Telegram rlottie numeric truncation error

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
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.
6.3$0-$5k0.87

Summaryinfo

A vulnerability identified as critical has been detected in Telegram rlottie. The affected element is an unknown function. Performing a manipulation results in numeric truncation error. This vulnerability was named CVE-2026-111105. The attack may be initiated remotely. There is no available exploit.

Detailsinfo

A vulnerability classified as critical has been found in Telegram rlottie (affected version not known). This affects some unknown functionality. The manipulation with an unknown input leads to a numeric truncation error vulnerability. CWE is classifying the issue as CWE-197. Truncation errors occur when a primitive is cast to a primitive of a smaller size and data is lost in the conversion. This is going to have an impact on confidentiality, integrity, and availability.

This vulnerability is uniquely identified as CVE-2026-111105. The exploitability is told to be easy. It is possible to initiate the attack remotely. 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 10/15/2026).

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

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

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

VulDB Base Score: 6.3
VulDB Temp Score: 6.3
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: Numeric truncation error
CWE: CWE-197 / CWE-189
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

Availability: 🔒
Status: Not defined
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

10/15/2026 Advisory disclosed
10/15/2026 +0 days VulDB entry created
10/15/2026 +0 days VulDB entry last update

Sourcesinfo

Status: Not defined

CVE: CVE-2026-111105 (🔒)
GCVE (CVE): GCVE-0-2026-111105
GCVE (VulDB): GCVE-100-420723

Entryinfo

Created: 10/15/2026 18:50
Changes: 10/15/2026 18:50 (46)
Complete: 🔍
Cache ID: 216::103

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

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