What is the official website of Keylend ?

The official website of Keylend is http://www.keylend.com.au.

What is Keylend's cybersecurity risk score?

Keylend has an AI-generated cybersecurity risk score of 734 out of 1000, indicating a Moderate security posture according to Rankiteo's assessment.

How many security incidents has Keylend experienced?

According to Rankiteo, Keylend currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has Keylend been affected by any supply chain cyber incidents ?

According to Rankiteo, Keylend has not been affected by any supply chain cyber incidents, and no incident IDs are currently listed for the organization.

Does Keylend have SOC 2 Type 1 certification ?

According to Rankiteo, Keylend is not certified under SOC 2 Type 1.

Does Keylend have SOC 2 Type 2 certification ?

According to Rankiteo, Keylend does not hold a SOC 2 Type 2 certification.

Does Keylend comply with GDPR ?

According to Rankiteo, Keylend is not listed as GDPR compliant.

Does Keylend have PCI DSS certification ?

According to Rankiteo, Keylend does not currently maintain PCI DSS compliance.

Does Keylend comply with HIPAA ?

According to Rankiteo, Keylend is not compliant with HIPAA regulations.

Does Keylend have ISO 27001 certification ?

According to Rankiteo,Keylend is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does Keylend operate in ?

Keylend operates primarily in the Financial Services industry.

How many employees does Keylend have ?

Keylend employs approximately 53 people worldwide.

Does Keylend own any subsidiaries ?

Keylend presently has no subsidiaries across any sectors.

How many LinkedIn followers does Keylend have ?

Keylend's official LinkedIn profile has approximately 726 followers.

What is the NAICS classification code for Keylend ?

Keylend is classified under the NAICS code 52, which corresponds to Finance and Insurance.

Does Keylend have a Crunchbase profile ?

No, Keylend does not have a profile on Crunchbase.

Does Keylend have a LinkedIn profile ?

Yes, Keylend maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/keylend.

How many cybersecurity incidents has Keylend experienced ?

As of June 23, 2026, Rankiteo reports that Keylend has experienced 1 cybersecurity incidents.

How many peer or competitor companies does Keylend have ?

Keylend has an estimated 32,124 peer or competitor companies worldwide.

What types of cybersecurity incidents has Keylend faced ?

Incident Types: The types of cybersecurity incidents that have occurred include Cyber Attack.

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Keylend

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734

/1000

Moderate

759

/1000

Fair

Keylend Vendor Cyber Rating & Cyber Score

keylend.com.au

Add Your Compliance Badge

Keylend established its origins in 1998 by founder and CEO Chris Burns. At Keylend we offer a wealth of knowledge and experience in finance for matters relating to residential, commercial, vehicle, and equipment finance as well as refinancing, personal loans and general insurance. Whether you are a first home buyer, next home buyer, experienced investor, or simply looking to refinance, our Lending Advisers can assist with all of your financial needs. We operate Australia wide with our head office based in Norwood, South Australia. As a full member of the Mortgage and Finance Association of Australia (MFAA), Keylend has a proud history and reputation in the Australian mortgage industry. With over 80 brokers Australia wide, we remain

Keylend A.I CyberSecurity Scoring

Scoring History

Keylend

Keylend CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

Keylend

Cyber Attack

4/2026

KEY1781583821

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A.I.

Keylend Company Scoring based on AI Models

Cyber Incidents Likelihood 3 - 6 - 9 months

Actual

Prediction

Incident Predictions locked

Access Monitoring Plan

A.I Risk Score Likelihood 3 - 6 - 9 months

Actual

Prediction A

Prediction B

Prediction C

Prediction D

A.I. Risk Score Predictions locked

Access Monitoring Plan

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Underwriter Stats for Keylend

Incidents vs Financial Services Industry Avg (This Year)

Keylend has 45.05% fewer incidents than the average of same-industry companies with at least one recorded incident.

Incidents vs All-Companies Average (This Year)

Keylend has 6.54% fewer incidents than the average of all companies with at least one recorded incident.

