CPE, which stands for Common Platform Enumeration, is a standardized scheme for naming hardware, software, and operating systems. CPE provides a structured naming scheme to uniquely identify and classify information technology systems, platforms, and packages based on certain attributes such as vendor, product name, version, update, edition, and language.
CWE, or Common Weakness Enumeration, is a comprehensive list and categorization of software weaknesses and vulnerabilities. It serves as a common language for describing software security weaknesses in architecture, design, code, or implementation that can lead to vulnerabilities.
CAPEC, which stands for Common Attack Pattern Enumeration and Classification, is a comprehensive, publicly available resource that documents common patterns of attack employed by adversaries in cyber attacks. This knowledge base aims to understand and articulate common vulnerabilities and the methods attackers use to exploit them.
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Cogent DataHub Use of Password Hash With Insufficient Computational Effort
Cogent DataHub before 7.3.5 does not use a salt during password hashing, which makes it easier for context-dependent attackers to obtain cleartext passwords via a brute-force attack.
CVE Solutions
Cogent Real-Time Systems, Inc. has produced a new version of the
Cogent DataHub application, Version 7.3.5, that fixes three of the four
identified vulnerabilities. The updated version is available at the
following address:
http://cogentdatahub.com/Download_Software.html
Cogent
has indicated that it will not be fixing the cryptographic weaknesses
of hashed usernames and passwords because of compatibility issues with
existing systems. Cogent and the researcher agree that an effective
mitigation strategy for users is to select sufficiently strong
passwords. Cogent has indicated that password hashes can be checked for
strength using sites such as: https://crackstation.net/ .
Use of Password Hash With Insufficient Computational Effort 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.
Category : Credentials Management Errors Weaknesses in this category are related to the management of credentials.
Metrics
Metrics
Score
Severity
CVSS Vector
Source
V2
6
AV:L/AC:H/Au:S/C:C/I:C/A:C
V2
5
AV:N/AC:L/Au:N/C:P/I:N/A:N
nvd@nist.gov
EPSS
EPSS is a scoring model that predicts the likelihood of a vulnerability being exploited.
EPSS Score
The EPSS model produces a probability score between 0 and 1 (0 and 100%). The higher the score, the greater the probability that a vulnerability will be exploited.
Date
EPSS V0
EPSS V1
EPSS V2 (> 2022-02-04)
EPSS V3 (> 2025-03-07)
EPSS V4 (> 2025-03-17)
2022-02-06
–
–
0.89%
–
–
2022-03-27
–
–
0.89%
–
–
2022-04-03
–
–
0.89%
–
–
2022-04-24
–
–
0.89%
–
–
2022-07-17
–
–
0.89%
–
–
2022-10-09
–
–
0.89%
–
–
2023-02-19
–
–
0.89%
–
–
2023-03-12
–
–
–
0.25%
–
2023-04-16
–
–
–
0.25%
–
2023-09-17
–
–
–
0.25%
–
2024-02-11
–
–
–
0.25%
–
2024-03-31
–
–
–
0.25%
–
2024-04-14
–
–
–
0.21%
–
2024-06-02
–
–
–
0.21%
–
2024-06-16
–
–
–
0.21%
–
2024-08-04
–
–
–
0.21%
–
2024-08-11
–
–
–
0.21%
–
2024-09-22
–
–
–
0.21%
–
2024-09-29
–
–
–
0.21%
–
2024-10-06
–
–
–
0.21%
–
2024-12-15
–
–
–
0.18%
–
2024-12-22
–
–
–
0.18%
–
2025-03-09
–
–
–
0.18%
–
2025-03-16
–
–
–
0.18%
–
2025-01-19
–
–
–
0.18%
–
2025-03-18
–
–
–
–
0.24%
2025-03-30
–
–
–
–
0.27%
2025-04-06
–
–
–
–
0.27%
2025-04-15
–
–
–
–
0.27%
2025-10-04
–
–
–
–
0.1%
2025-11-18
–
–
–
–
0.1%
2025-11-18
–
–
–
–
0.1,%
EPSS Percentile
The percentile is used to rank CVE according to their EPSS score. For example, a CVE in the 95th percentile according to its EPSS score is more likely to be exploited than 95% of other CVE. Thus, the percentile is used to compare the EPSS score of a CVE with that of other CVE.