Amazon Fulfillment Technologies & Robotics Company Cyber Security Posture
amazon.jobsOn the Fulfillment Technologies & Robotics Team, we build dynamic partnerships between people and intelligent machines. This intricate collaboration helps Amazon fulfill orders with unmatched accuracy. Since we began working with robotics, we've added over a million new jobs worldwide. Working in symphony with our robotic technology, employees have the opportunity to extend their technical capabilities by working alongside some of the industry’s most advanced technologies. This includes our fleet of autonomous mobile robots, sophisticated control software, and technologies like language perception, machine learning, object recognition, and semantic understanding of commands. These technologies help employees deliver an ever-improving customer and employee experience, as well as improve the safety of our facilities. Explore opportunities across the entire Fulfillment Technologies & Robotics team to find the right fit for you.
AFT&R Company Details
kiva-systems
12180 employees
153558.0
511
Software Development
amazon.jobs
Scan still pending
AMA_3086408
In-progress
AFT&R Risk Score (AI oriented)Between 900 and 1000
This score is AI-generated and less favored by cyber insurers, who prefer the TPRM score.
AFT&R Global Score.png)
Amazon Fulfillment Technologies & Robotics Company Scoring based on AI Models
| Model Name | Date | Description | Current Score Difference | Score |
|---|---|---|---|---|
| AVERAGE-Industry | 03-12-2025 | This score represents the average cybersecurity rating of companies already scanned within the same industry. It provides a benchmark to compare an individual company's security posture against its industry peers. | N/A | Between 900 and 1000 |
Amazon Fulfillment Technologies & Robotics Company Cyber Security News & History
| Entity | Type | Severity | Impact | Seen | Url ID | Details | View |
|---|---|---|---|---|---|---|---|
| Ring | Breach | 100 | 5 | 01/2021 | RIN01518622 | Link | |
Rankiteo Explanation : Attack threatening the organization's existenceDescription: A security flaw in Ring’s Neighbors app exposed the precise locations and home addresses of users who had posted to the app. It included the videos taken by Ring doorbells and security cameras and the bug made it possible to retrieve the location data of users who posted to the app. The bug retrieved the hidden data, including the user’s latitude and longitude and their home address, from Ring’s servers. The hackers also created tools to break into Ring accounts and over 1,500 user account passwords were found on the dark web. | |||||||
| Whole Foods Market | Breach | 50 | 2 | 09/2023 | WHO04111223 | Link | |
Rankiteo Explanation : Attack limited on finance or reputationDescription: Whole Foods Market chain Whole Foods Market Suffered Payment Card Breach. The security breach report states that thieves were able to obtain credit card details of patrons who made transactions at specific locations, such as full-service restaurants and taprooms inside some stores, without authorization. Whole Foods Market was notified of an incident in which payment card information used at select establishments like full-service restaurants and taprooms located within some locations was improperly accessed. The locations and total number of consumers affected by the attack remain unknown, as the company has not released any information about it. | |||||||
| webXray | Breach | 85 | 4 | 7/2024 | AMA000072524 | Link | |
Rankiteo Explanation : Attack with significant impact with customers data leaksDescription: webXray, a tool designed to expose privacy violations on the internet, reveals how tech giants like Google and various websites track user data and browsing habits. Developed by former Google engineer Tim Libert, webXray analyzes web activity to identify which sites collect data, including sensitive information. Such tracking, often without clear user consent, can breach laws like HIPAA and GDPR, posing serious threats to individuals' privacy. The tool aims to empower regulators and attorneys to assess and rectify these violations, promoting a balanced digital ecosystem. | |||||||
| Amazon | Cyber Attack | 80 | 2 | 01/2016 | AMA0417522 | Link | |
Rankiteo Explanation : Attack limited on finance or reputationDescription: Amazon’s customer service representative was tricked into disclosing Eric Springer, a user’s personal information by an attacker who used social engineering techniques. The attack initiated through the mail ended up in the attacker getting the credit card details along with the address and other details. The incident got all highlighted on the internet and people on the web demanded social engineering training to be given to employees to prevent any such incidents in the future. | |||||||
| Ring | Data Leak | 85 | 3 | 01/2020 | RIN211261222 | Link | |
