What is the official website of NAVLIN Price & Access Data ?

The official website of NAVLIN Price & Access Data is https://www.NAVLIN.com.

What is NAVLIN Price & Access Data's cybersecurity risk score?

NAVLIN Price & Access Data has an AI-generated cybersecurity risk score of 753 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has NAVLIN Price & Access Data experienced?

According to Rankiteo, NAVLIN Price & Access Data currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has NAVLIN Price & Access Data been affected by any supply chain cyber incidents ?

According to Rankiteo, NAVLIN Price & Access Data has not been affected by any supply chain cyber incidents, and no incident IDs are currently listed for the organization.

Does NAVLIN Price & Access Data have SOC 2 Type 1 certification ?

According to Rankiteo, NAVLIN Price & Access Data is not certified under SOC 2 Type 1.

Does NAVLIN Price & Access Data have SOC 2 Type 2 certification ?

According to Rankiteo, NAVLIN Price & Access Data does not hold a SOC 2 Type 2 certification.

Does NAVLIN Price & Access Data comply with GDPR ?

According to Rankiteo, NAVLIN Price & Access Data is not listed as GDPR compliant.

Does NAVLIN Price & Access Data have PCI DSS certification ?

According to Rankiteo, NAVLIN Price & Access Data does not currently maintain PCI DSS compliance.

Does NAVLIN Price & Access Data comply with HIPAA ?

According to Rankiteo, NAVLIN Price & Access Data is not compliant with HIPAA regulations.

Does NAVLIN Price & Access Data have ISO 27001 certification ?

According to Rankiteo,NAVLIN Price & Access Data is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does NAVLIN Price & Access Data operate in ?

NAVLIN Price & Access Data operates primarily in the Pharmaceutical Manufacturing industry.

How many employees does NAVLIN Price & Access Data have ?

NAVLIN Price & Access Data employs approximately 0 people worldwide.

Does NAVLIN Price & Access Data own any subsidiaries ?

NAVLIN Price & Access Data presently has no subsidiaries across any sectors.

How many LinkedIn followers does NAVLIN Price & Access Data have ?

NAVLIN Price & Access Data's official LinkedIn profile has approximately 873 followers.

What is the NAICS classification code for NAVLIN Price & Access Data ?

NAVLIN Price & Access Data is classified under the NAICS code 3254, which corresponds to Pharmaceutical and Medicine Manufacturing.

Does NAVLIN Price & Access Data have a Crunchbase profile ?

No, NAVLIN Price & Access Data does not have a profile on Crunchbase.

Does NAVLIN Price & Access Data have a LinkedIn profile ?

Yes, NAVLIN Price & Access Data maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/pricentric-one-by-eversana.

How many cybersecurity incidents has NAVLIN Price & Access Data experienced ?

As of June 23, 2026, Rankiteo reports that NAVLIN Price & Access Data has experienced 1 cybersecurity incidents.

How many peer or competitor companies does NAVLIN Price & Access Data have ?

NAVLIN Price & Access Data has an estimated 5,695 peer or competitor companies worldwide.

What types of cybersecurity incidents has NAVLIN Price & Access Data faced ?

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

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NPAD

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753

/1000

Fair

778

/1000

Fair

NAVLIN Price & Access Data Vendor Cyber Rating & Cyber Score

navlin.com

Add Your Compliance Badge

NAVLIN by EVERSANATM is a powerful intelligence tool that provides near real-time updates to drug price (list / net / tender), reimbursement, and cost of treatment information at the indication level across 95+ markets and 250+ therapeutic areas. The software technology supports the needs of both large pharma who need enterprise level data as well as small start-ups looking for niche therapeutic areas. More than just data, Pricentric delivers instant market access insight and pricing analytics.

NPAD A.I CyberSecurity Scoring

Scoring History

NPAD

NAVLIN Price & Access Data CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

NAVLIN Price & Acce...

Breach

4/2019

EVE238072625

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A.I.

NPAD 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 NPAD

Incidents vs Pharmaceutical Manufacturing Industry Avg (This Year)

No incidents recorded for NAVLIN Price & Access Data in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for NAVLIN Price & Access Data in 2026.

Incident Types NPAD vs Pharmaceutical Manufacturing Industry Avg (This Year)

No incidents recorded for NAVLIN Price & Access Data in 2026.

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

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SUBSIDIARY

NAVLIN Price & Access Data Subsidiaries

NPAD

Pharmaceutical Manufacturing

Website: https://www.NAVLIN.com

Company Size: 0

EVERSANAPharmaceutical Manufacturing

EVERSANA INTOUCHAdvertising Services

Seeker Health by EVERSANAPharmaceutical Manufacturing

NAVLIN by EVERSANAPharmaceutical Manufacturing

EVERSANA ENGAGEPharmaceutical Manufacturing

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NEWS

NAVLIN Price & Access Data 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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