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Established in 1903, Taj is The Indian Hotels Company Limited’s (IHCL) iconic brand for the world’s most discerning travellers seeking luxury and authentic experiences. Taj has been rated as India’s Strongest Brand across all sectors for an unprecedented fourth time and also as the World’s Strongest Hotel Brand for the third consecutive year in 2024 by Brand Finance. From landmark city addresses to enchanting jungle safaris, and from idyllic resorts to authentic living Grand Palaces, each Taj hotel offers an unrivalled fusion of warm Indian hospitality, world-class service and modern luxury. Taj's unique portfolio comprises hotels across India, North America, United Kingdom, Africa, Middle East, Sri Lanka, Maldives and Nepal.

Taj Hotels A.I CyberSecurity Scoring

Taj Hotels

Company Details

Linkedin ID:

taj-hotels

Employees number:

24,292

Number of followers:

876,798

NAICS:

7211

Industry Type:

Hospitality

Homepage:

tajhotels.com

IP Addresses:

0

Company ID:

TAJ_2265852

Scan Status:

In-progress

AI scoreTaj Hotels Risk Score (AI oriented)

Between 800 and 849

https://images.rankiteo.com/companyimages/taj-hotels.jpeg
Taj Hotels Hospitality
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globalscoreTaj Hotels Global Score (TPRM)

XXXX

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Taj Hotels Hospitality
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Taj Hotels Company CyberSecurity News & History

Past Incidents
5
Attack Types
3
EntityTypeSeverityImpactSeenBlog DetailsSupply Chain SourceIncident DetailsView
Taj HotelsCyber Attack100511/2025NA
Rankiteo Explanation :
Attack threatening the organization’s existence

Description: Tata Motors, the parent company of Jaguar Land Rover, suffered a severe cyberattack that forced a shutdown of production in the UK. The incident resulted in exceptional costs of £196 million ($258 million) directly tied to the attack, while revenue plummeted from £6.5 billion to £4.9 billion ($8.5 billion to $6.4 billion) year-over-year. The financial strain was partially offset by sales growth in India, but the CFO acknowledged the attack as a major operational disruption, highlighting its escalating frequency across industries. The attack’s scale costing the company an estimated £1.8 billion ($2.35 billion) in total losses underscores its catastrophic impact on production, supply chains, and profitability. The prolonged outage and financial hemorrhage align with high-severity cyber incidents that threaten organizational viability, particularly in manufacturing-heavy sectors like automotive.

Taj HotelsBreach10055/2025NA
Rankiteo Explanation :
Attack threatening the organization’s existence

Description: Tata Motors suffered a severe data breach exposing 70TB of sensitive corporate and customer data due to misconfigured AWS access, a vulnerability likely exacerbated by unauthorized 'shadow AI' deployments. The breach, reported by Undercode News in October 2025, highlights how employees bypassing IT protocols such as using unvetted AI tools for analytics or automation can introduce critical security gaps. The exposed data may include proprietary intellectual property, financial records, employee details, and customer information, posing risks of regulatory fines, reputational damage, and competitive disadvantages. The incident aligns with broader industry warnings about shadow AI creating blind spots in governance, where unsanctioned tools (e.g., generative AI platforms) grant third-party access to confidential data without oversight. The breach’s scale and the involvement of cloud misconfigurations often linked to unauthorized tool integrations underscore the systemic risks of ungoverned AI adoption in enterprise environments.

Taj HotelsRansomware10044/2025NA
Rankiteo Explanation :
Attack with significant impact with customers data leaks

Description: Tata Technologies, a global engineering and product development digital services company, was one of the victims of the Hunters International cybercriminal group. During their operations, before considering a move away from ransomware to purely data theft extortion schemes, Hunters International compromised and possibly extracted sensitive data from the company. The exact nature of the data stolen or the full consequences of the breach were not detailed, but given the profile of the company and the typical operational patterns of ransomware groups, the impact could be significant in terms of financial loss, intellectual property theft, and reputational damage.

Taj HotelsRansomware8531/2025NA
Rankiteo Explanation :
Attack with significant impact with internal employee data leaks

Description: The Hunters International ransomware gang targeted Tata Technologies in a January cyberattack, claiming to have stolen 1.4TB of data, disrupting IT systems but not affecting client delivery services. The impact on operations was reported as minimal, with no client data or critical service disruptions mentioned, but the breach included a threat to release the stolen files if no ransom was paid.

Taj HotelsRansomware85310/2022NA
Rankiteo Explanation :
Attack with significant impact with internal employee data leaks

Description: Tata Technologies, a subsidiary of Tata Motors, encountered a ransomware attack leading to the suspension of certain IT services as a precautionary measure. The incident targeted a segment of its IT infrastructure. While client delivery services remained unaffected, the extent of data breach, if any, was not disclosed. Notably, this follows a previous cyber incident in October 2022 where Tata Power faced a ransomware attack, with subsequent leakage of stolen information by Hive ransomware gang including sensitive employee and operational data.

Tata Motors (Jaguar Land Rover)
Cyber Attack
Severity: 100
Impact: 5
Seen: 11/2025
Blog:
Supply Chain Source: NA
Rankiteo Explanation
Attack threatening the organization’s existence

Description: Tata Motors, the parent company of Jaguar Land Rover, suffered a severe cyberattack that forced a shutdown of production in the UK. The incident resulted in exceptional costs of £196 million ($258 million) directly tied to the attack, while revenue plummeted from £6.5 billion to £4.9 billion ($8.5 billion to $6.4 billion) year-over-year. The financial strain was partially offset by sales growth in India, but the CFO acknowledged the attack as a major operational disruption, highlighting its escalating frequency across industries. The attack’s scale costing the company an estimated £1.8 billion ($2.35 billion) in total losses underscores its catastrophic impact on production, supply chains, and profitability. The prolonged outage and financial hemorrhage align with high-severity cyber incidents that threaten organizational viability, particularly in manufacturing-heavy sectors like automotive.