Rankiteo Explanation : Attack with significant impact with internal employee data leaksDescription: Amazon-owned home security camera company Ring fired employees for improperly accessing Ring users' video data. This data can be particularly sensitive though, as customers often put the cameras inside their home. Ring employees in Ukraine were given unrestricted access to videos from Ring cameras around the world. | |||||||
| Amazon | Data Leak | 50 | 2 | 01/2020 | AMA21461222 | Link | |
Rankiteo Explanation : Attack limited on finance or reputationDescription: Amazon had fired a number of employees after they shared customer email address and phone numbers with a third-party violating of their policies. No other information related to account was shared. | |||||||
| Twitch | Data Leak | 85 | 10/2021 | TWI19174123 | Link | ||
Rankiteo Explanation : Attack with significant impact with internal employee data leaks.Description: Amazon.com Inc’s live streaming e-sports platform Twitch was hit by a data breach. An anonymous hacker leaked Twitch data, including information related to the company’s source code, clients and unreleased games, according to Video Games Chronicle. The data was exposed due to an error in a Twitch server configuration change and was subsequently accessed by a malicious third party. | |||||||
| Ring | Data Leak | 60 | 4 | 12/2019 | RIN2178523 | Link | |
Rankiteo Explanation : Attack with significant impact with customers data leaksDescription: 3,672 Ring camera owners' login information, including login emails, passwords, time zones, and the names people give to certain Ring cameras, was stolen. This enables a potential assailant to observe cameras in someone's home, which is a grave potential breach of privacy. A hacker might access a Ring customer's home address, phone number, and payment information, including the type of card they have, its last four numbers, and security code, using the login email and password. The nature of the leaked data, which contains a username, password, camera name, and time zone in a standardized format, shows that it was acquired from a company database. | |||||||
| Amazon Web Services (AWS) | Data Leak | 85 | 4 | 02/2018 | AMA350181223 | Link | |
Rankiteo Explanation : Attack with significant impact with customers data leaksDescription: An Amazon S3 bucket containing scans of about 119,000 US and foreign citizens' IDs and personal information was found by researchers. The firm that owns the data, Bongo International, is owned by FedEx and supports North American retailers' and brands' online sales to customers abroad. In the AWS bucket were over 112,000 files, unencrypted data, and customer ID scans from a wide range of nations, including the US, Mexico, Canada, many EU nations, Saudi Arabia, Kuwait, Japan, Malaysia, China, and Australia. FedEx did not remove the S3 bucket until its presence was made public, despite Kromtech's best efforts to get in touch with them. | |||||||
| Amazon Web Services | Vulnerability | 60 | 3 | 8/2024 | AMA000082124 | Link | |
Rankiteo Explanation : Attack with significant impact with internal employee data leaksDescription: A vulnerability in Amazon Web Services' Application Load Balancer was discovered by security firm Miggo, which could potentially allow an attacker to bypass access controls and compromise web applications. This vulnerability was not due to a software flaw but stemmed from customers' configuration of the service, particularly the setup of authentication. Researchers identified over 15,000 web applications with potentially vulnerable configurations, though AWS disputes the figure and has contacted customers to recommend more secure setups. Exploiting this vulnerability would involve token forgery by the attacker to obtain unauthorized access to applications, escalating privileges within the system. | |||||||
Amazon Fulfillment Technologies & Robotics Company Subsidiaries
On the Fulfillment Technologies & Robotics Team, we build dynamic partnerships between people and intelligent machines. This intricate collaboration helps Amazon fulfill orders with unmatched accuracy. Since we began working with robotics, we've added over a million new jobs worldwide. Working in symphony with our robotic technology, employees have the opportunity to extend their technical capabilities by working alongside some of the industry’s most advanced technologies. This includes our fleet of autonomous mobile robots, sophisticated control software, and technologies like language perception, machine learning, object recognition, and semantic understanding of commands. These technologies help employees deliver an ever-improving customer and employee experience, as well as improve the safety of our facilities. Explore opportunities across the entire Fulfillment Technologies & Robotics team to find the right fit for you.
