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Analyze » Snap Inc. » NORSNA1770407892

Incident Score: Analysis & Impact (NORSNA1770407892)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-116
Company Score Before Incident743 / 1000
Company Score After Incident627 / 1000
INCIDENT NUMBERNORSNA1770407892
Type of Cyber IncidentCyber Attack
ATTACK VECTORSocial Engineering
DATA EXPOSEDNude or semi-nude images, personal...
INCIDENT DATE17/05/2025
STATUSGuilty plea entered, sentencing pending

Key Highlights From The Incident Analysis

  • Timeline of Snap Inc.'s Cyber Attack 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 Snap Inc. 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 Snap Inc. breach identified under incident ID NORSNA1770407892.

The analysis begins with a detailed overview of Snap Inc.'s information like the linkedin page: https://www.linkedin.com/company/snap-inc-co, the number of followers: 537234, the industry type: Software Development and the number of employees: 8406 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 743 and after the incident was 627 with a difference of -116 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 Snap Inc. and their customers.

Snapchat users (primarily women and girls) recently reported "Illinois Man Pleads Guilty to Mass Snapchat Hacking Scheme Targeting Hundreds of Women", a noteworthy cybersecurity incident.

A 27-year-old Illinois man, Kyle Svara, pleaded guilty to federal charges for a hacking campaign that compromised the Snapchat accounts of approximately 600 women and girls.

The disruption is felt across the environment, affecting Snapchat accounts, and exposing Nude or semi-nude images, personal account data, with nearly At least 59 accounts breached (600 targeted) records at risk.

In response, and stakeholders are being briefed through Encouragement for potential victims to come forward.

The case underscores how Guilty plea entered, sentencing pending, with advisories going out to stakeholders covering Potential victims encouraged to come forward.

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 Phishing: Spearphishing via Service (T1566.003) with high confidence (90%), supported by evidence indicating used social engineering tactics to deceive victims into handing over security access codes. Under the Credential Access tactic, the analysis identified Steal Application Access Token (T1528) with high confidence (90%), supported by evidence indicating posed as a Snapchat representative to obtain security access codes and Brute Force: Password Guessing (T1110.001) with moderate confidence (50%), supported by evidence indicating compromised the Snapchat accounts of approximately 600 women and girls. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating downloading and distributing nude or semi-nude images from breached accounts. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating images sold online or traded on internet forums and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate to high confidence (70%), supported by evidence indicating distributed nude or semi-nude images via online platforms. Under the Impact tactic, the analysis identified Data Destruction (T1485) with lower confidence (30%), supported by evidence indicating no evidence of data destruction, but images were distributed without consent and Data Encrypted for Impact (T1486) with lower confidence (10%), supported by evidence indicating no evidence of data encryption. Under the Defense Evasion tactic, the analysis identified Hide Artifacts: Hidden Files and Directories (T1564.001) with moderate confidence (60%), supported by evidence indicating lied to authorities about involvement in distributing child sexual abuse material and Masquerading: Match Legitimate Name or Location (T1036.005) with high confidence (90%), supported by evidence indicating posed as a Snapchat representative to deceive victims. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Phishing: Spearphishing via Service (90%)
Credential Access
Steal Application Access Token (90%)
Brute Force: Password Guessing (50%)
Collection
Data from Local System (90%)
Exfiltration
Exfiltration Over C2 Channel (80%)
Exfiltration Over Web Service: Exfiltration to Cloud Storage (70%)
Impact
Data Destruction (30%)
Data Encrypted for Impact (10%)
Defense Evasion
Hide Artifacts: Hidden Files and Directories (60%)
Masquerading: Match Legitimate Name or Location (90%)

Sources & References