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Analyze » Industrial By-Products Management Division, Tata Steel » DELOPETATAPPCELCOU1782491615

Incident Score: Analysis & Impact (DELOPETATAPPCELCOU1782491615)

The details regarding individual company incidents & reports gives you full view from every side.

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-98
Company Score Before Incident758 / 1000
Company Score After Incident660 / 1000
INCIDENT NUMBERDELOPETATAPPCELCOU1782491615
Type of Cyber IncidentBreach
ATTACK VECTORSoftware Exploitation (Cellebrite), Phishing, Dark Web Leak, Adversarial Prompt Injection, Backdoor
DATA EXPOSED630 GB of proprietary data...
INCIDENT DATE31/12/2024
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of Industrial By-Products Management Division, Tata Steel's Breach and lateral movement inside company's environment.
  • Overview of affected data sets, including SSNs and PHI, and why they materially increase incident severity.
  • How Rankiteo’s incident engine converts technical details into a normalized incident score.
  • How this cyber incident impacts Industrial By-Products Management Division, Tata Steel Rankiteo cyber scoring and cyber rating.
  • Rankiteo’s MITRE ATT&CK correlation analysis for this incident, with associated confidence level.

Full Incident Analysis Transcript

In this Rankiteo incident briefing, we review the Industrial By-Products Management Division, Tata Steel breach identified under incident ID DELOPETATAPPCELCOU1782491615.

The analysis begins with a detailed overview of Industrial By-Products Management Division, Tata Steel's information like the linkedin page: https://www.linkedin.com/company/tatasteel, the number of followers: 4725, the industry type: Mining and the number of employees: None employees

After the initial compromise, the video explains how Rankiteo's incident engine converts technical details into a normalized incident score. The incident score before the incident was 758 and after the incident was 660 with a difference of -98 which is could be a good indicator of the severity and impact of the incident.

In the next step of the video, we will analyze in more details the incident and the impact it had on Industrial By-Products Management Division, Tata Steel and their customers.

Andrey Pivovarov recently reported "Cybersecurity Roundup: Key Threats, Breaches, and Industry Shifts", a noteworthy cybersecurity incident.

This week’s cybersecurity landscape saw significant developments across state-sponsored attacks, corporate breaches, regulatory interventions, and emerging AI-driven threats.

The disruption is felt across the environment, affecting Transport for London fare refund systems, Administrative networks and macOS systems, and exposing 630 GB of proprietary data (Tata Electronics), Telegram and WhatsApp data (Andrey Pivovarov) and Apple and Tesla manufacturing schematics, plus an estimated financial loss of Millions in remediation costs (Transport for London).

In response, and began remediation that includes Apple patched Beats eavesdropping flaw.

The case underscores how and recommending next steps like Adopt zero-trust architectures, Expedite patching and Decommission legacy systems, with advisories going out to stakeholders covering Five Eyes advisory on AI-driven threats.

Finally, we try to match the incident with the MITRE ATT&CK framework to see if there is any correlation between the incident and the MITRE ATT&CK framework.

The MITRE ATT&CK framework is a knowledge base of techniques and sub-techniques that are used to describe the tactics and procedures of cyber adversaries. It is a powerful tool for understanding the threat landscape and for developing effective defense strategies.

MITRE ATT&CK® Correlation Analysis

Rankiteo's analysis has identified several MITRE ATT&CK tactics and techniques associated with this incident, each with varying levels of confidence based on available evidence. Under the Initial Access tactic, the analysis identified Exploit Public-Facing Application (T1190) with moderate to high confidence (80%), supported by evidence indicating russian authorities exploited Cellebrite software, Phishing: Spearphishing Link (T1566.002) with moderate to high confidence (70%), supported by evidence indicating coldRiver phishing campaigns against Pivovarov’s associates, and Supply Chain Compromise: Compromise Software Dependencies (T1195.002) with moderate confidence (60%), supported by evidence indicating tata Electronics breach via supply chain (Apple/Tesla schematics). Under the Execution tactic, the analysis identified User Execution: Malicious File (T1204.002) with moderate confidence (50%), supported by evidence indicating macOS.Gaslight backdoor deploys deceptive error messages and Command and Scripting Interpreter: Unix Shell (T1059.004) with moderate to high confidence (70%), supported by evidence indicating macOS.Gaslight provides an interactive shell. Under the Persistence tactic, the analysis identified Boot or Logon Autostart Execution: Plist Modification (T1547.011) with moderate confidence (60%), supported by evidence indicating macOS.Gaslight backdoor (Rust-based malware). Under the Privilege Escalation tactic, the analysis identified Exploitation for Privilege Escalation (T1068) with moderate confidence (50%), supported by evidence indicating cellebrite software exploitation for iPhone data extraction. Under the Defense Evasion tactic, the analysis identified Impair Defenses: Disable or Modify Tools (T1562.001) with moderate to high confidence (80%), supported by evidence indicating macOS.Gaslight uses adversarial prompt injection to evade LLM triage and Masquerading: Match Legitimate Name or Location (T1036.005) with moderate confidence (60%), supported by evidence indicating macOS.Gaslight deploys deceptive error messages. Under the Credential Access tactic, the analysis identified Credentials from Password Stores: Credentials from Web Browsers (T1555.003) with moderate to high confidence (70%), supported by evidence indicating cellebrite exploited Telegram/WhatsApp data from iPhone and OS Credential Dumping: LSASS Memory (T1003.001) with moderate confidence (50%), supported by evidence indicating transport for London breach forced 28,000 password resets. Under the Discovery tactic, the analysis identified Account Discovery: Local Account (T1087.001) with moderate confidence (60%), supported by evidence indicating macOS.Gaslight backdoor harvests data from local system. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating 630 GB of proprietary data (Tata Electronics) leaked and Email Collection: Remote Email Collection (T1114.002) with moderate to high confidence (70%), supported by evidence indicating telegram/WhatsApp data extracted via Cellebrite. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating 630 GB of Tata Electronics data published by World Leaks and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate confidence (60%), supported by evidence indicating dark web leak of Tata Electronics data. Under the Impact tactic, the analysis identified Data Encrypted for Impact (T1486) with lower confidence (40%), supported by evidence indicating transport for London breach disrupted fare refund systems and Data Manipulation: Stored Data Manipulation (T1565.001) with moderate confidence (50%), supported by evidence indicating administrative networks disrupted (Transport for London). These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Exploit Public-Facing Application (80%)
Phishing: Spearphishing Link (70%)
Supply Chain Compromise: Compromise Software Dependencies (60%)
Execution
User Execution: Malicious File (50%)
Command and Scripting Interpreter: Unix Shell (70%)
Persistence
Boot or Logon Autostart Execution: Plist Modification (60%)
Privilege Escalation
Exploitation for Privilege Escalation (50%)
Defense Evasion
Impair Defenses: Disable or Modify Tools (80%)
Masquerading: Match Legitimate Name or Location (60%)
Credential Access
Credentials from Password Stores: Credentials from Web Browsers (70%)
OS Credential Dumping: LSASS Memory (50%)
Discovery
Account Discovery: Local Account (60%)
Collection
Data from Local System (90%)
Email Collection: Remote Email Collection (70%)
Exfiltration
Exfiltration Over C2 Channel (80%)
Exfiltration Over Web Service: Exfiltration to Cloud Storage (60%)
Impact
Data Encrypted for Impact (40%)
Data Manipulation: Stored Data Manipulation (50%)

Sources & References