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AFT&R Cyber Security News
Amazon’s next-gen warehouse robots: UK’s £1bn digital defence spend; Meta backs Illinois nuclear plant
Amazon has announced a major leap forward in warehouse automation with a new initiative focused on “agentic AI” robots capable of performing ...
Introducing Vulcan: Amazon's first robot with a sense of touch
Built on advances in robotics, engineering, and physical AI, Vulcan is making our workers' jobs easier and safer while moving orders more ...
Amazon’s big bet on warehouse robots is already getting a boost from generative AI
Amazon already operates a fleet of more than 750000 robotics in the U.S. Generative AI is helping make these devices even more effective.
Amazon Inks Deal with Covariant to Advance Warehouse Automation
Amazon teams with Covariant to enhance AI-driven warehouse robotics, aiming for safer, more adaptable systems.
Amazon is using tech from a Khosla Ventures-backed startup to run robot warehouses at Whole Foods
Fulfil's technology will enable shoppers to purchase items that are not stocked at Whole Foods, such as Coca-Cola soda and Kellogg's ...
The Warehouse of the Future: Where Sci-Fi Meets Supply Chain
AI software will power the brains of the warehouse, maximizing inventory management, improving order fulfillment accuracy, and boosting ...
Amazon Adopts Autonomous Forklifts to Enhance Efficiency
They operate continuously without breaks, leading to higher productivity and reduced labour costs. Equipped with advanced sensors and AI, these ...
Amazon trials humanoid warehouse robots to support workforce
Amazon says Sparrow is the first robotic system in its warehouses that can detect, select, and handle individual products in its inventory. The ...
Amazon hires the founders of AI robotics startup Covariant
Amazon announced Friday evening that it has hired Covariant's founders — Pieter Abbeel, Peter Chen, and Rocky Duan — along with “about a ...
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Frequently Asked Questions (FAQ) on Cybersecurity Incidents
AFT&R CyberSecurity History Information
Total Incidents: According to Rankiteo, AFT&R has faced 10 incidents in the past.
Incident Types: The types of cybersecurity incidents that have occurred include ['Breach', 'Cyber Attack', 'Vulnerability', 'Data Leak'].
Total Financial Loss: The total financial loss from these incidents is estimated to be {total_financial_loss}.
Cybersecurity Posture: The company's overall cybersecurity posture is described as On the Fulfillment Technologies & Robotics Team, we build dynamic partnerships between people and intelligent machines. This intricate collaboration helps Amazon fulfill orders with unmatched accuracy. Since we began working with robotics, we've added over a million new jobs worldwide. Working in symphony with our robotic technology, employees have the opportunity to extend their technical capabilities by working alongside some of the industry’s most advanced technologies. This includes our fleet of autonomous mobile robots, sophisticated control software, and technologies like language perception, machine learning, object recognition, and semantic understanding of commands. These technologies help employees deliver an ever-improving customer and employee experience, as well as improve the safety of our facilities. Explore opportunities across the entire Fulfillment Technologies & Robotics team to find the right fit for you..
Detection and Response: The company detects and responds to cybersecurity incidents through {description_of_detection_and_response_process}.
Incident Details
Incident 1: Ransomware Attack
Title: {Incident_Title}
Description: {Brief_description_of_the_incident}
Date Detected: {Detection_Date}
Date Publicly Disclosed: {Disclosure_Date}
Date Resolved: {Resolution_Date}
Type: {Type_of_Attack}
Attack Vector: {Attack_Vector}
Vulnerability Exploited: {Vulnerability}
Threat Actor: {Threat_Actor}
Motivation: {Motivation}
Incident 2: Data Breach
Title: {Incident_Title}
Description: {Brief_description_of_the_incident}
Date Detected: {Detection_Date}
Date Publicly Disclosed: {Disclosure_Date}
Date Resolved: {Resolution_Date}
Type: {Type_of_Attack}
Attack Vector: {Attack_Vector}
Vulnerability Exploited: {Vulnerability}
Threat Actor: {Threat_Actor}
Motivation: {Motivation}
Common Attack Types: The most common types of attacks the company has faced are ['Breach', 'Data Leak'].