Tata Motors
Breach
Severity: 100
Impact: 5
Seen: 5/2025
Blog:
Supply Chain Source: NA
Rankiteo Explanation
Attack threatening the organization’s existence

Description: Tata Motors suffered a severe data breach exposing 70TB of sensitive corporate and customer data due to misconfigured AWS access, a vulnerability likely exacerbated by unauthorized 'shadow AI' deployments. The breach, reported by Undercode News in October 2025, highlights how employees bypassing IT protocols such as using unvetted AI tools for analytics or automation can introduce critical security gaps. The exposed data may include proprietary intellectual property, financial records, employee details, and customer information, posing risks of regulatory fines, reputational damage, and competitive disadvantages. The incident aligns with broader industry warnings about shadow AI creating blind spots in governance, where unsanctioned tools (e.g., generative AI platforms) grant third-party access to confidential data without oversight. The breach’s scale and the involvement of cloud misconfigurations often linked to unauthorized tool integrations underscore the systemic risks of ungoverned AI adoption in enterprise environments.

Tata Technologies
Ransomware
Severity: 100
Impact: 4
Seen: 4/2025
Blog:
Supply Chain Source: NA
Rankiteo Explanation
Attack with significant impact with customers data leaks

Description: Tata Technologies, a global engineering and product development digital services company, was one of the victims of the Hunters International cybercriminal group. During their operations, before considering a move away from ransomware to purely data theft extortion schemes, Hunters International compromised and possibly extracted sensitive data from the company. The exact nature of the data stolen or the full consequences of the breach were not detailed, but given the profile of the company and the typical operational patterns of ransomware groups, the impact could be significant in terms of financial loss, intellectual property theft, and reputational damage.

Tata Technologies
Ransomware
Severity: 85
Impact: 3
Seen: 1/2025
Blog:
Supply Chain Source: NA
Rankiteo Explanation
Attack with significant impact with internal employee data leaks

Description: The Hunters International ransomware gang targeted Tata Technologies in a January cyberattack, claiming to have stolen 1.4TB of data, disrupting IT systems but not affecting client delivery services. The impact on operations was reported as minimal, with no client data or critical service disruptions mentioned, but the breach included a threat to release the stolen files if no ransom was paid.

Tata Technologies
Ransomware
Severity: 85
Impact: 3
Seen: 10/2022
Blog:
Supply Chain Source: NA
Rankiteo Explanation
Attack with significant impact with internal employee data leaks

Description: Tata Technologies, a subsidiary of Tata Motors, encountered a ransomware attack leading to the suspension of certain IT services as a precautionary measure. The incident targeted a segment of its IT infrastructure. While client delivery services remained unaffected, the extent of data breach, if any, was not disclosed. Notably, this follows a previous cyber incident in October 2022 where Tata Power faced a ransomware attack, with subsequent leakage of stolen information by Hive ransomware gang including sensitive employee and operational data.

Ailogo

Taj Hotels Company Scoring based on AI Models

Cyber Incidents Likelihood 3 - 6 - 9 months

🔒
Incident Predictions locked
Access Monitoring Plan

A.I Risk Score Likelihood 3 - 6 - 9 months

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A.I. Risk Score Predictions locked
Access Monitoring Plan
statics

Underwriter Stats for Taj Hotels

Incidents vs Hospitality Industry Average (This Year)

No incidents recorded for Taj Hotels in 2026.

Incidents vs All-Companies Average (This Year)

No incidents recorded for Taj Hotels in 2026.

Incident Types Taj Hotels vs Hospitality Industry Avg (This Year)

No incidents recorded for Taj Hotels in 2026.

Incident History — Taj Hotels (X = Date, Y = Severity)

Taj Hotels cyber incidents detection timeline including parent company and subsidiaries

Taj Hotels Company Subsidiaries

SubsidiaryImage

Established in 1903, Taj is The Indian Hotels Company Limited’s (IHCL) iconic brand for the world’s most discerning travellers seeking luxury and authentic experiences. Taj has been rated as India’s Strongest Brand across all sectors for an unprecedented fourth time and also as the World’s Strongest Hotel Brand for the third consecutive year in 2024 by Brand Finance. From landmark city addresses to enchanting jungle safaris, and from idyllic resorts to authentic living Grand Palaces, each Taj hotel offers an unrivalled fusion of warm Indian hospitality, world-class service and modern luxury. Taj's unique portfolio comprises hotels across India, North America, United Kingdom, Africa, Middle East, Sri Lanka, Maldives and Nepal.

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newsone

Taj Hotels CyberSecurity News

February 11, 2026 08:00 AM
IHCL to open Taj hotel in Weligama, Sri Lanka

IHCL has announced the signing of a new Taj hotel in Weligama, Sri Lanka, marking an expansion of its presence in the country.

February 08, 2026 08:00 AM
Cybersecurity biggest risk for enterprises, says FICCI-EY report

Cybersecurity has emerged as the biggest risk for enterprises, followed by limited adoption of AI, workforce challenges and ESG compliance,...

