What is the official website of EPSYL - ALCEN Group ?

The official website of EPSYL - ALCEN Group is https://www.epsyl-alcen.com/.

What is EPSYL - ALCEN Group's cybersecurity risk score?

EPSYL - ALCEN Group has an AI-generated cybersecurity risk score of 752 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has EPSYL - ALCEN Group experienced?

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

Has EPSYL - ALCEN Group been affected by any supply chain cyber incidents ?

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

Does EPSYL - ALCEN Group have SOC 2 Type 1 certification ?

According to Rankiteo, EPSYL - ALCEN Group is not certified under SOC 2 Type 1.

Does EPSYL - ALCEN Group have SOC 2 Type 2 certification ?

According to Rankiteo, EPSYL - ALCEN Group does not hold a SOC 2 Type 2 certification.

Does EPSYL - ALCEN Group comply with GDPR ?

According to Rankiteo, EPSYL - ALCEN Group is not listed as GDPR compliant.

Does EPSYL - ALCEN Group have PCI DSS certification ?

According to Rankiteo, EPSYL - ALCEN Group does not currently maintain PCI DSS compliance.

Does EPSYL - ALCEN Group comply with HIPAA ?

According to Rankiteo, EPSYL - ALCEN Group is not compliant with HIPAA regulations.

Does EPSYL - ALCEN Group have ISO 27001 certification ?

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

Which industry does EPSYL - ALCEN Group operate in ?

EPSYL - ALCEN Group operates primarily in the Research Services industry.

How many employees does EPSYL - ALCEN Group have ?

EPSYL - ALCEN Group employs approximately 231 people worldwide.

Does EPSYL - ALCEN Group own any subsidiaries ?

EPSYL - ALCEN Group presently has no subsidiaries across any sectors.

How many LinkedIn followers does EPSYL - ALCEN Group have ?

EPSYL - ALCEN Group's official LinkedIn profile has approximately 10,695 followers.

What is the NAICS classification code for EPSYL - ALCEN Group ?

EPSYL - ALCEN Group is classified under the NAICS code 5417, which corresponds to Scientific Research and Development Services.

Does EPSYL - ALCEN Group have a Crunchbase profile ?

No, EPSYL - ALCEN Group does not have a profile on Crunchbase.

Does EPSYL - ALCEN Group have a LinkedIn profile ?

Yes, EPSYL - ALCEN Group maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/epsyl-ingenierie.

How many cybersecurity incidents has EPSYL - ALCEN Group experienced ?

As of June 23, 2026, Rankiteo reports that EPSYL - ALCEN Group has not experienced any cybersecurity incidents.

How many peer or competitor companies does EPSYL - ALCEN Group have ?

EPSYL - ALCEN Group has an estimated 5,816 peer or competitor companies worldwide.

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752

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Fair

777

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EPSYL - ALCEN Group Vendor Cyber Rating & Cyber Score

epsyl-alcen.com

Add Your Compliance Badge

EPSYL is a company of the ALCEN group, meeting various needs in systems design and optimization for large industrial sectors (Nuclear, Aeronautics, Transport). EPSILON conducts studies for its customers and for its own products and undertakes complex projects in design and implementation with the support and industrial power of the ALCEN group. By combining its specialist skills in multi-physics modeling/simulation and its deep understanding of systems, EPSILON can drastically shorten the time between the upstream phases of projects and downstream validation tests. EPSILON has chosen to focus on multi-physics questions combining thermal, fluidic and mechanical issues. In this respect, EPSILON wishes to strengthen its thermal

EAG A.I CyberSecurity Scoring

Scoring History

EAG

EPSYL - ALCEN Group CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

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Impact

Seen

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No data available

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A.I.

EAG 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 EAG

Incidents vs Research Services Industry Avg (This Year)

No incidents recorded for EPSYL - ALCEN Group in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for EPSYL - ALCEN Group in 2026.

Incident Types EAG vs Research Services Industry Avg (This Year)

No incidents recorded for EPSYL - ALCEN Group in 2026.

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

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SUBSIDIARY

EPSYL - ALCEN Group Subsidiaries

EAG

Research Services

Website: https://www.epsyl-alcen.com/

Company Size: 231

ALCENManufacturing

TRONICOAppliances, Electrical, and Electronics Manufacturing

TAME-POWERElectric Power Transmission, Control, and Distribution

TAME-CAREMedical Equipment Manufacturing

TAME-WATEREnvironmental Services

ALSEAMARDefense and Space Manufacturing

SeaExplorer gliderRenewable Energy Semiconductor Manufacturing

PMB-ALCENMedical Equipment Manufacturing

iMiGiNE - PMBMedical Equipment Manufacturing

PMB-ALCENMedical Equipment Manufacturing

BMTI - Alcen GroupOil and Gas

ADR - ALCENDefense and Space Manufacturing

ITOPPDefense and Space Manufacturing

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NEWS

EPSYL - ALCEN Group 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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