What is the official website of Ibrahim Fibres Ltd. ?

The official website of Ibrahim Fibres Ltd. is http://www.igcpk.com.

What is Ibrahim Fibres Ltd.'s cybersecurity risk score?

Ibrahim Fibres Ltd. has an AI-generated cybersecurity risk score of 760 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has Ibrahim Fibres Ltd. experienced?

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

Has Ibrahim Fibres Ltd. been affected by any supply chain cyber incidents ?

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

Does Ibrahim Fibres Ltd. have SOC 2 Type 1 certification ?

According to Rankiteo, Ibrahim Fibres Ltd. is not certified under SOC 2 Type 1.

Does Ibrahim Fibres Ltd. have SOC 2 Type 2 certification ?

According to Rankiteo, Ibrahim Fibres Ltd. does not hold a SOC 2 Type 2 certification.

Does Ibrahim Fibres Ltd. comply with GDPR ?

According to Rankiteo, Ibrahim Fibres Ltd. is not listed as GDPR compliant.

Does Ibrahim Fibres Ltd. have PCI DSS certification ?

According to Rankiteo, Ibrahim Fibres Ltd. does not currently maintain PCI DSS compliance.

Does Ibrahim Fibres Ltd. comply with HIPAA ?

According to Rankiteo, Ibrahim Fibres Ltd. is not compliant with HIPAA regulations.

Does Ibrahim Fibres Ltd. have ISO 27001 certification ?

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

Which industry does Ibrahim Fibres Ltd. operate in ?

Ibrahim Fibres Ltd. operates primarily in the Textile Manufacturing industry.

How many employees does Ibrahim Fibres Ltd. have ?

Ibrahim Fibres Ltd. employs approximately 967 people worldwide.

Does Ibrahim Fibres Ltd. own any subsidiaries ?

Ibrahim Fibres Ltd. presently has no subsidiaries across any sectors.

How many LinkedIn followers does Ibrahim Fibres Ltd. have ?

Ibrahim Fibres Ltd.'s official LinkedIn profile has approximately 39,431 followers.

What is the NAICS classification code for Ibrahim Fibres Ltd. ?

Ibrahim Fibres Ltd. is classified under the NAICS code 313, which corresponds to Textile Mills.

Does Ibrahim Fibres Ltd. have a Crunchbase profile ?

No, Ibrahim Fibres Ltd. does not have a profile on Crunchbase.

Does Ibrahim Fibres Ltd. have a LinkedIn profile ?

Yes, Ibrahim Fibres Ltd. maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/ibrahim-fibres-ltd.

How many cybersecurity incidents has Ibrahim Fibres Ltd. experienced ?

As of June 23, 2026, Rankiteo reports that Ibrahim Fibres Ltd. has not experienced any cybersecurity incidents.

How many peer or competitor companies does Ibrahim Fibres Ltd. have ?

Ibrahim Fibres Ltd. has an estimated 2,206 peer or competitor companies worldwide.

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IFL

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760

/1000

Fair

785

/1000

Fair

Ibrahim Fibres Ltd. Vendor Cyber Rating & Cyber Score

igcpk.com

Add Your Compliance Badge

IFL is the largest producer of Polyester Staple Fibre in Pakistan and a leading textile manufacturing company in the country. Our business group is diversified in finance and owns one of the oldest banks in the country- Allied Bank Limited. Polyester Plant manufacturing operations consist of three production plants located within the same premises, at 38th K.M. Faisalabad – Sheikhupura Road, Faisalabad and are spread over an area of more than 100 acres of land with a capacity to produce 390,600 tons per annum of Polyester Staple Fibre (PSF). Spun Yarn Division of Ibrahim Fibres Limited consists of four projects: TP1 (Textile Plant 1) Total installed capacity of 58,080 spindles. TP2 (Textile Plant 2) Total installed capacity

IFL A.I CyberSecurity Scoring

Scoring History

IFL

Ibrahim Fibres Ltd. CyberSecurity News & History

Past Incidents

Attack Types

Entity

Type

Severity

Impact

Seen

Blog Details

Supply Chain Source

Incident Details

View

No data available

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A.I.

IFL 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 IFL

Incidents vs Textile Manufacturing Industry Avg (This Year)

No incidents recorded for Ibrahim Fibres Ltd. in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Ibrahim Fibres Ltd. in 2026.

Incident Types IFL vs Textile Manufacturing Industry Avg (This Year)

No incidents recorded for Ibrahim Fibres Ltd. in 2026.

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

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SUBSIDIARY

Ibrahim Fibres Ltd. Subsidiaries

Parent Company

IFL

Textile Manufacturing

Website: http://www.igcpk.com

Company Size: 967

No subsidiary data available for this company.

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Ibrahim Fibres Ltd. Similar Companies

Mohawk Industries

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Are you looking for more? At Mohawk Industries, we’re committed to more – more customer solutions, more process improvements, more sustainable manufacturing and more opportunities for our team. As a Fortune 500 global flooring leader with some of the best-known brands in the industry, Mohawk is a great place to start or develop your career with an emphasis on more of what’s important to you. Whether you want to lead more, innovate more, learn more or create more, you can find your more with Mohawk.

Shaw Industries

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Shaw Industries Group, Inc. is a leader in flooring and other surface solutions designed for residential housing, commercial spaces and outdoor environments. Leveraging strengths in design, innovation and operational excellence, the company takes a people-centered, customer-focused, and growth-minded approach to meet diverse market needs. It creates differentiated customer experiences through its expansive portfolio of brands: Anderson Tuftex, COREtec, Shaw Floors, Patcraft, Philadelphia Commercial, Shaw Contract, Shaw Sports Turf, Shawgrass, Southwest Greens, Watershed Geo and more. Headquartered in Dalton, Georgia, Shaw is a wholly owned subsidiary of Berkshire Hathaway, Inc. with approximately $6 billion in annual sales and 18,000 associates worldwide. Interested in a career with Shaw? Browse open positions at https://careers.shawinc.com/.

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NEWS

Ibrahim Fibres Ltd. CyberSecurity News

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

January 16, 2026 08:00 AM

Galaxy Backbone prioritises infrastructure, cybersecurity in Nigeria’s digital drive

Galaxy Backbone has said it is placing renewed emphasis on digital infrastructure and cybersecurity as it marks two decades of supporting...

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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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