Silicon Labs Bootloader up to 4.0.1 GBL Parser memory corruption

CVSS Meta Temp Score
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Current Exploit Price (≈)
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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.
8.7$0-$5k0.00

Summaryinfo

A vulnerability marked as critical has been reported in Silicon Labs Bootloader up to 4.0.1. The affected element is an unknown function of the component GBL Parser. The manipulation leads to memory corruption. This vulnerability is uniquely identified as CVE-2022-24936. The attack can only be initiated within the local network. No exploit exists.

Detailsinfo

A vulnerability was found in Silicon Labs Bootloader up to 4.0.1. It has been rated as critical. This issue affects an unknown code of the component GBL Parser. The manipulation with an unknown input leads to a memory corruption vulnerability. Using CWE to declare the problem leads to 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. Impacted is confidentiality, integrity, and availability. The summary by CVE is:

Out-of-Bounds error in GBL parser in Silicon Labs Gecko Bootloader version 4.0.1 and earlier allows attacker to overwrite flash Sign key and OTA decryption key via malicious bootloader upgrade.

The weakness was disclosed 11/02/2022. It is possible to read the advisory at community.silabs.com. The identification of this vulnerability is CVE-2022-24936 since 02/10/2022. 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 12/04/2022).

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

Vendor

Name

Version

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 8.7
VulDB Meta Temp Score: 8.7

VulDB Base Score: 8.8
VulDB Temp Score: 8.8
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 9.1
NVD Vector: 🔍

CNA Base Score: 8.3
CNA Vector ([email protected]): 🔍

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

02/10/2022 🔍
11/02/2022 +265 days 🔍
11/02/2022 +0 days 🔍
12/04/2022 +32 days 🔍

Sourcesinfo

Advisory: community.silabs.com
Status: Confirmed

CVE: CVE-2022-24936 (🔍)
GCVE (CVE): GCVE-0-2022-24936
GCVE (VulDB): GCVE-100-212867

Entryinfo

Created: 11/02/2022 21:51
Updated: 12/04/2022 09:39
Changes: 11/02/2022 21:51 (48), 12/04/2022 09:39 (12)
Complete: 🔍
Cache ID: 216::103

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

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