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Analyze » Apple » 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-35
Company Score Before Incident773 / 1000
Company Score After Incident738 / 1000
Company LinkView Apple Profile
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 Apple'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 Apple 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 Apple breach identified under incident ID DELOPETATAPPCELCOU1782491615.

The analysis begins with a detailed overview of Apple's information like the linkedin page: https://www.linkedin.com/company/apple, the number of followers: 18297555, the industry type: Computers and Electronics Manufacturing and the number of employees: 194686 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 773 and after the incident was 738 with a difference of -35 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 Apple 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 Trusted Relationship (T1199) with moderate to high confidence (80%), supported by evidence indicating russian authorities exploited Cellebrite software to extract data, Exploit Public-Facing Application (T1190) with moderate to high confidence (70%), supported by evidence indicating cellebrite software exploitation for iPhone data extraction, and Phishing: Spearphishing Attachment (T1566.001) with moderate to high confidence (70%), supported by evidence indicating coldRiver phishing campaigns against Pivovarov’s associates. Under the Execution tactic, the analysis identified User Execution: Malicious File (T1204.002) with moderate confidence (60%), 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 Create or Modify System Process: Launch Agent (T1543.001) with moderate confidence (60%), supported by evidence indicating macOS.Gaslight backdoor persistence on macOS systems. 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 Masquerading: Match Legitimate Name or Location (T1036.005) with moderate to high confidence (80%), supported by evidence indicating macOS.Gaslight uses deceptive error messages to evade LLM-assisted triage and Impair Defenses: Disable or Modify Tools (T1562.001) with moderate confidence (60%), supported by evidence indicating adversarial prompt injection disrupts automated security analysis. Under the Credential Access tactic, the analysis identified Credentials from Password Stores (T1555) with moderate to high confidence (70%), supported by evidence indicating cellebrite software extracted Telegram and WhatsApp data from iPhone and OS Credential Dumping (T1003) with moderate confidence (60%), supported by evidence indicating transport for London breach forced 28,000 employees to reset passwords. Under the Discovery tactic, the analysis identified File and Directory Discovery (T1083) with moderate to high confidence (70%), supported by evidence indicating 630 GB of proprietary data leaked, including Apple/Tesla schematics. 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 compromised via Tata Electronics breach and Email Collection: Remote Email Collection (T1114.002) with moderate to high confidence (70%), supported by evidence indicating telegram and WhatsApp data harvested from iPhone. 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 on dark web by World Leaks and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate confidence (60%), supported by evidence indicating proprietary data leaked via dark web. Under the Impact tactic, the analysis identified Data Encrypted for Impact (T1486) with lower confidence (40%), supported by evidence indicating no details on encryption, but data exfiltration implies potential impact and Defacement: Internal Defacement (T1491.001) with moderate confidence (50%), supported by evidence indicating transport for London administrative networks disrupted. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Trusted Relationship (80%)
Exploit Public-Facing Application (70%)
Phishing: Spearphishing Attachment (70%)
Execution
User Execution: Malicious File (60%)
Command and Scripting Interpreter: Unix Shell (70%)
Persistence
Create or Modify System Process: Launch Agent (60%)
Privilege Escalation
Exploitation for Privilege Escalation (50%)
Defense Evasion
Masquerading: Match Legitimate Name or Location (80%)
Impair Defenses: Disable or Modify Tools (60%)
Credential Access
Credentials from Password Stores (70%)
OS Credential Dumping (60%)
Discovery
File and Directory Discovery (70%)
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%)
Defacement: Internal Defacement (50%)