Froxlor up to 0.9.34 Random Number Generator random values

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
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CTI Interest Score
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8.4$0-$5k0.00

Summaryinfo

A vulnerability was found in Froxlor up to 0.9.34. It has been classified as critical. Affected is an unknown function of the component Random Number Generator. Performing a manipulation results in random values. This vulnerability was named CVE-2016-5100. The attack may be initiated remotely. There is no available exploit. Upgrading the affected component is recommended.

Detailsinfo

A vulnerability, which was classified as critical, was found in Froxlor up to 0.9.34. This affects an unknown code block of the component Random Number Generator. The manipulation with an unknown input leads to a random values vulnerability. CWE is classifying the issue as CWE-330. The product uses insufficiently random numbers or values in a security context that depends on unpredictable numbers. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:

Froxlor before 0.9.35 uses the PHP rand function for random number generation, which makes it easier for remote attackers to guess the password reset token by predicting a value.

The bug was discovered 02/13/2017. The weakness was presented 02/13/2017 (Website). It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2016-5100 since 05/26/2016. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. The technical details are unknown and an exploit is not publicly available. The attack technique deployed by this issue is T1600.001 according to MITRE ATT&CK.

Upgrading to version 0.9.35 eliminates this vulnerability.

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Name

Version

License

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 8.5
VulDB Meta Temp Score: 8.4

VulDB Base Score: 7.3
VulDB Temp Score: 7.0
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 9.8
NVD Vector: 🔍

CVSSv2info

AVACAuCIA
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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍

NVD Base Score: 🔍

Exploitinginfo

Class: Random values
CWE: CWE-330 / CWE-310
CAPEC: 🔍
ATT&CK: 🔍

Physical: No
Local: No
Remote: Yes

Availability: 🔍
Status: Not defined

EPSS Score: 🔍
EPSS Percentile: 🔍

Price Prediction: 🔍
Current Price Estimation: 🔍

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: Upgrade
Status: 🔍

0-Day Time: 🔍

Upgrade: Froxlor 0.9.35
Patch: github.com

Timelineinfo

05/26/2016 🔍
02/13/2017 +263 days 🔍
02/13/2017 +0 days 🔍
02/13/2017 +0 days 🔍
02/14/2017 +1 days 🔍
11/14/2022 +2099 days 🔍

Sourcesinfo

Product: github.com

Advisory: da4ec3e1b591de96675817a009e26e05e848a6ba
Status: Not defined
Confirmation: 🔍

CVE: CVE-2016-5100 (🔍)
GCVE (CVE): GCVE-0-2016-5100
GCVE (VulDB): GCVE-100-96843
OSVDB: - CVE-2016-5100 - Froxlor - Weak Encryption Issue

Entryinfo

Created: 02/14/2017 09:05
Updated: 11/14/2022 08:29
Changes: 02/14/2017 09:05 (56), 08/14/2020 10:53 (4), 11/14/2022 08:29 (5)
Complete: 🔍
Cache ID: 216::103

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