What is the official website of Natural Gas by S&P Global Energy ?

The official website of Natural Gas by S&P Global Energy is https://www.spglobal.com/commodity-insights/en/commodities/natural-gas.

What is Natural Gas by S&P Global Energy's cybersecurity risk score?

Natural Gas by S&P Global Energy has an AI-generated cybersecurity risk score of 749 out of 1000, indicating a Moderate security posture according to Rankiteo's assessment.

How many security incidents has Natural Gas by S&P Global Energy experienced?

According to Rankiteo, Natural Gas by S&P Global Energy currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has Natural Gas by S&P Global Energy been affected by any supply chain cyber incidents ?

According to Rankiteo, Natural Gas by S&P Global Energy has not been affected by any supply chain cyber incidents, and no incident IDs are currently listed for the organization.

Does Natural Gas by S&P Global Energy have SOC 2 Type 1 certification ?

According to Rankiteo, Natural Gas by S&P Global Energy is not certified under SOC 2 Type 1.

Does Natural Gas by S&P Global Energy have SOC 2 Type 2 certification ?

According to Rankiteo, Natural Gas by S&P Global Energy does not hold a SOC 2 Type 2 certification.

Does Natural Gas by S&P Global Energy comply with GDPR ?

According to Rankiteo, Natural Gas by S&P Global Energy is not listed as GDPR compliant.

Does Natural Gas by S&P Global Energy have PCI DSS certification ?

According to Rankiteo, Natural Gas by S&P Global Energy does not currently maintain PCI DSS compliance.

Does Natural Gas by S&P Global Energy comply with HIPAA ?

According to Rankiteo, Natural Gas by S&P Global Energy is not compliant with HIPAA regulations.

Does Natural Gas by S&P Global Energy have ISO 27001 certification ?

According to Rankiteo,Natural Gas by S&P Global Energy is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does Natural Gas by S&P Global Energy operate in ?

Natural Gas by S&P Global Energy operates primarily in the Oil and Gas industry.

How many employees does Natural Gas by S&P Global Energy have ?

Natural Gas by S&P Global Energy employs approximately None employees people worldwide.

Does Natural Gas by S&P Global Energy own any subsidiaries ?

Natural Gas by S&P Global Energy presently has no subsidiaries across any sectors.

How many LinkedIn followers does Natural Gas by S&P Global Energy have ?

Natural Gas by S&P Global Energy's official LinkedIn profile has approximately 14,076 followers.

What is the NAICS classification code for Natural Gas by S&P Global Energy ?

Natural Gas by S&P Global Energy is classified under the NAICS code 211, which corresponds to Oil and Gas Extraction.

Does Natural Gas by S&P Global Energy have a Crunchbase profile ?

No, Natural Gas by S&P Global Energy does not have a profile on Crunchbase.

Does Natural Gas by S&P Global Energy have a LinkedIn profile ?

Yes, Natural Gas by S&P Global Energy maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/natural-gas-sp.

How many cybersecurity incidents has Natural Gas by S&P Global Energy experienced ?

As of June 23, 2026, Rankiteo reports that Natural Gas by S&P Global Energy has not experienced any cybersecurity incidents.

How many peer or competitor companies does Natural Gas by S&P Global Energy have ?

Natural Gas by S&P Global Energy has an estimated 10,952 peer or competitor companies worldwide.

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NGSGE

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749

/1000

Moderate

774

/1000

Fair

Natural Gas by S&P Global Energy Vendor Cyber Rating & Cyber Score

spglobal.com

Add Your Compliance Badge

Providing benchmark prices, business-critical market news, fundamental data and insightful market analysis for the #naturalgas and #LNG markets globally.

NGSGE A.I CyberSecurity Scoring

Scoring History

NGSGE

Natural Gas by S&P Global Energy CyberSecurity News & History

Past Incidents

Attack Types

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Type

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Impact

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A.I.

NGSGE 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

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Prediction D

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Underwriter Stats for NGSGE

Incidents vs Oil and Gas Industry Avg (This Year)

No incidents recorded for Natural Gas by S&P Global Energy in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Natural Gas by S&P Global Energy in 2026.

Incident Types NGSGE vs Oil and Gas Industry Avg (This Year)

No incidents recorded for Natural Gas by S&P Global Energy in 2026.

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

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SUBSIDIARY

Natural Gas by S&P Global Energy Subsidiaries

Parent Company

NGSGE

Oil and Gas

Website: https://www.spglobal.com/commodity-insights/en/commodities/natural-gas

Company Size: 1,001-5,000 employees

No subsidiary data available for this company.

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NEWS

Natural Gas by S&P Global Energy 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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