What is the official website of Emapta Philippines ?

The official website of Emapta Philippines is https://careers.emapta.com.

What is Emapta Philippines's cybersecurity risk score?

Emapta Philippines has an AI-generated cybersecurity risk score of 754 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has Emapta Philippines experienced?

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

Has Emapta Philippines been affected by any supply chain cyber incidents ?

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

Does Emapta Philippines have SOC 2 Type 1 certification ?

According to Rankiteo, Emapta Philippines is not certified under SOC 2 Type 1.

Does Emapta Philippines have SOC 2 Type 2 certification ?

According to Rankiteo, Emapta Philippines does not hold a SOC 2 Type 2 certification.

Does Emapta Philippines comply with GDPR ?

According to Rankiteo, Emapta Philippines is not listed as GDPR compliant.

Does Emapta Philippines have PCI DSS certification ?

According to Rankiteo, Emapta Philippines does not currently maintain PCI DSS compliance.

Does Emapta Philippines comply with HIPAA ?

According to Rankiteo, Emapta Philippines is not compliant with HIPAA regulations.

Does Emapta Philippines have ISO 27001 certification ?

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

Which industry does Emapta Philippines operate in ?

Emapta Philippines operates primarily in the Outsourcing and Offshoring Consulting industry.

How many employees does Emapta Philippines have ?

Emapta Philippines employs approximately None employees people worldwide.

Does Emapta Philippines own any subsidiaries ?

Emapta Philippines presently has no subsidiaries across any sectors.

How many LinkedIn followers does Emapta Philippines have ?

Emapta Philippines's official LinkedIn profile has approximately 8,064 followers.

What is the NAICS classification code for Emapta Philippines ?

Emapta Philippines is classified under the NAICS code 541615, which corresponds to Others.

Does Emapta Philippines have a Crunchbase profile ?

No, Emapta Philippines does not have a profile on Crunchbase.

Does Emapta Philippines have a LinkedIn profile ?

Yes, Emapta Philippines maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/emaptaph.

How many cybersecurity incidents has Emapta Philippines experienced ?

As of June 23, 2026, Rankiteo reports that Emapta Philippines has not experienced any cybersecurity incidents.

How many peer or competitor companies does Emapta Philippines have ?

Emapta Philippines has an estimated 1,157 peer or competitor companies worldwide.

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Emapta Philippines

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754

/1000

Fair

779

/1000

Fair

Emapta Philippines Vendor Cyber Rating & Cyber Score

emapta.com

Add Your Compliance Badge

We prioritize diversity, inclusion, and equality in our workforce. We believe that a diverse team fuels innovation and drives success. We embrace individuals' unique backgrounds, experiences, and perspectives, fostering an environment where everyone feels valued and empowered. Our hiring practices are fair and unbiased, providing equal opportunities for all qualified candidates. We actively seek diverse talent and encourage individuals from underrepresented groups to apply. Join us in creating a workplace that celebrates diversity, inclusion, and equality to drive positive change for all.

Emapta Philippines A.I CyberSecurity Scoring

Scoring History

Emapta Philippines

Emapta Philippines CyberSecurity News & History

Past Incidents

Attack Types

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Impact

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Blog Details

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A.I.

Emapta Philippines 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 Emapta Philippines

Incidents vs Outsourcing and Offshoring Consulting Industry Avg (This Year)

No incidents recorded for Emapta Philippines in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Emapta Philippines in 2026.

Incident Types Emapta Philippines vs Outsourcing and Offshoring Consulting Industry Avg (This Year)

No incidents recorded for Emapta Philippines in 2026.

Incident History - Emapta Philippines (X = Date, Y = Severity)

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SUBSIDIARY

Emapta Philippines Subsidiaries

Emapta Philippines

Outsourcing and Offshoring Consulting

Website: https://careers.emapta.com

Company Size: 5,001-10,000 employees

Emapta GlobalOutsourcing and Offshoring Consulting

Emapta Sri LankaOutsourcing and Offshoring Consulting

Emapta MalaysiaOutsourcing and Offshoring Consulting

Emapta LatamOutsourcing and Offshoring Consulting

Emapta MacedoniaOutsourcing and Offshoring Consulting

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NEWS

Emapta Philippines CyberSecurity News

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

August 27, 2025 07:00 AM

Emapta Named One of HR Asia’s Best Companies to Work for in Asia 2025

MANILA, Philippines, August 27, 2025--Emapta, a global leader in offshore and nearshore dedicated staffing and workforce advisory services,...

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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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