What is the official website of Hurricane Electric ?

The official website of Hurricane Electric is http://he.net/.

What is Hurricane Electric's cybersecurity risk score?

Hurricane Electric has an AI-generated cybersecurity risk score of 735 out of 1000, indicating a Moderate security posture according to Rankiteo's assessment.

How many security incidents has Hurricane Electric experienced?

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

Has Hurricane Electric been affected by any supply chain cyber incidents ?

According to Rankiteo, Hurricane Electric has been affected by a supply chain cyber incident involving Hurricane Electric, with the incident ID HURCLO1773109431.

Does Hurricane Electric have SOC 2 Type 1 certification ?

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

Does Hurricane Electric have SOC 2 Type 2 certification ?

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

Does Hurricane Electric comply with GDPR ?

According to Rankiteo, Hurricane Electric is not listed as GDPR compliant.

Does Hurricane Electric have PCI DSS certification ?

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

Does Hurricane Electric comply with HIPAA ?

According to Rankiteo, Hurricane Electric is not compliant with HIPAA regulations.

Does Hurricane Electric have ISO 27001 certification ?

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

Which industry does Hurricane Electric operate in ?

Hurricane Electric operates primarily in the Technology, Information and Internet industry.

How many employees does Hurricane Electric have ?

Hurricane Electric employs approximately 137 people worldwide.

Does Hurricane Electric own any subsidiaries ?

Hurricane Electric presently has no subsidiaries across any sectors.

How many LinkedIn followers does Hurricane Electric have ?

Hurricane Electric's official LinkedIn profile has approximately 9,490 followers.

What is the NAICS classification code for Hurricane Electric ?

Hurricane Electric is classified under the NAICS code 513, which corresponds to Others.

Does Hurricane Electric have a Crunchbase profile ?

No, Hurricane Electric does not have a profile on Crunchbase.

Does Hurricane Electric have a LinkedIn profile ?

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

How many cybersecurity incidents has Hurricane Electric experienced ?

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

How many peer or competitor companies does Hurricane Electric have ?

Hurricane Electric has an estimated 14,827 peer or competitor companies worldwide.

What types of cybersecurity incidents has Hurricane Electric faced ?

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

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Hurricane Electric

Boost Score +25 with badge (5 left)

735

/1000

Moderate

760

/1000

Fair

Hurricane Electric Vendor Cyber Rating & Cyber Score

he.net

Add Your Compliance Badge

Hurricane Electric operates a global internet backbone, providing IP Transit (IPv6/IPv4 wholesale Internet bandwidth). The company operates the world's largest IPv4 and IPv6 global network, with direct connectivity to more than 7000 different networks, including more than 180 Internet peering points, and at 150+ POPs in 103 cities ... in North America (27 states & 7 provinces), Europe, Asia, South America, the Middle East, and Africa. HE.net also operates three carrier-neutral data centers for colocation of customer equipment, in Fremont and San Jose, California. Hurricane Electric was founded in 1994 and is headquartered in Fremont, California.

Hurricane Electric A.I CyberSecurity Scoring

Scoring History

Hurricane Electric

Hurricane Electric CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

Hurricane Electric

Cyber Attack

3/2026

Hurricane Elect...

HURCLO177310943...

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A.I.

Hurricane Electric 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 Hurricane Electric

Incidents vs Technology, Information and Internet Industry Avg (This Year)

Hurricane Electric has 38.27% fewer incidents than the average of same-industry companies with at least one recorded incident.

Incidents vs All-Companies Average (This Year)

Hurricane Electric has 5.66% fewer incidents than the average of all companies with at least one recorded incident.

Incident Types Hurricane Electric vs Technology, Information and Internet Industry Avg (This Year)

Hurricane Electric 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 - Hurricane Electric (X = Date, Y = Severity)

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SUBSIDIARY

Hurricane Electric Subsidiaries

Parent Company

Hurricane Electric

Technology, Information and Internet

Website: http://he.net/

Company Size: 51-200 employees

No subsidiary data available for this company.

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Everforth, Inc. (NYSE: EFOR) is a leading technology and digital engineering company that helps organizations adapt, innovate, and thrive in a world of constant change. Our six solution areas — AI and data, cloud and infrastructure, application and digital engineering, experience, cybersecurity, and enterprise platforms — accelerate time to value for our commercial and federal clients. Powered by proprietary assets, accelerators, and proven expertise, Everforth turns complexity into progress and delivers measurable outcomes. Everforth: Adapt and Thrive™.

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Independiente / Freelance

wikipedia.org

La etimología de la palabra deriva del término medieval inglés usado para un mercenario (free-independiente o lance-lanza), es decir, un caballero que no servía a ningún señor en concreto y cuyos servicios podían ser alquilados por cualquiera. El término fue acuñado inicialmente por Sir Walter Scott (1771-1832) en su reconocido romance histórico Ivanhoe para describir a un "guerrero medieval mercenario". La frase en inglés luego hizo la transición a un sustantivo figurativo alrededor de 1860 y fue luego reconocido como un verbo oficialmente en 1903 por varias autoridades en lingüística tales como el Diccionario Oxford de Inglés. Solamente en tiempos modernos ha mutado el término de un sustantivo (un freelance o un freelancer) y un adverbio (un periodista que trabaja freelance). Esta palabra es empleada como anglicismo en castellano como dos palabras separadas "free lance" (del inglés) o autónomo pero no tiene aplicación como verbo. Fuente: Wikipedia. https://es.wikipedia.org/wiki/Freelance Acerca de Independiente / Freelance Somos una de las comunidades de habla hispana más grandes en LinkedIn para profesionales que eligen trabajar de forma independiente. Un espacio para conectar, compartir recursos y encontrar oportunidades. Publicaciones para Empresas y Reclutadores. Para publicar una búsqueda de talento, por favor envíe los detalles de la oferta a: [email protected] El proceso es simple y asincrónico.

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NEWS

Hurricane Electric CyberSecurity News

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

March 03, 2026 02:25 PM

Hackers Abuse .arpa Top-Level Domain to Host Phishing Scams

Hackers abuse the .arpa Top-Level Domain to host phishing scams, using IPv6 tunnels, reverse DNS tricks, and shadow domains to bypass...

Read Article

January 13, 2026 08:00 AM

Wisconsin Co-op Leader Urges Congress to Renew Crucial Cybersecurity Program

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Read Article

July 07, 2025 07:00 AM

'Cyber security' behind decision to end defense satellite sharing of hurricane data

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Read Article

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June 04, 2025 07:00 AM

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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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