Tata Steel
Company Details
Linkedin ID:
tatasteelltd
Website:
Employees number:
56,276
Number of followers:
2,283,578
NAICS:
212
Industry Type:
Homepage:
tatasteel.com
IP Addresses:
0
Company ID:
TAT_2335259
Scan Status:
In-progress
Tata Steel Company CyberSecurity Posture
tatasteel.com
Tata Steel group is among the top global steel companies with an annual crude steel capacity of 34 million tonnes per annum. It is one of the world's most geographically-diversified steel producers, with operations and commercial presence across the world. The group (excluding SEA operations) recorded a consolidated turnover of US $19.7 billion in the financial year ending March 31, 2020. A Great Place to Work-CertifiedTM organisation, Tata Steel Ltd., together with its subsidiaries, associates and joint ventures, is spread across five continents with an employee base of over 65,000. Tata Steel has been a part of the DJSI Emerging Markets Index since 2012 and has been consistently ranked amongst top 5 steel companies in the DJSI Corporate Sustainability Assessment since 2016. Besides being a member of ResponsibleSteelTM and worldsteel’s Climate Action Programme, Tata Steel has won several awards and recognitions including the World Economic Forum’s Global Lighthouse recognition for its Kalinganagar Plant - a first in India, and Prime Minister’s Trophy for the best performing integrated steel plant for 2016-17. The Company, ranked as India’s most valuable Metals & Mining brand by Brand Finance, received the ‘Honourable Mention’ at the National CSR Awards 2019, Steel Sustainability Champion 2019 by worldsteel, CII Greenco Star Performer Award 2019, ‘Most Ethical Company’ award 2020 from Ethisphere Institute, Best Risk Management Framework & Systems Award (2020) by CNBC TV-18, and Award for Excellence in Financial Reporting FY20 by ICAI, among several others. To know more, visit www.tatasteel.com and www.wealsomaketomorrow.com.
Tata Steel A.I CyberSecurity Scoring
Tata Steel Risk Score (AI oriented)Between 800 and 849
Tata Steel
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Tata Steel Global Score (TPRM)XXXX
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Tata Steel Company CyberSecurity News & History
Past Incidents
5
Attack Types
3
Tata Motors (Jaguar Land Rover)
Cyber Attack
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
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
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
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
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 Steel Company Scoring based on AI Models
Cyber Incidents Likelihood 3 - 6 - 9 months
A.I Risk Score Likelihood 3 - 6 - 9 months
Underwriter Stats for Tata Steel
Incidents vs Mining Industry Average (This Year)
No incidents recorded for Tata Steel in 2026.
Incidents vs All-Companies Average (This Year)
No incidents recorded for Tata Steel in 2026.
Incident Types Tata Steel vs Mining Industry Avg (This Year)
No incidents recorded for Tata Steel in 2026.
Incident History — Tata Steel (X = Date, Y = Severity)
Tata Steel cyber incidents detection timeline including parent company and subsidiaries
Tata Steel Company Subsidiaries
Tata Steel group is among the top global steel companies with an annual crude steel capacity of 34 million tonnes per annum. It is one of the world's most geographically-diversified steel producers, with operations and commercial presence across the world. The group (excluding SEA operations) recorded a consolidated turnover of US $19.7 billion in the financial year ending March 31, 2020. A Great Place to Work-CertifiedTM organisation, Tata Steel Ltd., together with its subsidiaries, associates and joint ventures, is spread across five continents with an employee base of over 65,000. Tata Steel has been a part of the DJSI Emerging Markets Index since 2012 and has been consistently ranked amongst top 5 steel companies in the DJSI Corporate Sustainability Assessment since 2016. Besides being a member of ResponsibleSteelTM and worldsteel’s Climate Action Programme, Tata Steel has won several awards and recognitions including the World Economic Forum’s Global Lighthouse recognition for its Kalinganagar Plant - a first in India, and Prime Minister’s Trophy for the best performing integrated steel plant for 2016-17. The Company, ranked as India’s most valuable Metals & Mining brand by Brand Finance, received the ‘Honourable Mention’ at the National CSR Awards 2019, Steel Sustainability Champion 2019 by worldsteel, CII Greenco Star Performer Award 2019, ‘Most Ethical Company’ award 2020 from Ethisphere Institute, Best Risk Management Framework & Systems Award (2020) by CNBC TV-18, and Award for Excellence in Financial Reporting FY20 by ICAI, among several others. To know more, visit www.tatasteel.com and www.wealsomaketomorrow.com.
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Frequently Asked Questions
Explore insights on cybersecurity incidents, risk posture, and Rankiteo's assessments.
Tata Steel CyberSecurity History Information
Official Website of Tata Steel
The official website of Tata Steel is https://www.tatasteel.com.
Tata Steel’s AI-Generated Cybersecurity Score
According to Rankiteo, Tata Steel’s AI-generated cybersecurity score is 802, reflecting their Good security posture.
How many security badges does Tata Steel’ have ?
According to Rankiteo, Tata Steel currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.
Has Tata Steel been affected by any supply chain cyber incidents ?
According to Rankiteo, Tata Steel has not been affected by any supply chain cyber incidents, and no incident IDs are currently listed for the organization.