February 08, 2026 08:00 AM
Avoid costly, large LLM buildouts; focus on smaller models, says Vembu

India should not emulate or compete head-on with the massive Large Language Models (LLMs) currently dominating the AI landscape,...

January 19, 2026 08:00 AM
Mag HON 362-363: Taj Hotels : a heritage luxury that is difficult to translate outside India

Flagship brand of Indian Hotels Company Limited (IHCL), a subsidiary of the Tata Group, Taj embodies a luxury strategy based on three...

January 05, 2026 08:00 AM
IHCL signs greenfield Taj hotel project in Mohali, India

Indian Hotels Company (IHCL) has signed a greenfield Taj hotel project in Mohali, Punjab, India, which will feature 225 rooms.

December 11, 2025 08:00 AM
Taj Banjara checks out; acquired by Auro Realty

Hyderabad: The iconic Taj Banjara hotel in the heart of Hyderabad's upmarket Banjara Hills has been acquired by Aurobindo Group's realty arm...

December 09, 2025 08:00 AM
Cygnett Hotels strengthens leadership team with key strategic appointments

Cygnett Hotels & Resorts has appointed Rahul Rana as Director–Culinary, bringing 22 years of global experience across Accor, Marriott,...

November 20, 2025 08:00 AM
Kyndryl renews pact with Vodafone Idea to upgrade IT and cybersecurity

US-based IT firm Kyndryl on Thursday announced a three-year partnership renewal with Vodafone Idea (Vi) to transform the telecom operator's...

October 23, 2025 07:00 AM
Entrepreneur Shradha Sharma Calls Out Delhi’s Taj Hotel Over ‘Padmasana’ Sitting Row

Your Story founder alleges she was schooled over posture, attire and footwear; netizens debate cultural sensitivity in fine dining spaces.

faq

Frequently Asked Questions

Explore insights on cybersecurity incidents, risk posture, and Rankiteo's assessments.

Taj Hotels CyberSecurity History Information

Official Website of Taj Hotels

The official website of Taj Hotels is http://www.tajhotels.com.

Taj Hotels’s AI-Generated Cybersecurity Score

According to Rankiteo, Taj Hotels’s AI-generated cybersecurity score is 818, reflecting their Good security posture.

How many security badges does Taj Hotels’ have ?

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

Has Taj Hotels been affected by any supply chain cyber incidents ?

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

Does Taj Hotels have SOC 2 Type 1 certification ?

According to Rankiteo, Taj Hotels is not certified under SOC 2 Type 1.

Does Taj Hotels have SOC 2 Type 2 certification ?

According to Rankiteo, Taj Hotels does not hold a SOC 2 Type 2 certification.

Does Taj Hotels comply with GDPR ?

According to Rankiteo, Taj Hotels is not listed as GDPR compliant.

Does Taj Hotels have PCI DSS certification ?

According to Rankiteo, Taj Hotels does not currently maintain PCI DSS compliance.

Does Taj Hotels comply with HIPAA ?

According to Rankiteo, Taj Hotels is not compliant with HIPAA regulations.

Does Taj Hotels have ISO 27001 certification ?

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

Industry Classification of Taj Hotels

Taj Hotels operates primarily in the Hospitality industry.

Number of Employees at Taj Hotels

Taj Hotels employs approximately 24,292 people worldwide.

Subsidiaries Owned by Taj Hotels

Taj Hotels presently has no subsidiaries across any sectors.

Taj Hotels’s LinkedIn Followers

Taj Hotels’s official LinkedIn profile has approximately 876,798 followers.

NAICS Classification of Taj Hotels

Taj Hotels is classified under the NAICS code 7211, which corresponds to Traveler Accommodation.

Taj Hotels’s Presence on Crunchbase

No, Taj Hotels does not have a profile on Crunchbase.

Taj Hotels’s Presence on LinkedIn

Yes, Taj Hotels maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/taj-hotels.

Cybersecurity Incidents Involving Taj Hotels

As of April 05, 2026, Rankiteo reports that Taj Hotels has experienced 5 cybersecurity incidents.

Number of Peer and Competitor Companies

Taj Hotels has an estimated 14,067 peer or competitor companies worldwide.

What types of cybersecurity incidents have occurred at Taj Hotels ?

Incident Types: The types of cybersecurity incidents that have occurred include Ransomware, Breach and Cyber Attack.

What was the total financial impact of these incidents on Taj Hotels ?

Total Financial Loss: The total financial loss from these incidents is estimated to be $1.80 billion.

How does Taj Hotels detect and respond to cybersecurity incidents ?

Detection and Response: The company detects and responds to cybersecurity incidents through an containment measures with suspension of certain it services, and containment measures with ai discovery tools, containment measures with advanced monitoring, containment measures with policy enforcement, and remediation measures with employee education, remediation measures with ai governance frameworks, remediation measures with transparency initiatives, remediation measures with audit tools for unauthorized ai, and communication strategy with stakeholder advisories, communication strategy with employee training programs, and enhanced monitoring with ai-powered monitoring for shadow ai, and communication strategy with public disclosure in quarterly results; cfo statement acknowledging impact..

Incident Details

Can you provide details on each incident ?

Incident : Ransomware Attack

Title: Ransomware Attack on Tata Technologies

Description: Tata Technologies encountered a ransomware attack leading to the suspension of certain IT services as a precautionary measure. The incident targeted a segment of its IT infrastructure. While client delivery services remained unaffected, the extent of data breach, if any, was not disclosed. This follows a previous cyber incident in October 2022 where Tata Power faced a ransomware attack, with subsequent leakage of stolen information by Hive ransomware gang including sensitive employee and operational data.

