What is the official website of Tempel a Worthington Steel Company ?

The official website of Tempel a Worthington Steel Company is https://http://www.tempel.com.

What is Tempel a Worthington Steel Company's cybersecurity risk score?

Tempel a Worthington Steel Company has an AI-generated cybersecurity risk score of 679 out of 1000, indicating a Weak security posture according to Rankiteo's assessment.

How many security incidents has Tempel a Worthington Steel Company experienced?

According to Rankiteo, Tempel a Worthington Steel Company currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has Tempel a Worthington Steel Company been affected by any supply chain cyber incidents ?

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

Does Tempel a Worthington Steel Company have SOC 2 Type 1 certification ?

According to Rankiteo, Tempel a Worthington Steel Company is not certified under SOC 2 Type 1.

Does Tempel a Worthington Steel Company have SOC 2 Type 2 certification ?

According to Rankiteo, Tempel a Worthington Steel Company does not hold a SOC 2 Type 2 certification.

Does Tempel a Worthington Steel Company comply with GDPR ?

According to Rankiteo, Tempel a Worthington Steel Company is not listed as GDPR compliant.

Does Tempel a Worthington Steel Company have PCI DSS certification ?

According to Rankiteo, Tempel a Worthington Steel Company does not currently maintain PCI DSS compliance.

Does Tempel a Worthington Steel Company comply with HIPAA ?

According to Rankiteo, Tempel a Worthington Steel Company is not compliant with HIPAA regulations.

Does Tempel a Worthington Steel Company have ISO 27001 certification ?

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

Which industry does Tempel a Worthington Steel Company operate in ?

Tempel a Worthington Steel Company operates primarily in the Manufacturing industry.

How many employees does Tempel a Worthington Steel Company have ?

Tempel a Worthington Steel Company employs approximately 616 people worldwide.

Does Tempel a Worthington Steel Company own any subsidiaries ?

Tempel a Worthington Steel Company presently has no subsidiaries across any sectors.

How many LinkedIn followers does Tempel a Worthington Steel Company have ?

Tempel a Worthington Steel Company's official LinkedIn profile has approximately 10,475 followers.

What is the NAICS classification code for Tempel a Worthington Steel Company ?

Tempel a Worthington Steel Company is classified under the NAICS code 30, which corresponds to Manufacturing.

Does Tempel a Worthington Steel Company have a Crunchbase profile ?

No, Tempel a Worthington Steel Company does not have a profile on Crunchbase.

Does Tempel a Worthington Steel Company have a LinkedIn profile ?

Yes, Tempel a Worthington Steel Company maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/tempel.

How many cybersecurity incidents has Tempel a Worthington Steel Company experienced ?

As of June 23, 2026, Rankiteo reports that Tempel a Worthington Steel Company has experienced 1 cybersecurity incidents.

How many peer or competitor companies does Tempel a Worthington Steel Company have ?

Tempel a Worthington Steel Company has an estimated 8,154 peer or competitor companies worldwide.

What types of cybersecurity incidents has Tempel a Worthington Steel Company faced ?

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

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TWSC

Boost Score +25 with badge (5 left)

679

/1000

Weak

704

/1000

Moderate

Tempel a Worthington Steel Company Vendor Cyber Rating & Cyber Score

tempel.com

Add Your Compliance Badge

With over 75+ years of experience, we're a leading manufacturer of high-precision magnetic steel laminations for autos, motors, generators, transformers and beyond.

TWSC A.I CyberSecurity Scoring

Scoring History

TWSC

Tempel a Worthington Steel Company CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

Tempel a Worthingto...

Breach

2/2025

TEM1769208314

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A.I.

TWSC 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 TWSC

Incidents vs Manufacturing Industry Avg (This Year)

No incidents recorded for Tempel a Worthington Steel Company in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Tempel a Worthington Steel Company in 2026.

Incident Types TWSC vs Manufacturing Industry Avg (This Year)

No incidents recorded for Tempel a Worthington Steel Company in 2026.

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

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SUBSIDIARY

Tempel a Worthington Steel Company Subsidiaries

Parent Company

TWSC

Manufacturing

Website: https://http://www.tempel.com

Company Size: 616

No subsidiary data available for this company.

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NEWS

Tempel a Worthington Steel Company CyberSecurity News

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

December 04, 2023 08:00 AM

Worthington Ent. Completes Spin-Off Of Worthington Steel On December 1

Post separation, both companies began trading 'Regular- Way' on 12/1.

Read Article

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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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