What is the official website of heise online ?

The official website of heise online is https://www.heise.de.

What is heise online's cybersecurity risk score?

heise online has an AI-generated cybersecurity risk score of 750 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has heise online experienced?

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

Has heise online been affected by any supply chain cyber incidents ?

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

Does heise online have SOC 2 Type 1 certification ?

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

Does heise online have SOC 2 Type 2 certification ?

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

Does heise online comply with GDPR ?

According to Rankiteo, heise online is not listed as GDPR compliant.

Does heise online have PCI DSS certification ?

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

Does heise online comply with HIPAA ?

According to Rankiteo, heise online is not compliant with HIPAA regulations.

Does heise online have ISO 27001 certification ?

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

Which industry does heise online operate in ?

heise online operates primarily in the Book and Periodical Publishing industry.

How many employees does heise online have ?

heise online employs approximately 53 people worldwide.

Does heise online own any subsidiaries ?

heise online presently has no subsidiaries across any sectors.

How many LinkedIn followers does heise online have ?

heise online's official LinkedIn profile has approximately 87,727 followers.

What is the NAICS classification code for heise online ?

heise online is classified under the NAICS code 511, which corresponds to Publishing Industries (except Internet).

Does heise online have a Crunchbase profile ?

No, heise online does not have a profile on Crunchbase.

Does heise online have a LinkedIn profile ?

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

How many cybersecurity incidents has heise online experienced ?

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

How many peer or competitor companies does heise online have ?

heise online has an estimated 5,126 peer or competitor companies worldwide.

What types of cybersecurity incidents has heise online faced ?

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

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heise online

Boost Score +25 with badge (5 left)

750

/1000

Fair

775

/1000

Fair

heise online Vendor Cyber Rating & Cyber Score

heise.de

Add Your Compliance Badge

heise online (www.heise.de) zählt zu den meistgenutzten IT-Nachrichtendiensten in Deutschland. In dem redaktionsübergreifenden Internet-Auftritt finden IT-Interessierte tagesaktuelle Informationen aus den Redaktionen der Zeitschriftentitel c't, iX, Mac & i, Make und Technology Review sowie des Online-Magazins Telepolis. Zum Impressum: https://www.heise.de/impressum.html Unsere Datenschutzerklärung: https://www.heise.de/privacy

heise online A.I CyberSecurity Scoring

Scoring History

heise online

heise online CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

heise online

Vulnerability

100

6/2026

HEI1782211360

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A.I.

heise online 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 heise online

Incidents vs Book and Periodical Publishing Industry Avg (This Year)

heise online has 0.0% fewer incidents than the average of same-industry companies with at least one recorded incident.

Incidents vs All-Companies Average (This Year)

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

Incident Types heise online vs Book and Periodical Publishing Industry Avg (This Year)

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

Incident History - heise online (X = Date, Y = Severity)

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SUBSIDIARY

heise online Subsidiaries

heise online

Book and Periodical Publishing

Website: https://www.heise.de

Company Size: 501-1,000 employees

secIT by heiseInformation Technology & Services

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heise online Similar Companies

Forbes

forbes.com

Forbes Media is a global media, branding and technology company, with a focus on news and information about business, investing, technology, entrepreneurship, leadership and affluent lifestyles. The company publishes Forbes, Forbes Asia, and Forbes Europe magazines as well as Forbes.com. The Forbes brand today reaches more than 94 million people worldwide with its business message each month through its magazines and 37 licensed local editions around the globe, Forbes.com, TV, conferences, research, social and mobile platforms. Forbes Media’s brand extensions include conferences, real estate, education, financial services, and technology license agreements. Forbes is an equal opportunity employer.

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NEWS

heise online 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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