Type: Ransomware Attack

Incident : Ransomware

Title: Tata Technologies Ransomware Attack

Description: The Hunters International ransomware gang targeted Tata Technologies in a January cyberattack, claiming to have stolen 1.4TB of data, disrupting IT systems but not affecting client delivery services. The impact on operations was reported as minimal, with no client data or critical service disruptions mentioned, but the breach included a threat to release the stolen files if no ransom was paid.

Date Detected: January 2023

Type: Ransomware

Threat Actor: Hunters International

Motivation: Financial gain

Incident : Data Breach

Title: Tata Technologies Data Breach by Hunters International

Description: Tata Technologies, a global engineering and product development digital services company, was one of the victims of the Hunters International cybercriminal group. During their operations, before considering a move away from ransomware to purely data theft extortion schemes, Hunters International compromised and possibly extracted sensitive data from the company. The exact nature of the data stolen or the full consequences of the breach were not detailed, but given the profile of the company and the typical operational patterns of ransomware groups, the impact could be significant in terms of financial loss, intellectual property theft, and reputational damage.

Type: Data Breach

Threat Actor: Hunters International

Motivation: Financial GainIntellectual Property Theft

Incident : Unauthorized AI Deployment

Title: Shadow AI’s Silent Siege on Corporate Security

Description: Employees are deploying unauthorized 'shadow AI' systems at an alarming rate (35% surge), bypassing IT oversight and exposing enterprises to security risks like data leaks, regulatory fines, intellectual property theft, and eroded trust. Shadow AI involves unsanctioned use of AI tools (e.g., generative AI, no-code agents) for tasks like data analysis or content generation, creating blind spots in corporate governance. High-profile breaches (e.g., Tata Motors' 70TB data exposure via misconfigured AWS) and zero-click AI attacks (e.g., 'Shadow Escape') highlight the risks. Enterprises lack comprehensive governance frameworks, with only 37% of staff using shadow AI in 2025, posing major data risks across departments like marketing and finance.

Date Publicly Disclosed: 2025-10-28

Type: Unauthorized AI Deployment

Attack Vector: Unauthorized AI Tool UsageNo-Code AI AgentsThird-Party AI Service IntegrationMisconfigured Cloud Access (e.g., AWS)Zero-Click AI Exploits (e.g., 'Shadow Escape')

Vulnerability Exploited: Lack of IT OversightAbsence of AI Governance FrameworksEmployee Use of Unvetted AI ToolsData Sharing with Third-Party AI ServicesWeak Access Controls (e.g., AWS Misconfigurations)

Threat Actor: Insider Threat (Unintentional)Employees Using Unauthorized AICybercriminals Exploiting Shadow AI Vulnerabilities (e.g., Qilin Ransomware Groups)

Motivation: Productivity GainsTask AutomationCompetitive EdgeLack of Awareness About RisksFinancial Gain (for Cybercriminals)

Incident : Cyberattack (Production Disruption)

Title: Cyberattack on Tata Motors (Jaguar Land Rover) Disrupts UK Production

Description: Tata Motors, owner of Jaguar Land Rover, revealed a cyberattack that shut down production in the UK, costing the company approximately £1.8 billion ($2.35 billion). The incident resulted in exceptional costs of £196 million ($258 million) and a revenue drop from £6.5 billion to £4.9 billion ($8.5bn to $6.4bn) year-over-year for the quarter ended September 30th. Sales growth in India partially offset the losses. CFO Richard Molyneux acknowledged the severity of the incident, noting its increasing prevalence among companies.

Type: Cyberattack (Production Disruption)

What are the most common types of attacks the company has faced ?

Common Attack Types: The most common types of attacks the company has faced is Ransomware.

How does the company identify the attack vectors used in incidents ?

Identification of Attack Vectors: The company identifies the attack vectors used in incidents through Employee-Deployed AI ToolsNo-Code AI AgentsThird-Party AI Service Integrations.

Impact of the Incidents

What was the impact of each incident ?

Incident : Ransomware Attack TAT000020325

Systems Affected: Segment of IT infrastructure

Incident : Ransomware TAT702030425

Data Compromised: 1.4TB

Systems Affected: IT systems

Operational Impact: Minimal

Incident : Data Breach TAT235040325

Data Compromised: Sensitive Data

Brand Reputation Impact: Significant

Incident : Unauthorized AI Deployment TAT2032920103125

Data Compromised: Sensitive corporate data, Intellectual property, Proprietary information, Customer data (potential), 70tb of data (tata motors example)

Systems Affected: Enterprise WorkflowsData Analysis ToolsContent Generation PlatformsCloud Storage (e.g., AWS)AI-Powered Applications

Operational Impact: Blind Spots in GovernanceRegulatory Non-ComplianceEroded Stakeholder TrustDisrupted Business Operations

Brand Reputation Impact: Erosion of TrustNegative PublicityPotential Customer Attrition

Legal Liabilities: Regulatory FinesNon-Compliance Penalties (e.g., AI Ethics Laws)Litigation Risks

Identity Theft Risk: ['Potential (via Data Leaks)']

Payment Information Risk: ['Potential (if Financial Data Shared with Unauthorized AI)']

Incident : Cyberattack (Production Disruption) TAT0662106111725

Financial Loss: £1.8 billion ($2.35 billion) (total); £196 million ($258 million) (direct exceptional costs)

Systems Affected: Production systems (UK)

Operational Impact: Production shutdown in the UK

Revenue Loss: £1.6 billion ($2.1bn) year-over-year (from £6.5bn to £4.9bn)

What is the average financial loss per incident ?

