What is the official website of fDi Intelligence ?

The official website of fDi Intelligence is http://www.fDiIntelligence.com.

What is fDi Intelligence's cybersecurity risk score?

fDi Intelligence has an AI-generated cybersecurity risk score of 759 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has fDi Intelligence experienced?

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

Has fDi Intelligence been affected by any supply chain cyber incidents ?

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

Does fDi Intelligence have SOC 2 Type 1 certification ?

According to Rankiteo, fDi Intelligence is not certified under SOC 2 Type 1.

Does fDi Intelligence have SOC 2 Type 2 certification ?

According to Rankiteo, fDi Intelligence does not hold a SOC 2 Type 2 certification.

Does fDi Intelligence comply with GDPR ?

According to Rankiteo, fDi Intelligence is not listed as GDPR compliant.

Does fDi Intelligence have PCI DSS certification ?

According to Rankiteo, fDi Intelligence does not currently maintain PCI DSS compliance.

Does fDi Intelligence comply with HIPAA ?

According to Rankiteo, fDi Intelligence is not compliant with HIPAA regulations.

Does fDi Intelligence have ISO 27001 certification ?

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

Which industry does fDi Intelligence operate in ?

fDi Intelligence operates primarily in the Financial Services industry.

How many employees does fDi Intelligence have ?

fDi Intelligence employs approximately None employees people worldwide.

Does fDi Intelligence own any subsidiaries ?

fDi Intelligence presently has no subsidiaries across any sectors.

How many LinkedIn followers does fDi Intelligence have ?

fDi Intelligence's official LinkedIn profile has approximately 17,971 followers.

What is the NAICS classification code for fDi Intelligence ?

fDi Intelligence is classified under the NAICS code 52, which corresponds to Finance and Insurance.

Does fDi Intelligence have a Crunchbase profile ?

No, fDi Intelligence does not have a profile on Crunchbase.

Does fDi Intelligence have a LinkedIn profile ?

Yes, fDi Intelligence maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/fdi-intelligence.

How many cybersecurity incidents has fDi Intelligence experienced ?

As of June 23, 2026, Rankiteo reports that fDi Intelligence has experienced 10 cybersecurity incidents.

How many peer or competitor companies does fDi Intelligence have ?

fDi Intelligence has an estimated 32,132 peer or competitor companies worldwide.

What types of cybersecurity incidents has fDi Intelligence faced ?

Incident Types: The types of cybersecurity incidents that have occurred include Data Leak, Ransomware and Breach.

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fDi Intelligence

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759

/1000

Fair

784

/1000

Fair

fDi Intelligence Vendor Cyber Rating & Cyber Score

fDiIntelligence.com

Add Your Compliance Badge

Stay ahead with global industry coverage. Through in-depth articles and interviews with industry leaders, our editorial coverage allows readers to stay up-to-date on investment destinations, track the companies and sectors making moves and follow the latest data trends and location rankings.

fDi Intelligence A.I CyberSecurity Scoring

Scoring History

fDi Intelligence

fDi Intelligence CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

Nikkei

Breach

3/2026

WORNOTGOOZOONIK...

Nikkei Asia

Ransomware

100

1/2026

NIK1776752855

fDi Intelligence

Breach

11/2025

NIK311014311104...

fDi Intelligence

Breach

9/2025

NIK170221711072...

fDi Intelligence

Breach

5/2025

NIK073290711062...

fDi Intelligence

Breach

6/2022

NIK399203911052...

fDi Intelligence

Ransomware

100

05/2022

NIK174123522

fDi Intelligence

Data Leak

03/2021

NIK2344291222

fDi Intelligence

Data Leak

05/2020

NIK1332301222

fDi Intelligence

Breach

6/2019

NIK170221711062...

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A.I.

fDi Intelligence 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 fDi Intelligence

Incidents vs Financial Services Industry Avg (This Year)

No incidents recorded for fDi Intelligence in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for fDi Intelligence in 2026.

Incident Types fDi Intelligence vs Financial Services Industry Avg (This Year)

No incidents recorded for fDi Intelligence in 2026.

Incident History - fDi Intelligence (X = Date, Y = Severity)

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SUBSIDIARY

fDi Intelligence Subsidiaries

fDi Intelligence

Financial Services

Website: http://www.fDiIntelligence.com

Company Size: 11-50 employees

Financial TimesNewspaper Publishing

NikkeiNewspaper Publishing

Nikkei AsiaNewspaper Publishing

Nikkei ScoutAsiaInformation Services

Nikkei AmericaInformation Services

Nikkei Market DataFinancial Services

Nikkei Europe LtdNewspaper Publishing

NIKKEI FORUMイベントサービス

FT LiveEvents Services

The BankerBanking

FT StrategiesBusiness Consulting and Services

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NEWS

fDi Intelligence CyberSecurity News

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

January 21, 2026 01:57 PM

Proposed FDI Relaxation Could Reshape India’s Defense Manufacturing

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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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