What is the official website of Independiente / Freelance ?

The official website of Independiente / Freelance is https://es.wikipedia.org/wiki/Freelance.

What is Independiente / Freelance's cybersecurity risk score?

Independiente / Freelance has an AI-generated cybersecurity risk score of 800 out of 1000, indicating a Good security posture according to Rankiteo's assessment.

How many security incidents has Independiente / Freelance experienced?

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

Has Independiente / Freelance been affected by any supply chain cyber incidents ?

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

Does Independiente / Freelance have SOC 2 Type 1 certification ?

According to Rankiteo, Independiente / Freelance is not certified under SOC 2 Type 1.

Does Independiente / Freelance have SOC 2 Type 2 certification ?

According to Rankiteo, Independiente / Freelance does not hold a SOC 2 Type 2 certification.

Does Independiente / Freelance comply with GDPR ?

According to Rankiteo, Independiente / Freelance is not listed as GDPR compliant.

Does Independiente / Freelance have PCI DSS certification ?

According to Rankiteo, Independiente / Freelance does not currently maintain PCI DSS compliance.

Does Independiente / Freelance comply with HIPAA ?

According to Rankiteo, Independiente / Freelance is not compliant with HIPAA regulations.

Does Independiente / Freelance have ISO 27001 certification ?

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

Which industry does Independiente / Freelance operate in ?

Independiente / Freelance operates primarily in the Technology, Information and Internet industry.

How many employees does Independiente / Freelance have ?

Independiente / Freelance employs approximately 53,205 people worldwide.

Does Independiente / Freelance own any subsidiaries ?

Independiente / Freelance presently has no subsidiaries across any sectors.

How many LinkedIn followers does Independiente / Freelance have ?

Independiente / Freelance's official LinkedIn profile has approximately 132,627 followers.

What is the NAICS classification code for Independiente / Freelance ?

Independiente / Freelance is classified under the NAICS code 513, which corresponds to Others.

Does Independiente / Freelance have a Crunchbase profile ?

No, Independiente / Freelance does not have a profile on Crunchbase.

Does Independiente / Freelance have a LinkedIn profile ?

Yes, Independiente / Freelance maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/independiente-freelance.

How many cybersecurity incidents has Independiente / Freelance experienced ?

As of June 23, 2026, Rankiteo reports that Independiente / Freelance has not experienced any cybersecurity incidents.

How many peer or competitor companies does Independiente / Freelance have ?

Independiente / Freelance has an estimated 14,827 peer or competitor companies worldwide.

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800

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825

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Good

Independiente / Freelance Vendor Cyber Rating & Cyber Score

wikipedia.org

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La etimología de la palabra deriva del término medieval inglés usado para un mercenario (free-independiente o lance-lanza), es decir, un caballero que no servía a ningún señor en concreto y cuyos servicios podían ser alquilados por cualquiera. El término fue acuñado inicialmente por Sir Walter Scott (1771-1832) en su reconocido romance histórico Ivanhoe para describir a un "guerrero medieval mercenario". La frase en inglés luego hizo la transición a un sustantivo figurativo alrededor de 1860 y fue luego reconocido como un verbo oficialmente en 1903 por varias autoridades en lingüística tales como el Diccionario Oxford de Inglés. Solamente en tiempos modernos ha mutado el término de un sustantivo (un freelance o un freelancer) y un

IF A.I CyberSecurity Scoring

Scoring History

Independiente / Freelance CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

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No data available

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A.I.

IF 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 IF

Incidents vs Technology, Information and Internet Industry Avg (This Year)

No incidents recorded for Independiente / Freelance in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Independiente / Freelance in 2026.

Incident Types IF vs Technology, Information and Internet Industry Avg (This Year)

No incidents recorded for Independiente / Freelance in 2026.

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

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SUBSIDIARY

Independiente / Freelance Subsidiaries

Parent Company

IF

Technology, Information and Internet

Website: https://es.wikipedia.org/wiki/Freelance

Company Size: 10,001+ employees

No subsidiary data available for this company.

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NEWS

Independiente / Freelance 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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