Average Financial Loss: The average financial loss per incident is $360.00 million.

What types of data are most commonly compromised in incidents ?

Commonly Compromised Data Types: The types of data most commonly compromised in incidents are Sensitive Data, Sensitive Corporate Data, Intellectual Property, Proprietary Information, Customer Data (Potential), Confidential Employee Data and .

Which entities were affected by each incident ?

Incident : Ransomware Attack TAT000020325

Entity Name: Tata Technologies

Entity Type: Corporation

Industry: Technology

Incident : Ransomware TAT702030425

Entity Name: Tata Technologies

Entity Type: Company

Industry: Technology

Incident : Data Breach TAT235040325

Entity Name: Tata Technologies

Entity Type: Company

Industry: Engineering and Product Development Digital Services

Incident : Unauthorized AI Deployment TAT2032920103125

Entity Name: Global Enterprises (General)

Entity Type: Corporations, Multinational Companies, SMEs

Industry: All Industries (e.g., Technology, Finance, Marketing, Manufacturing)

Location: Global

Incident : Unauthorized AI Deployment TAT2032920103125

Entity Name: Tata Motors

Entity Type: Automotive Manufacturer

Industry: Automotive

Location: India (Global Operations)

Size: Large Enterprise

Incident : Unauthorized AI Deployment TAT2032920103125

Entity Name: Malaysian Companies

Entity Type: Corporations, SMEs

Industry: Multiple (e.g., Technology, Finance)

Location: Malaysia

Incident : Unauthorized AI Deployment TAT2032920103125

Entity Name: Australian Businesses

Entity Type: Corporations, SMEs

Industry: Multiple

Location: Australia

Incident : Cyberattack (Production Disruption) TAT0662106111725

Entity Name: Tata Motors (Jaguar Land Rover)

Entity Type: Automotive Manufacturer

Industry: Automotive

Location: UK (production disruption); India (parent company)

Response to the Incidents

What measures were taken in response to each incident ?

Incident : Ransomware Attack TAT000020325

Containment Measures: Suspension of certain IT services

Incident : Unauthorized AI Deployment TAT2032920103125

Containment Measures: AI Discovery ToolsAdvanced MonitoringPolicy Enforcement

Remediation Measures: Employee EducationAI Governance FrameworksTransparency InitiativesAudit Tools for Unauthorized AI

Communication Strategy: Stakeholder AdvisoriesEmployee Training Programs

Enhanced Monitoring: AI-Powered Monitoring for Shadow AI

Incident : Cyberattack (Production Disruption) TAT0662106111725

Communication Strategy: Public disclosure in quarterly results; CFO statement acknowledging impact

Data Breach Information

What type of data was compromised in each breach ?

Incident : Ransomware TAT702030425

Incident : Data Breach TAT235040325

Type of Data Compromised: Sensitive Data

Sensitivity of Data: High

Incident : Unauthorized AI Deployment TAT2032920103125

Type of Data Compromised: Sensitive corporate data, Intellectual property, Proprietary information, Customer data (potential), Confidential employee data

Number of Records Exposed: 70TB (Tata Motors Example), None

Sensitivity of Data: High (Corporate Secrets, PII, Financial Data)

Data Exfiltration: Potential (via Unauthorized AI Tools)Confirmed in Tata Motors Case

Personally Identifiable Information: Potential (if Shared with AI Tools)

What measures does the company take to prevent data exfiltration ?

Prevention of Data Exfiltration: The company takes the following measures to prevent data exfiltration: Employee Education, AI Governance Frameworks, Transparency Initiatives, Audit Tools for Unauthorized AI, .

How does the company handle incidents involving personally identifiable information (PII) ?

Handling of PII Incidents: The company handles incidents involving personally identifiable information (PII) through by suspension of certain it services, ai discovery tools, advanced monitoring, policy enforcement and .

Ransomware Information

Was ransomware involved in any of the incidents ?

Incident : Ransomware TAT702030425

Data Exfiltration: True

Incident : Unauthorized AI Deployment TAT2032920103125

Ransomware Strain: Qilin (Mentioned in Context of Exploiting Weak Points)

Regulatory Compliance

Were there any regulatory violations and fines imposed for each incident ?

Incident : Unauthorized AI Deployment TAT2032920103125

Regulations Violated: Potential Violations of AI Ethics Laws, Data Protection Regulations (e.g., GDPR, CCPA), Industry-Specific Compliance Standards,

Regulatory Notifications: NAIC Guidance on Responsible AI (October 2025)

Lessons Learned and Recommendations

What lessons were learned from each incident ?

Incident : Unauthorized AI Deployment TAT2032920103125

Lessons Learned: Shadow AI poses significant risks akin to shadow IT but with higher stakes due to AI's data-hungry nature., Unauthorized AI tools create blind spots in governance, leading to data leaks, compliance violations, and reputational damage., Enterprises lack comprehensive frameworks to detect and mitigate shadow AI risks., Employee education and transparency are critical to addressing insider threats from unauthorized AI usage., Proactive detection (e.g., AI discovery tools) and policy enforcement are essential for governance.

What recommendations were made to prevent future incidents ?