Identification of Attack Vectors: The company identifies the attack vectors used in incidents through {description_of_identification_process}.
Impact of the Incidents
Incident 1: Ransomware Attack
Financial Loss: {Financial_Loss}
Data Compromised: {Data_Compromised}
Systems Affected: {Systems_Affected}
Downtime: {Downtime}
Operational Impact: {Operational_Impact}
Conversion Rate Impact: {Conversion_Rate_Impact}
Revenue Loss: {Revenue_Loss}
Customer Complaints: {Customer_Complaints}
Brand Reputation Impact: {Brand_Reputation_Impact}
Legal Liabilities: {Legal_Liabilities}
Identity Theft Risk: {Identity_Theft_Risk}
Payment Information Risk: {Payment_Information_Risk}
Incident 2: Data Breach
Financial Loss: {Financial_Loss}
Data Compromised: {Data_Compromised}
Systems Affected: {Systems_Affected}
Downtime: {Downtime}
Operational Impact: {Operational_Impact}
Conversion Rate Impact: {Conversion_Rate_Impact}
Revenue Loss: {Revenue_Loss}
Customer Complaints: {Customer_Complaints}
Brand Reputation Impact: {Brand_Reputation_Impact}
Legal Liabilities: {Legal_Liabilities}
Identity Theft Risk: {Identity_Theft_Risk}
Payment Information Risk: {Payment_Information_Risk}
Average Financial Loss: The average financial loss per incident is {average_financial_loss}.
Commonly Compromised Data Types: The types of data most commonly compromised in incidents are {list_of_commonly_compromised_data_types}.
Incident 1: Ransomware Attack
Entity Name: {Entity_Name}
Entity Type: {Entity_Type}
Industry: {Industry}
Location: {Location}
Size: {Size}
Customers Affected: {Customers_Affected}
Incident 2: Data Breach
Entity Name: {Entity_Name}
Entity Type: {Entity_Type}
Industry: {Industry}
Location: {Location}
Size: {Size}
Customers Affected: {Customers_Affected}
Response to the Incidents
Incident 1: Ransomware Attack
Incident Response Plan Activated: {Yes/No}
Third Party Assistance: {Yes/No}
Law Enforcement Notified: {Yes/No}
Containment Measures: {Containment_Measures}
Remediation Measures: {Remediation_Measures}
Recovery Measures: {Recovery_Measures}
Communication Strategy: {Communication_Strategy}
Adaptive Behavioral WAF: {Adaptive_Behavioral_WAF}
On-Demand Scrubbing Services: {On_Demand_Scrubbing_Services}
Network Segmentation: {Network_Segmentation}
Enhanced Monitoring: {Enhanced_Monitoring}
Incident 2: Data Breach
Incident Response Plan Activated: {Yes/No}
Third Party Assistance: {Yes/No}
Law Enforcement Notified: {Yes/No}
Containment Measures: {Containment_Measures}
Remediation Measures: {Remediation_Measures}
Recovery Measures: {Recovery_Measures}
Communication Strategy: {Communication_Strategy}
Adaptive Behavioral WAF: {Adaptive_Behavioral_WAF}
On-Demand Scrubbing Services: {On_Demand_Scrubbing_Services}
Network Segmentation: {Network_Segmentation}
Enhanced Monitoring: {Enhanced_Monitoring}
Incident Response Plan: The company's incident response plan is described as {description_of_incident_response_plan}.
Third-Party Assistance: The company involves third-party assistance in incident response through {description_of_third_party_involvement}.
Data Breach Information
Incident 2: Data Breach
Type of Data Compromised: {Type_of_Data}
Number of Records Exposed: {Number_of_Records}
Sensitivity of Data: {Sensitivity_of_Data}
Data Exfiltration: {Yes/No}
Data Encryption: {Yes/No}
File Types Exposed: {File_Types}
Personally Identifiable Information: {Yes/No}
Prevention of Data Exfiltration: The company takes the following measures to prevent data exfiltration: {description_of_prevention_measures}.