Incident Types Keylend vs Financial Services Industry Avg (This Year)

Keylend reported 1 incidents this year: 1 cyber attacks, 0 ransomware, 0 vulnerabilities, 0 data breaches, compared to industry peers with at least 1 incident.

Incident History - Keylend (X = Date, Y = Severity)

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SUBSIDIARY

Keylend Subsidiaries

Parent Company

Keylend

Financial Services

Website: http://www.keylend.com.au

Company Size: 51-200 employees

No subsidiary data available for this company.

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NEWS

Keylend CyberSecurity News

Latest updates, reports, and threat intel affecting the global network.

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CVE

Latest

Global CVEs (Not Company-Specific)

CVE-2026-54236

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, the fix for CVE-2026-22778, which introduced a sanitize_message helper that strips object-repr memory addresses from error messages before they reach the client, is incomplete: several response paths echo str(exc) directly to clients without calling sanitize_message. The unsanitized sites include the Anthropic API router in vllm/entrypoints/anthropic/api_router.py (the POST /v1/messages and POST /v1/messages/count_tokens handlers), the Server-Sent Events streaming converter in vllm/entrypoints/anthropic/serving.py, and the realtime speech-to-text WebSocket in vllm/entrypoints/speech_to_text/realtime/connection.py. These paths catch the exception inside the route coroutine and construct the JSONResponse themselves, bypassing the sanitizing global FastAPI exception handler, and WebSocket frames do not traverse that handler chain at all. Using the same primitive as the parent issue, an unauthenticated attacker can send malformed image bytes through the Anthropic Messages API image content parts so that PIL.Image.open raises an UnidentifiedImageError whose message contains the BytesIO object repr, leaking the heap memory address verbatim in the error.message field of the response body. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 5.3)

cvss3

Base Score: 5.3

Complexity: LOW

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N

Impact Score

1.4

Exploitability

3.9

REFERENCES

CVE-2026-54235

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: )

cvss4

Base Score: 6.9

Complexity: LOW

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

Impact Score

Exploitability

REFERENCES

CVE-2026-54233

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, vLLM's /v1/audio/transcriptions endpoint limits compressed upload size but not decoded PCM output. A 25MB OPUS file expands to ~14.9GB of float32 PCM at decode time. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 6.5)

cvss3

Base Score: 6.5

Complexity: LOW

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Impact Score

3.6

Exploitability

2.8

REFERENCES

CVE-2026-54232

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.1, the vLLM Dockerfile is vulnerable to a dependency confusion attack through the flashinfer-jit-cache package. The package is installed from a custom index (flashinfer.ai/whl/) using --extra-index-url, but the package name was not registered on PyPI, and UV_INDEX_STRATEGY="unsafe-best-match" is set globally. An attacker who registers flashinfer-jit-cache on PyPI with version 0.6.11.post2 can execute arbitrary code as root during the Docker build and backdoor every resulting container image, enabling exfiltration of all user prompts, API credentials, and model data from production vLLM deployments This vulnerability is fixed in 0.22.1.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: 8.8)

cvss3

Base Score: 8.8

Complexity: LOW

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Impact Score

5.9

Exploitability

2.8

REFERENCES

https://github.com/vllm-project/vllm/security/advisories/GHSA-jrf6-vqxq-pjv2

CVE-2026-53923

SUMMARY

vLLM is an inference and serving engine for large language models (LLMs). From 0.5.5 until 0.23.1rc0, integer truncation of tensor dimensions in vLLM's GGUF dequantize kernels (csrc/quantization/gguf/gguf_kernel.cu) causes partial tensor processing. The output tensor is allocated at full size via torch::empty (uninitialized memory), but the dequantize CUDA kernel processes only a truncated number of elements. The unfilled portion of the output tensor retains whatever was previously in GPU memory. In multi-tenant inference deployments, this residual GPU memory may contain tensor data from other users' inference requests, constituting information disclosure. This vulnerability is fixed in 0.23.1rc0.

Published

Date2026-06-22

Updated

Date2026-06-22

RISK INFORMATION (Score: )

cvss4

Base Score: 5.3

Complexity: LOW

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:L/VI:L/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

Impact Score

Exploitability

REFERENCES

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