Incident : Unauthorized AI Deployment TAT2032920103125

Recommendations: Implement **AI governance frameworks** to monitor and approve AI tool usage., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Foster a **culture of transparency** where employees report AI tool adoptions., Conduct **regular audits** of AI usage across departments to identify blind spots., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Prioritize **vendor risk assessments** for third-party AI services to ensure data security.Implement **AI governance frameworks** to monitor and approve AI tool usage., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Foster a **culture of transparency** where employees report AI tool adoptions., Conduct **regular audits** of AI usage across departments to identify blind spots., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Prioritize **vendor risk assessments** for third-party AI services to ensure data security.Implement **AI governance frameworks** to monitor and approve AI tool usage., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Foster a **culture of transparency** where employees report AI tool adoptions., Conduct **regular audits** of AI usage across departments to identify blind spots., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Prioritize **vendor risk assessments** for third-party AI services to ensure data security.Implement **AI governance frameworks** to monitor and approve AI tool usage., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Foster a **culture of transparency** where employees report AI tool adoptions., Conduct **regular audits** of AI usage across departments to identify blind spots., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Prioritize **vendor risk assessments** for third-party AI services to ensure data security.Implement **AI governance frameworks** to monitor and approve AI tool usage., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Foster a **culture of transparency** where employees report AI tool adoptions., Conduct **regular audits** of AI usage across departments to identify blind spots., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Prioritize **vendor risk assessments** for third-party AI services to ensure data security.Implement **AI governance frameworks** to monitor and approve AI tool usage., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Foster a **culture of transparency** where employees report AI tool adoptions., Conduct **regular audits** of AI usage across departments to identify blind spots., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Prioritize **vendor risk assessments** for third-party AI services to ensure data security.Implement **AI governance frameworks** to monitor and approve AI tool usage., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Foster a **culture of transparency** where employees report AI tool adoptions., Conduct **regular audits** of AI usage across departments to identify blind spots., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Prioritize **vendor risk assessments** for third-party AI services to ensure data security.Implement **AI governance frameworks** to monitor and approve AI tool usage., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Foster a **culture of transparency** where employees report AI tool adoptions., Conduct **regular audits** of AI usage across departments to identify blind spots., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Prioritize **vendor risk assessments** for third-party AI services to ensure data security.Implement **AI governance frameworks** to monitor and approve AI tool usage., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Foster a **culture of transparency** where employees report AI tool adoptions., Conduct **regular audits** of AI usage across departments to identify blind spots., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Prioritize **vendor risk assessments** for third-party AI services to ensure data security.Implement **AI governance frameworks** to monitor and approve AI tool usage., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Foster a **culture of transparency** where employees report AI tool adoptions., Conduct **regular audits** of AI usage across departments to identify blind spots., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Prioritize **vendor risk assessments** for third-party AI services to ensure data security.

What are the key lessons learned from past incidents ?

Key Lessons Learned: The key lessons learned from past incidents are Shadow AI poses significant risks akin to shadow IT but with higher stakes due to AI's data-hungry nature.,Unauthorized AI tools create blind spots in governance, leading to data leaks, compliance violations, and reputational damage.,Enterprises lack comprehensive frameworks to detect and mitigate shadow AI risks.,Employee education and transparency are critical to addressing insider threats from unauthorized AI usage.,Proactive detection (e.g., AI discovery tools) and policy enforcement are essential for governance.

References

Where can I find more information about each incident ?

Incident : Unauthorized AI Deployment TAT2032920103125

Source: Undercode News (X)

Date Accessed: 2025-10-28

Incident : Unauthorized AI Deployment TAT2032920103125

Source: IBM Topic Overview

Incident : Unauthorized AI Deployment TAT2032920103125

Source: The Hacker News

Incident : Unauthorized AI Deployment TAT2032920103125

Source: Invicti 2025 Blog

Incident : Unauthorized AI Deployment TAT2032920103125

Source: Skywork.ai

Incident : Unauthorized AI Deployment TAT2032920103125

Source: TechTarget

Incident : Unauthorized AI Deployment TAT2032920103125

Source: WitnessAI Blog

Incident : Unauthorized AI Deployment TAT2032920103125

Source: ISACA Industry News

Incident : Unauthorized AI Deployment TAT2032920103125

Source: Forbes Council Post

Date Accessed: 2025-10-24

Incident : Unauthorized AI Deployment TAT2032920103125

Source: Techwire Asia

Date Accessed: 2025-10-25

Incident : Unauthorized AI Deployment TAT2032920103125

Source: The New Stack

Incident : Unauthorized AI Deployment TAT2032920103125

Source: WebProNews

Incident : Unauthorized AI Deployment TAT2032920103125

Source: News Hub (Australian Businesses)

Date Accessed: 2025-10-23

Incident : Unauthorized AI Deployment TAT2032920103125

Source: News Hub (NAIC Guidance)

Date Accessed: 2025-10-25

Incident : Unauthorized AI Deployment TAT2032920103125

Source: Aithority

Incident : Cyberattack (Production Disruption) TAT0662106111725

Source: Asia In Brief (The Register)

Where can stakeholders find additional resources on cybersecurity best practices ?

Additional Resources: Stakeholders can find additional resources on cybersecurity best practices at and Source: Undercode News (X)Date Accessed: 2025-10-28, and Source: IBM Topic Overview, and Source: The Hacker News, and Source: Invicti 2025 Blog, and Source: Skywork.ai, and Source: TechTarget, and Source: WitnessAI Blog, and Source: ISACA Industry News, and Source: Forbes Council PostDate Accessed: 2025-10-24, and Source: Techwire AsiaDate Accessed: 2025-10-25, and Source: The New Stack, and Source: WebProNews, and Source: News Hub (Australian Businesses)Date Accessed: 2025-10-23, and Source: News Hub (NAIC Guidance)Date Accessed: 2025-10-25, and Source: Aithority, and Source: Asia In Brief (The Register).