Handling of PII Incidents: The company handles incidents involving personally identifiable information (PII) through {description_of_handling_process}.
Ransomware Information
Incident 1: Ransomware Attack
Ransom Demanded: {Ransom_Amount}
Ransom Paid: {Ransom_Paid}
Ransomware Strain: {Ransomware_Strain}
Data Encryption: {Yes/No}
Data Exfiltration: {Yes/No}
Ransom Payment Policy: The company's policy on paying ransoms in ransomware incidents is described as {description_of_ransom_payment_policy}.
Data Recovery from Ransomware: The company recovers data encrypted by ransomware through {description_of_data_recovery_process}.
Regulatory Compliance
Incident 1: Ransomware Attack
Regulations Violated: {Regulations_Violated}
Fines Imposed: {Fines_Imposed}
Legal Actions: {Legal_Actions}
Regulatory Notifications: {Regulatory_Notifications}
Incident 2: Data Breach
Regulations Violated: {Regulations_Violated}
Fines Imposed: {Fines_Imposed}
Legal Actions: {Legal_Actions}
Regulatory Notifications: {Regulatory_Notifications}
Regulatory Frameworks: The company complies with the following regulatory frameworks regarding cybersecurity: {list_of_regulatory_frameworks}.
Ensuring Regulatory Compliance: The company ensures compliance with regulatory requirements through {description_of_compliance_measures}.
Lessons Learned and Recommendations
Incident 1: Ransomware Attack
Lessons Learned: {Lessons_Learned}
Incident 2: Data Breach
Lessons Learned: {Lessons_Learned}
Incident 1: Ransomware Attack
Recommendations: {Recommendations}
Incident 2: Data Breach
Recommendations: {Recommendations}
Key Lessons Learned: The key lessons learned from past incidents are {list_of_key_lessons_learned}.
Implemented Recommendations: The company has implemented the following recommendations to improve cybersecurity: {list_of_implemented_recommendations}.
References
Additional Resources: Stakeholders can find additional resources on cybersecurity best practices at {list_of_additional_resources}.
Investigation Status
Incident 1: Ransomware Attack
Investigation Status: {Investigation_Status}
Incident 2: Data Breach
Investigation Status: {Investigation_Status}
Communication of Investigation Status: The company communicates the status of incident investigations to stakeholders through {description_of_communication_process}.
Stakeholder and Customer Advisories
Incident 1: Ransomware Attack
Stakeholder Advisories: {Stakeholder_Advisories}
Customer Advisories: {Customer_Advisories}
Incident 2: Data Breach
Stakeholder Advisories: {Stakeholder_Advisories}
Customer Advisories: {Customer_Advisories}
Advisories Provided: The company provides the following advisories to stakeholders and customers following an incident: {description_of_advisories_provided}.
Initial Access Broker
Incident 1: Ransomware Attack
Entry Point: {Entry_Point}
Reconnaissance Period: {Reconnaissance_Period}
Backdoors Established: {Backdoors_Established}
High Value Targets: {High_Value_Targets}
Data Sold on Dark Web: {Yes/No}
Incident 2: Data Breach
Entry Point: {Entry_Point}
Reconnaissance Period: {Reconnaissance_Period}
Backdoors Established: {Backdoors_Established}
High Value Targets: {High_Value_Targets}
Data Sold on Dark Web: {Yes/No}
Monitoring and Mitigation of Initial Access Brokers: The company monitors and mitigates the activities of initial access brokers through {description_of_monitoring_and_mitigation_measures}.
Post-Incident Analysis
Incident 1: Ransomware Attack
Root Causes: {Root_Causes}
Corrective Actions: {Corrective_Actions}
Incident 2: Data Breach
Root Causes: {Root_Causes}
Corrective Actions: {Corrective_Actions}
Post-Incident Analysis Process: The company's process for conducting post-incident analysis is described as {description_of_post_incident_analysis_process}.
Corrective Actions Taken: The company has taken the following corrective actions based on post-incident analysis: {list_of_corrective_actions_taken}.
