libsixel 1.8.2 fromsixel.c sixel_decode_raw_impl integer overflow

HistoryDiffrelatejsonxmlCTI

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 (≈) Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.	CTI Interest Score Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
8.5	$0-$5k	0.00

Summaryinfo

A vulnerability was found in libsixel 1.8.2. It has been classified as critical. Affected by this vulnerability is the function sixel_decode_raw_impl of the file fromsixel.c. The manipulation leads to integer overflow. This vulnerability is referenced as CVE-2019-19637. Remote exploitation of the attack is possible. No exploit is available.

Detailsinfo

A vulnerability was found in libsixel 1.8.2 and classified as critical. This issue affects the function sixel_decode_raw_impl of the file fromsixel.c. The manipulation with an unknown input leads to a integer overflow vulnerability. Using CWE to declare the problem leads to CWE-190. The product performs a calculation that can produce an integer overflow or wraparound, when the logic assumes that the resulting value will always be larger than the original value. This can introduce other weaknesses when the calculation is used for resource management or execution control. Impacted is confidentiality, integrity, and availability. The summary by CVE is:

An issue was discovered in libsixel 1.8.2. There is an integer overflow in the function sixel_decode_raw_impl at fromsixel.c.

The weakness was published 12/08/2019. The identification of this vulnerability is CVE-2019-19637 since 12/08/2019. The attack may be initiated remotely. No form of authentication is needed for a successful exploitation. Technical details of the vulnerability are known, but there is no available exploit.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

Similar entries are available at VDB-146796, VDB-146794 and VDB-146793. Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Name

libsixel

Version

1.8.2

License

open-source

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

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

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

NVD Base Score: 9.8
NVD Vector: 🔍

CVSSv2info

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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: 🔍

Exploitinginfo

Class: Integer overflow
CWE: CWE-190 / CWE-189
CAPEC: 🔍
ATT&CK: 🔍

Physical: No
Local: No
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 Intelligenceinfo

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

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔍

Timelineinfo

12/08/2019 🔍
12/08/2019 +0 days 🔍
12/08/2019 +0 days 🔍
03/09/2024 +1553 days 🔍

Sourcesinfo

Advisory: 105
Status: Not defined

CVE: CVE-2019-19637 (🔍)
GCVE (CVE): GCVE-0-2019-19637
GCVE (VulDB): GCVE-100-146795
See also: 🔍

Entryinfo

Created: 12/08/2019 13:23
Updated: 03/09/2024 08:31
Changes: 12/08/2019 13:23 (36), 12/08/2019 13:28 (17), 03/09/2024 08:31 (4)
Complete: 🔍
Cache ID: 216::103

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