Investigation Status

What is the current status of the investigation for each incident ?

Incident : Unauthorized AI Deployment TAT2032920103125

Investigation Status: Ongoing (Industry-Wide Trend Analysis)

How does the company communicate the status of incident investigations to stakeholders ?

Communication of Investigation Status: The company communicates the status of incident investigations to stakeholders through Stakeholder Advisories, Employee Training Programs and Public disclosure in quarterly results; CFO statement acknowledging impact.

Stakeholder and Customer Advisories

Were there any advisories issued to stakeholders or customers for each incident ?

Incident : Unauthorized AI Deployment TAT2032920103125

Stakeholder Advisories: Cisos And It Leaders Urged To Implement Ai Governance Frameworks., Enterprises Advised To Audit Unauthorized Ai Innovations., Regulatory Bodies (E.G., Naic) Issuing Guidance On Responsible Ai Practices..

Customer Advisories: Customers of affected enterprises (e.g., Tata Motors) may face heightened risks of data exposure.General public advised to monitor corporate disclosures about shadow AI-related breaches.

What advisories does the company provide to stakeholders and customers following an incident ?

Advisories Provided: The company provides the following advisories to stakeholders and customers following an incident: were Cisos And It Leaders Urged To Implement Ai Governance Frameworks., Enterprises Advised To Audit Unauthorized Ai Innovations., Regulatory Bodies (E.G., Naic) Issuing Guidance On Responsible Ai Practices., Customers Of Affected Enterprises (E.G., Tata Motors) May Face Heightened Risks Of Data Exposure., General Public Advised To Monitor Corporate Disclosures About Shadow Ai-Related Breaches. and .

Initial Access Broker

How did the initial access broker gain entry for each incident ?

Incident : Unauthorized AI Deployment TAT2032920103125

Entry Point: Employee-Deployed Ai Tools, No-Code Ai Agents, Third-Party Ai Service Integrations,

High Value Targets: Sensitive Corporate Data, Intellectual Property, Customer Databases,

Data Sold on Dark Web: Sensitive Corporate Data, Intellectual Property, Customer Databases,

Post-Incident Analysis

What were the root causes and corrective actions taken for each incident ?

Incident : Unauthorized AI Deployment TAT2032920103125

Root Causes: Lack Of It Oversight For Ai Tool Deployments., Absence Of Enterprise-Wide Ai Governance Policies., Employee Unaware Of Risks Associated With Unauthorized Ai Tools., Rapid Proliferation Of Easy-To-Use, No-Code Ai Agents., Inadequate Monitoring Of Data Flows To Third-Party Ai Services.,

Corrective Actions: Develop And Enforce **Ai Usage Policies** Aligned With Security And Compliance Standards., Implement **Ai Discovery And Monitoring Tools** To Detect Shadow Deployments., Conduct **Regular Risk Assessments** For Third-Party Ai Services., Establish **Cross-Departmental Ai Governance Committees** To Oversee Tool Adoption., Enhance **Employee Training Programs** On Shadow Ai Risks And Approved Alternatives., Integrate **Ai Ethics And Compliance Checks** Into Procurement Processes For New Tools., Foster **Collaboration With Regulators** To Stay Ahead Of Evolving Ai-Related Laws., Promote **Transparency Initiatives** Where Employees Voluntarily Disclose Ai Tool Usage.,

What is the company's process for conducting post-incident analysis ?

Post-Incident Analysis Process: The company's process for conducting post-incident analysis is described as Ai-Powered Monitoring For Shadow Ai, .

What corrective actions has the company taken based on post-incident analysis ?

Corrective Actions Taken: The company has taken the following corrective actions based on post-incident analysis: Develop And Enforce **Ai Usage Policies** Aligned With Security And Compliance Standards., Implement **Ai Discovery And Monitoring Tools** To Detect Shadow Deployments., Conduct **Regular Risk Assessments** For Third-Party Ai Services., Establish **Cross-Departmental Ai Governance Committees** To Oversee Tool Adoption., Enhance **Employee Training Programs** On Shadow Ai Risks And Approved Alternatives., Integrate **Ai Ethics And Compliance Checks** Into Procurement Processes For New Tools., Foster **Collaboration With Regulators** To Stay Ahead Of Evolving Ai-Related Laws., Promote **Transparency Initiatives** Where Employees Voluntarily Disclose Ai Tool Usage., .

Additional Questions

General Information

Who was the attacking group in the last incident ?

Last Attacking Group: The attacking group in the last incident were an Hunters International, Hunters International, Insider Threat (Unintentional)Employees Using Unauthorized AICybercriminals Exploiting Shadow AI Vulnerabilities (e.g. and Qilin Ransomware Groups).

Incident Details

What was the most recent incident detected ?

Most Recent Incident Detected: The most recent incident detected was on January 2023.

What was the most recent incident publicly disclosed ?

Most Recent Incident Publicly Disclosed: The most recent incident publicly disclosed was on 2025-10-28.

Impact of the Incidents

What was the highest financial loss from an incident ?

Highest Financial Loss: The highest financial loss from an incident was £1.8 billion ($2.35 billion) (total); £196 million ($258 million) (direct exceptional costs).

What was the most significant data compromised in an incident ?

Most Significant Data Compromised: The most significant data compromised in an incident were 1.4TB, Sensitive Data, Sensitive Corporate Data, Intellectual Property, Proprietary Information, Customer Data (Potential), 70TB of Data (Tata Motors Example) and .

