Internet Computer Candid up to 0.9.9 inconsistent special elements

CVSS Meta Temp Score
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CTI Interest Score
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7.3$0-$5k0.00

Summaryinfo

A vulnerability classified as critical has been found in Internet Computer Candid up to 0.9.9. This impacts an unknown function. This manipulation causes improper handling of inconsistent special elements. This vulnerability is tracked as CVE-2023-6245. The attack is possible to be carried out remotely. No exploit exists. It is recommended to upgrade the affected component.

Detailsinfo

A vulnerability classified as critical was found in Internet Computer Candid up to 0.9.9. Affected by this vulnerability is some unknown processing. The manipulation with an unknown input leads to a improper handling of inconsistent special elements vulnerability. The CWE definition for the vulnerability is CWE-168. The product does not properly handle input in which an inconsistency exists between two or more special characters or reserved words. As an impact it is known to affect availability. The summary by CVE is:

The Candid library causes a Denial of Service while parsing a specially crafted payload with 'empty' data type. For example, if the payload is `record { * ; empty }` and the canister interface expects `record { * }` then the Rust candid decoder treats empty as an extra field required by the type. The problem with the type empty is that the candid Rust library wrongly categorizes empty as a recoverable error when skipping the field and thus causing an infinite decoding loop. Canisters using affected versions of candid are exposed to denial of service by causing the decoding to run indefinitely until the canister traps due to reaching maximum instruction limit per execution round. Repeated exposure to the payload will result in degraded performance of the canister. Note: Canisters written in Motoko are unaffected.

The weakness was disclosed 12/08/2023 as GHSA-7787-p7x6-fq3j. It is possible to read the advisory at github.com. This vulnerability is known as CVE-2023-6245 since 11/21/2023. The technical details are unknown and an exploit is not publicly available.

The vulnerability scanner Nessus provides a plugin with the ID 253216 (Linux Distros Unpatched Vulnerability : CVE-2023-6245), which helps to determine the existence of the flaw in a target environment.

Upgrading to version 0.9.10 eliminates this vulnerability. Applying a patch is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.

The vulnerability is also documented in the vulnerability database at Tenable (253216). 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: 7.5
VulDB Meta Temp Score: 7.3

VulDB Base Score: 7.5
VulDB Temp Score: 7.2
VulDB Vector: 🔍
VulDB Reliability: 🔍

CNA Base Score: 7.5
CNA Vector (Dfinity): 🔍

CVSSv2info

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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍

Exploitinginfo

Class: Improper handling of inconsistent special elements
CWE: CWE-168 / CWE-20
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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Nessus ID: 253216
Nessus Name: Linux Distros Unpatched Vulnerability : CVE-2023-6245

Threat Intelligenceinfo

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

Countermeasuresinfo

Recommended: Upgrade
Status: 🔍

0-Day Time: 🔍

Upgrade: Candid 0.9.10
Patch: github.com

Timelineinfo

11/21/2023 🔍
12/08/2023 +17 days 🔍
12/08/2023 +0 days 🔍
08/24/2025 +625 days 🔍

Sourcesinfo

Advisory: GHSA-7787-p7x6-fq3j
Status: Confirmed

CVE: CVE-2023-6245 (🔍)
GCVE (CVE): GCVE-0-2023-6245
GCVE (VulDB): GCVE-100-247267

Entryinfo

Created: 12/08/2023 19:30
Updated: 08/24/2025 19:28
Changes: 12/08/2023 19:30 (49), 12/31/2023 13:47 (1), 08/24/2025 19:28 (17)
Complete: 🔍
Cache ID: 216::103

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

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