Irfan Skiljan IrfanView 4.54 memory corruption

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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6.1$0-$5k0.00

Summaryinfo

A vulnerability classified as critical has been found in Irfan Skiljan IrfanView 4.54. Affected by this issue is some unknown functionality. This manipulation causes memory corruption. The identification of this vulnerability is CVE-2020-23545. It is possible to initiate the attack remotely. There is no exploit available.

Detailsinfo

A vulnerability classified as critical was found in Irfan Skiljan IrfanView 4.54 (Image Processing Software). Affected by this vulnerability is some unknown processing. The manipulation with an unknown input leads to a memory corruption vulnerability. The CWE definition for the vulnerability is CWE-119. The product performs operations on a memory buffer, but it can read from or write to a memory location that is outside of the intended boundary of the buffer. As an impact it is known to affect confidentiality, integrity, and availability.

The weakness was shared 12/15/2021. It is possible to read the advisory at github.com. This vulnerability is known as CVE-2020-23545 since 08/13/2020. It demands that the victim is doing some kind of user interaction. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 12/15/2021).

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

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

Productinfo

Type

Vendor

Name

Version

License

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 6.3
VulDB Meta Temp Score: 6.1

VulDB Base Score: 6.3
VulDB Temp Score: 6.1
VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv2info

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

Exploitinginfo

Class: Memory corruption
CWE: CWE-119
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: no mitigation known
Status: 🔍

0-Day Time: 🔍

Timelineinfo

08/13/2020 🔍
12/15/2021 +489 days 🔍
12/15/2021 +0 days 🔍
12/18/2021 +3 days 🔍

Sourcesinfo

Advisory: github.com
Status: Not defined

CVE: CVE-2020-23545 (🔍)
GCVE (CVE): GCVE-0-2020-23545
GCVE (VulDB): GCVE-100-188299

Entryinfo

Created: 12/15/2021 13:13
Updated: 12/18/2021 08:26
Changes: 12/15/2021 13:13 (37), 12/18/2021 08:26 (1)
Complete: 🔍
Cache ID: 216::103

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

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