Does Tata Steel have SOC 2 Type 1 certification ?
According to Rankiteo, Tata Steel is not certified under SOC 2 Type 1.
Does Tata Steel have SOC 2 Type 2 certification ?
According to Rankiteo, Tata Steel does not hold a SOC 2 Type 2 certification.
Does Tata Steel comply with GDPR ?
According to Rankiteo, Tata Steel is not listed as GDPR compliant.
Does Tata Steel have PCI DSS certification ?
According to Rankiteo, Tata Steel does not currently maintain PCI DSS compliance.
Does Tata Steel comply with HIPAA ?
According to Rankiteo, Tata Steel is not compliant with HIPAA regulations.
Does Tata Steel have ISO 27001 certification ?
According to Rankiteo,Tata Steel is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.
Industry Classification of Tata Steel
Tata Steel operates primarily in the Mining industry.
Number of Employees at Tata Steel
Tata Steel employs approximately 56,276 people worldwide.
Subsidiaries Owned by Tata Steel
Tata Steel presently has no subsidiaries across any sectors.
Tata Steel’s LinkedIn Followers
Tata Steel’s official LinkedIn profile has approximately 2,283,578 followers.
NAICS Classification of Tata Steel
Tata Steel is classified under the NAICS code 212, which corresponds to Mining (except Oil and Gas).
Tata Steel’s Presence on Crunchbase
No, Tata Steel does not have a profile on Crunchbase.
Tata Steel’s Presence on LinkedIn
Yes, Tata Steel maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/tatasteelltd.
Cybersecurity Incidents Involving Tata Steel
As of January 24, 2026, Rankiteo reports that Tata Steel has experienced 5 cybersecurity incidents.
Number of Peer and Competitor Companies
Tata Steel has an estimated 3,737 peer or competitor companies worldwide.
What types of cybersecurity incidents have occurred at Tata Steel ?
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 Tata Steel ?
Total Financial Loss: The total financial loss from these incidents is estimated to be $1.80 billion.
How does Tata Steel 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 ?
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
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
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
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)
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 Proprietary Information, Sensitive Corporate Data, 70TB of Data (Tata Motors Example), Customer Data (Potential), Sensitive Data, 1.4TB and Intellectual Property.
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 Implement **AI governance frameworks** to monitor and approve AI tool usage., Adopt **hybrid approaches** combining technology (e.g., auditing tools) and policy updates to mitigate risks., Deploy **AI discovery tools** to detect unauthorized shadow AI deployments., Collaborate with **regulatory bodies** (e.g., NAIC) to align AI practices with evolving compliance standards., Foster a **culture of transparency** where employees report AI tool adoptions., 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., Update **security policies** to explicitly address shadow AI risks and compliance requirements., Conduct **regular audits** of AI usage across departments to identify blind spots. and Provide **employee training** on the risks of unauthorized AI tools and approved alternatives..
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 Skywork.ai, Forbes Council Post, Asia In Brief (The Register), WebProNews, News Hub (Australian Businesses), ISACA Industry News, News Hub (NAIC Guidance), Undercode News (X), The New Stack, Techwire Asia, WitnessAI Blog, Invicti 2025 Blog, The Hacker News, Aithority, TechTarget and IBM Topic Overview.
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
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Description
Typemill is a flat-file, Markdown-based CMS designed for informational documentation websites. A reflected Cross-Site Scripting (XSS) exists in the login error view template `login.twig` of versions 2.19.1 and below. The `username` value can be echoed back without proper contextual encoding when authentication fails. An attacker can execute script in the login page context. This issue has been fixed in version 2.19.2.
Risk Information
cvss3
Base: 5.4
Severity: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:N
Description
A DOM-based Cross-Site Scripting (XSS) vulnerability exists in the DomainCheckerApp class within domain/script.js of Sourcecodester Domain Availability Checker v1.0. The vulnerability occurs because the application improperly handles user-supplied data in the createResultElement method by using the unsafe innerHTML property to render domain search results.
Description
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Description
A UNIX symbolic link following issue in the jailer component in Firecracker version v1.13.1 and earlier and 1.14.0 on Linux may allow a local host user with write access to the pre-created jailer directories to overwrite arbitrary host files via a symlink attack during the initialization copy at jailer startup, if the jailer is executed with root privileges. To mitigate this issue, users should upgrade to version v1.13.2 or 1.14.1 or above.
Risk Information
cvss3
Base: 6.0
Severity: LOW
CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:N/I:H/A:H
cvss4
Base: 6.0
Severity: LOW
CVSS:4.0/AV:L/AC:L/AT:N/PR:H/UI:N/VC:N/VI:N/VA:N/SC:N/SI:H/SA:H/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
References
Description
An information disclosure vulnerability exists in the /srvs/membersrv/getCashiers endpoint of the Aptsys gemscms backend platform thru 2025-05-28. This unauthenticated endpoint returns a list of cashier accounts, including names, email addresses, usernames, and passwords hashed using MD5. As MD5 is a broken cryptographic function, the hashes can be easily reversed using public tools, exposing user credentials in plaintext. This allows remote attackers to perform unauthorized logins and potentially gain access to sensitive POS operations or backend functions.
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