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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7.0$0-$5k0.00

Summaryinfo

A vulnerability was found in Irfan Skiljan IrfanView 4.54. It has been classified as critical. The affected element is an unknown function. Performing a manipulation results in memory corruption. This vulnerability is identified as CVE-2020-23554. The attack can be initiated remotely. There is not any exploit available.

Detailsinfo

A vulnerability, which was classified as critical, was found in Irfan Skiljan IrfanView 4.54 (Image Processing Software). This affects an unknown code block. The manipulation with an unknown input leads to a memory corruption vulnerability. CWE is classifying the issue as 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. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:

IrfanView 4.54 allows a user-mode write access violation starting at FORMATS!GetPlugInInfo+0x0000000000007e20.

The weakness was released 09/16/2022. It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2020-23554 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 10/18/2022).

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: 7.0
VulDB Meta Temp Score: 7.0

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

NVD Base Score: 7.8
NVD Vector: 🔍

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: Partially
Local: Yes
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 🔍
09/16/2022 +764 days 🔍
09/16/2022 +0 days 🔍
10/18/2022 +32 days 🔍

Sourcesinfo

Advisory: github.com
Status: Not defined

CVE: CVE-2020-23554 (🔍)
GCVE (CVE): GCVE-0-2020-23554
GCVE (VulDB): GCVE-100-208731

Entryinfo

Created: 09/16/2022 08:33
Updated: 10/18/2022 13:34
Changes: 09/16/2022 08:33 (38), 10/18/2022 13:34 (11)
Complete: 🔍
Cache ID: 216::103

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

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