What is the official website of IIFL (India Infoline Group) ?

The official website of IIFL (India Infoline Group) is https://www.indiainfoline.com/.

What is IIFL (India Infoline Group)'s cybersecurity risk score?

IIFL (India Infoline Group) has an AI-generated cybersecurity risk score of 783 out of 1000, indicating a Fair security posture according to Rankiteo's assessment.

How many security incidents has IIFL (India Infoline Group) experienced?

According to Rankiteo, IIFL (India Infoline Group) currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.

Has IIFL (India Infoline Group) been affected by any supply chain cyber incidents ?

According to Rankiteo, IIFL (India Infoline Group) has not been affected by any supply chain cyber incidents, and no incident IDs are currently listed for the organization.

Does IIFL (India Infoline Group) have SOC 2 Type 1 certification ?

According to Rankiteo, IIFL (India Infoline Group) is not certified under SOC 2 Type 1.

Does IIFL (India Infoline Group) have SOC 2 Type 2 certification ?

According to Rankiteo, IIFL (India Infoline Group) does not hold a SOC 2 Type 2 certification.

Does IIFL (India Infoline Group) comply with GDPR ?

According to Rankiteo, IIFL (India Infoline Group) is not listed as GDPR compliant.

Does IIFL (India Infoline Group) have PCI DSS certification ?

According to Rankiteo, IIFL (India Infoline Group) does not currently maintain PCI DSS compliance.

Does IIFL (India Infoline Group) comply with HIPAA ?

According to Rankiteo, IIFL (India Infoline Group) is not compliant with HIPAA regulations.

Does IIFL (India Infoline Group) have ISO 27001 certification ?

According to Rankiteo,IIFL (India Infoline Group) is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.

Which industry does IIFL (India Infoline Group) operate in ?

IIFL (India Infoline Group) operates primarily in the Financial Services industry.

How many employees does IIFL (India Infoline Group) have ?

IIFL (India Infoline Group) employs approximately 14,736 people worldwide.

Does IIFL (India Infoline Group) own any subsidiaries ?

IIFL (India Infoline Group) presently has no subsidiaries across any sectors.

How many LinkedIn followers does IIFL (India Infoline Group) have ?

IIFL (India Infoline Group)'s official LinkedIn profile has approximately 280,510 followers.

What is the NAICS classification code for IIFL (India Infoline Group) ?

IIFL (India Infoline Group) is classified under the NAICS code 52, which corresponds to Finance and Insurance.

Does IIFL (India Infoline Group) have a Crunchbase profile ?

No, IIFL (India Infoline Group) does not have a profile on Crunchbase.

Does IIFL (India Infoline Group) have a LinkedIn profile ?

Yes, IIFL (India Infoline Group) maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/iifl.

How many cybersecurity incidents has IIFL (India Infoline Group) experienced ?

As of June 23, 2026, Rankiteo reports that IIFL (India Infoline Group) has not experienced any cybersecurity incidents.

How many peer or competitor companies does IIFL (India Infoline Group) have ?

IIFL (India Infoline Group) has an estimated 32,128 peer or competitor companies worldwide.

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783

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Fair

808

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Good

IIFL (India Infoline Group) Vendor Cyber Rating & Cyber Score

indiainfoline.com

Add Your Compliance Badge

IIFL group is one of India's largest diversified financial services conglomerates with three listed entities - IIFL Finance, IIFL Securities and 360 ONE Wealth & Asset Management. Founded in 1995 by Nirmal Jain as a small research house, today IIFL Group employs over 40000 people and caters to over 10 million customers through various financial products and services. Our strength has been to continuously innovate and reinvent ourselves. IIFL’s evolution from an entrepreneurial start-up in 1995 to a full range diversified financial services group is a story of steady growth by adapting to the dynamic business environment, without losing focus on our core domain of financial services. Today IIFL Group manages assets over $50 billion and

I A.I CyberSecurity Scoring

Scoring History

IIFL (India Infoline Group) 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.

I 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 I

Incidents vs Financial Services Industry Avg (This Year)

No incidents recorded for IIFL (India Infoline Group) in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for IIFL (India Infoline Group) in 2026.

Incident Types I vs Financial Services Industry Avg (This Year)

No incidents recorded for IIFL (India Infoline Group) in 2026.

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

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SUBSIDIARY

IIFL (India Infoline Group) Subsidiaries

I

Financial Services

Website: https://www.indiainfoline.com/

Company Size: 10,000+ employees

IIFL Realty Ltd.Real Estate

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NEWS

IIFL (India Infoline Group) CyberSecurity News

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

January 10, 2026 10:41 AM

Compliance Challenges For Financial Advisors: Key Compliance Responsibilities

In India's regulated market, financial advisors must comply with SEBI, exchanges, KYC-AML and cybersecurity norms to protect clients, build trust,...

Read Article

October 27, 2025 07:00 AM

Indian IT Sector Analysis: Trends, Growth & Insights | IIFL Capital

The Indian IT sector is poised at a challenging crossroads as we are already in the earnings season for the first quarter of the fiscal year 2024.

Read Article

September 19, 2025 07:00 AM

iValue Infosolutions Limited - A Leading Enterprise Tech Player

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Read Article

March 19, 2025 01:47 PM

Future Trends of Sub-Broking- What to Know | IIFL Capital

Explore the future of sub-broking in India with trends in digital transformation, AI use, and shifting investor needs in this comprehensive industry...

Read Article

March 17, 2025 07:00 AM

Wipro Restructures Business Lines to Boost AI, Cloud, and Digital Transformation

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November 25, 2024 08:21 PM

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December 17, 2023 08:00 AM

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November 23, 2022 08:00 AM

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October 27, 2021 07:00 AM

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CISO Movement: ICICI Securities has roped in cybersecurity leader Sanjay Tiwari as their Head - Information Security (CISO).

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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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