Additional Questions
General Information
Ransom Payment History: The company has {paid/not_paid} ransoms in the past.
Last Ransom Demanded: The amount of the last ransom demanded was {last_ransom_amount}.
Last Attacking Group: The attacking group in the last incident was {last_attacking_group}.
Incident Details
Most Recent Incident Detected: The most recent incident detected was on {most_recent_incident_detected_date}.
Most Recent Incident Publicly Disclosed: The most recent incident publicly disclosed was on {most_recent_incident_publicly_disclosed_date}.
Most Recent Incident Resolved: The most recent incident resolved was on {most_recent_incident_resolved_date}.
Impact of the Incidents
Highest Financial Loss: The highest financial loss from an incident was {highest_financial_loss}.
Most Significant Data Compromised: The most significant data compromised in an incident was {most_significant_data_compromised}.
Most Significant System Affected: The most significant system affected in an incident was {most_significant_system_affected}.
Response to the Incidents
Third-Party Assistance in Most Recent Incident: The third-party assistance involved in the most recent incident was {third_party_assistance_in_most_recent_incident}.
Containment Measures in Most Recent Incident: The containment measures taken in the most recent incident were {containment_measures_in_most_recent_incident}.
Data Breach Information
Most Sensitive Data Compromised: The most sensitive data compromised in a breach was {most_sensitive_data_compromised}.
Number of Records Exposed: The number of records exposed in the most significant breach was {number_of_records_exposed}.
Ransomware Information
Highest Ransom Demanded: The highest ransom demanded in a ransomware incident was {highest_ransom_demanded}.
Highest Ransom Paid: The highest ransom paid in a ransomware incident was {highest_ransom_paid}.
Regulatory Compliance
Highest Fine Imposed: The highest fine imposed for a regulatory violation was {highest_fine_imposed}.
Most Significant Legal Action: The most significant legal action taken for a regulatory violation was {most_significant_legal_action}.
Lessons Learned and Recommendations
Most Significant Lesson Learned: The most significant lesson learned from past incidents was {most_significant_lesson_learned}.
Most Significant Recommendation Implemented: The most significant recommendation implemented to improve cybersecurity was {most_significant_recommendation_implemented}.
References
Most Recent Source: The most recent source of information about an incident is {most_recent_source}.
Most Recent URL for Additional Resources: The most recent URL for additional resources on cybersecurity best practices is {most_recent_url}.
Investigation Status
Current Status of Most Recent Investigation: The current status of the most recent investigation is {current_status_of_most_recent_investigation}.
Stakeholder and Customer Advisories
Most Recent Stakeholder Advisory: The most recent stakeholder advisory issued was {most_recent_stakeholder_advisory}.
Most Recent Customer Advisory: The most recent customer advisory issued was {most_recent_customer_advisory}.
Initial Access Broker
Most Recent Entry Point: The most recent entry point used by an initial access broker was {most_recent_entry_point}.
Most Recent Reconnaissance Period: The most recent reconnaissance period for an incident was {most_recent_reconnaissance_period}.
Post-Incident Analysis
Most Significant Root Cause: The most significant root cause identified in post-incident analysis was {most_significant_root_cause}.
Most Significant Corrective Action: The most significant corrective action taken based on post-incident analysis was {most_significant_corrective_action}.
What Do We Measure?
Every week, Rankiteo analyzes billions of signals to give organizations a sharper, faster view of emerging risks. With deeper, more actionable intelligence at their fingertips, security teams can outpace threat actors, respond instantly to Zero-Day attacks, and dramatically shrink their risk exposure window.
These are some of the factors we use to calculate the overall score:
Identify exposed access points, detect misconfigured SSL certificates, and uncover vulnerabilities across the network infrastructure.
Gain visibility into the software components used within an organization to detect vulnerabilities, manage risk, and ensure supply chain security.
Monitor and manage all IT assets and their configurations to ensure accurate, real-time visibility across the company's technology environment.
Leverage real-time insights on active threats, malware campaigns, and emerging vulnerabilities to proactively defend against evolving cyberattacks.
