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Analyze » GonnaOrder » GON1767064516

Incident Score: Analysis & Impact (GON1767064516)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-115
Company Score Before Incident765 / 1000
Company Score After Incident650 / 1000
INCIDENT NUMBERGON1767064516
Type of Cyber IncidentBreach
ATTACK VECTORMisconfigured Kafka Broker
DATA EXPOSEDReal-time order information, phone numbers,...
INCIDENT DATE11/06/2025
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of GonnaOrder'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 GonnaOrder 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 GonnaOrder breach identified under incident ID GON1767064516.

The analysis begins with a detailed overview of GonnaOrder's information like the linkedin page: https://www.linkedin.com/company/gonnaorder, the number of followers: 1564, the industry type: Technology, Information and Internet and the number of employees: 26 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 765 and after the incident was 650 with a difference of -115 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 GonnaOrder and their customers.

GonnaOrder recently reported "GonnaOrder Kafka Broker Data Exposure", a noteworthy cybersecurity incident.

Major European food delivery platform GonnaOrder had real-time order information from thousands of its customers inadvertently exposed by a Kafka Broker instance that has been unsecured since August 2022.

The disruption is felt across the environment, affecting Kafka Broker instance, and exposing Real-time order information, phone numbers, ordered locations, delivery notes, payment details, names, home addresses, access codes, with nearly Millions (potential) records at risk.

In response, moved swiftly to contain the threat with measures like Instance secured late last month.

Overall, the incident is a reminder of why proactive monitoring and strong governance matter.

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 unsecured Apache Kafka Broker instance accessible for nearly two years and Exploitation of Remote Services (T1210) with moderate to high confidence (70%), supported by evidence indicating kafka Broker misconfiguration allowed unauthorized access. Under the Collection tactic, the analysis identified Data from Cloud Storage (T1530) with high confidence (90%), supported by evidence indicating real-time order data scraped from exposed Kafka Broker and Automated Collection (T1119) with moderate to high confidence (80%), supported by evidence indicating attackers could deploy a collector to continuously scrape data. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (70%), supported by evidence indicating prolonged data scraping activities could facilitate exfiltration and Exfiltration Over C2 Channel (T1041) with moderate confidence (60%), supported by evidence indicating potential data exfiltration via unauthorized access to Kafka Broker. Under the Impact tactic, the analysis identified Data Destruction (T1485) with lower confidence (30%), supported by evidence indicating potential misuse of exposed data for fraud or phishing and Stored Data Manipulation (T1565.001) with lower confidence (40%), supported by evidence indicating exposed data included payment information and access codes. Under the Defense Evasion tactic, the analysis identified Impair Defenses: Disable or Modify Tools (T1562.001) with moderate confidence (50%), supported by evidence indicating unsecured Kafka Broker instance due to misconfiguration. 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%)
Exploitation of Remote Services (70%)
Collection
Data from Cloud Storage (90%)
Automated Collection (80%)
Exfiltration
Transfer Data to Cloud Account (70%)
Exfiltration Over C2 Channel (60%)
Impact
Data Destruction (30%)
Stored Data Manipulation (40%)
Defense Evasion
Impair Defenses: Disable or Modify Tools (50%)

Sources & References