What was the most significant system affected in an incident ?

Most Significant System Affected: The most significant system affected in an incident were Enterprise WorkflowsData Analysis ToolsContent Generation PlatformsCloud Storage (e.g., AWS)AI-Powered Applications and Production systems (UK).

Response to the Incidents

What containment measures were taken in the most recent incident ?

Containment Measures in Most Recent Incident: The containment measures taken in the most recent incident were Suspension of certain IT services and AI Discovery ToolsAdvanced MonitoringPolicy Enforcement.

Data Breach Information

What was the most sensitive data compromised in a breach ?

Most Sensitive Data Compromised: The most sensitive data compromised in a breach were Intellectual Property, Proprietary Information, Sensitive Data, 1.4TB, Customer Data (Potential), 70TB of Data (Tata Motors Example) and Sensitive Corporate Data.

What was the number of records exposed in the most significant breach ?

Number of Records Exposed in Most Significant Breach: The number of records exposed in the most significant breach was 70.0.

Lessons Learned and Recommendations

What was the most significant lesson learned from past incidents ?

Most Significant Lesson Learned: The most significant lesson learned from past incidents was Proactive detection (e.g., AI discovery tools) and policy enforcement are essential for governance.

What was the most significant recommendation implemented to improve cybersecurity ?

Most Significant Recommendation Implemented: The most significant recommendation implemented to improve cybersecurity was Foster a **culture of transparency** where employees report AI tool adoptions., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Provide **employee training** on the risks of unauthorized AI tools and approved alternatives., Implement **AI governance frameworks** to monitor and approve AI tool usage., Prioritize **vendor risk assessments** for third-party AI services to ensure data security., Integrate **advanced monitoring** (e.g., AI-powered solutions) to track data flows to third-party AI services., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Conduct **regular audits** of AI usage across departments to identify blind spots. and Update **security policies** to explicitly address shadow AI risks and compliance requirements..

References

What is the most recent source of information about an incident ?

Most Recent Source: The most recent source of information about an incident are TechTarget, Forbes Council Post, Undercode News (X), Techwire Asia, The New Stack, WebProNews, News Hub (Australian Businesses), ISACA Industry News, Asia In Brief (The Register), Skywork.ai, Invicti 2025 Blog, WitnessAI Blog, The Hacker News, Aithority, IBM Topic Overview and News Hub (NAIC Guidance).

Investigation Status

What is the current status of the most recent investigation ?

Current Status of Most Recent Investigation: The current status of the most recent investigation is Ongoing (Industry-Wide Trend Analysis).

Stakeholder and Customer Advisories

What was the most recent stakeholder advisory issued ?

Most Recent Stakeholder Advisory: The most recent stakeholder advisory issued was CISOs and IT leaders urged to implement AI governance frameworks., Enterprises advised to audit unauthorized AI innovations., Regulatory bodies (e.g., NAIC) issuing guidance on responsible AI practices., .

What was the most recent customer advisory issued ?

Most Recent Customer Advisory: The most recent customer advisory issued were an Customers of affected enterprises (e.g. and Tata Motors) may face heightened risks of data exposure.General public advised to monitor corporate disclosures about shadow AI-related breaches.

Initial Access Broker

cve

Latest Global CVEs (Not Company-Specific)

Description

nimiq/core-rs-albatross is a Rust implementation of the Nimiq Proof-of-Stake protocol based on the Albatross consensus algorithm. Prior to version 1.3.0, two peer-facing consensus request handlers assume that the history index is always available and call blockchain.history_store.history_index().unwrap() directly. That assumption is false by construction. HistoryStoreProxy::history_index() explicitly returns None for the valid HistoryStoreProxy::WithoutIndex state. when a full node is syncing or otherwise running without the history index, a remote peer can send RequestTransactionsProof or RequestTransactionReceiptsByAddress and trigger an Option::unwrap() panic on the request path. This issue has been patched in version 1.3.0.

Risk Information
cvss3
Base: 5.3
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Description

PraisonAI is a multi-agent teams system. Prior to version 1.5.95, FileTools.download_file() in praisonaiagents validates the destination path but performs no validation on the url parameter, passing it directly to httpx.stream() with follow_redirects=True. An attacker who controls the URL can reach any host accessible from the server including cloud metadata services and internal network services. This issue has been patched in version 1.5.95.

Risk Information
cvss3
Base: 8.6
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Description

PraisonAI is a multi-agent teams system. Prior to version 4.5.97, OAuthManager.validate_token() returns True for any token not found in its internal store, which is empty by default. Any HTTP request to the MCP server with an arbitrary Bearer token is treated as authenticated, granting full access to all registered tools and agent capabilities. This issue has been patched in version 4.5.97.

Risk Information
cvss3
Base: 9.1
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
Description

PraisonAI is a multi-agent teams system. Prior to version 4.5.97, the PraisonAI Gateway server accepts WebSocket connections at /ws and serves agent topology at /info with no authentication. Any network client can connect, enumerate registered agents, and send arbitrary messages to agents and their tool sets. This issue has been patched in version 4.5.97.

Risk Information
cvss3
Base: 9.1
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
Description

PraisonAI is a multi-agent teams system. Prior to version 4.5.90, MCPToolIndex.search_tools() compiles a caller-supplied string directly as a Python regular expression with no validation, sanitization, or timeout. A crafted regex causes catastrophic backtracking in the re engine, blocking the Python thread for hundreds of seconds and causing a complete service outage. This issue has been patched in version 4.5.90.

Risk Information
cvss3
Base: 6.5
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

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