MP3Gain 1.5.2 mpglibDBL layer3.c III_i_stereo out-of-bounds
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 5.4 | $0-$5k | 0.00 |
Summary
A vulnerability marked as critical has been reported in MP3Gain 1.5.2. This impacts the function III_i_stereo of the file layer3.c of the component mpglibDBL. Performing a manipulation results in out-of-bounds.
This vulnerability is reported as CVE-2017-14410. The attack requires a local approach. No exploit exists.
Details
A vulnerability was found in MP3Gain 1.5.2. It has been classified as critical. This affects the function III_i_stereo of the file layer3.c of the component mpglibDBL. The manipulation with an unknown input leads to a out-of-bounds vulnerability. CWE is classifying the issue as CWE-125. The product reads data past the end, or before the beginning, of the intended buffer. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:
A buffer over-read was discovered in III_i_stereo in layer3.c in mpglibDBL, as used in MP3Gain version 1.5.2. The vulnerability causes an application crash, which leads to remote denial of service.
The bug was discovered 09/08/2017. The weakness was disclosed 09/13/2017 (Website). It is possible to read the advisory at blogs.gentoo.org. This vulnerability is uniquely identified as CVE-2017-14410 since 09/12/2017. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. It demands that the victim is doing some kind of user interaction. Technical details of the vulnerability are known, but there is no available exploit.
The vulnerability was handled as a non-public zero-day exploit for at least 4 days. During that time the estimated underground price was around $0-$5k.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
The entries VDB-106469, VDB-106468, VDB-106466 and VDB-106465 are pretty similar. Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔍VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 5.4VulDB Meta Temp Score: 5.4
VulDB Base Score: 5.3
VulDB Temp Score: 5.3
VulDB Vector: 🔍
VulDB Reliability: 🔍
NVD Base Score: 5.5
NVD Vector: 🔍
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍
NVD Base Score: 🔍
Exploiting
Class: Out-of-boundsCWE: CWE-125 / CWE-119
CAPEC: 🔍
ATT&CK: 🔍
Physical: Partially
Local: Yes
Remote: Yes
Availability: 🔍
Status: Not defined
EPSS Score: 🔍
EPSS Percentile: 🔍
Price Prediction: 🔍
Current Price Estimation: 🔍
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔍
Timeline
09/08/2017 🔍09/12/2017 🔍
09/12/2017 🔍
09/13/2017 🔍
09/13/2017 🔍
11/15/2019 🔍
Sources
Advisory: blogs.gentoo.orgStatus: Not defined
CVE: CVE-2017-14410 (🔍)
GCVE (CVE): GCVE-0-2017-14410
GCVE (VulDB): GCVE-100-106467
See also: 🔍
Entry
Created: 09/13/2017 12:09Updated: 11/15/2019 13:31
Changes: 09/13/2017 12:09 (52), 11/15/2019 13:31 (7)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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