparing it to the stored hash. Many hash algorithms are designed to execute quickly with minimal overhead, even cryptographic hashes. However, this efficiency is a problem for password storage, because it can reduce an attacker’s workload for brute-force password cracking. If an attacker can obtain the hashes through some other method (such as SQL injection on a database that stores hashes), then the attacker can store the hashes offline and use various techniques to crack the passwords by computing hashes efficiently. 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 (such as cloud computing) and GPU, ASIC, or FPGA hardware. In such a scenario, an efficient hash algorithm helps the attacker. There are several properties of a hash scheme that are relevant to its strength against an offline, massively-parallel attack:

Note that the security requirements for the product may vary depending on the environment and the value of the passwords. Different schemes might not provide all of these properties, yet may still provide sufficient security for the environment. Conversely, a solution might be very strong in preserving one property, which still being very weak for an attack against another property, or it might not be able to significantly reduce the efficiency of a massively-parallel attack.

Potential Mitigations

  • 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.

References