Company Details
airbnb
58,281
3,074,256
5112
airbnb.com
189
AIR_1562828
Completed

Airbnb Company CyberSecurity Posture
airbnb.comAirbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays, experiences and services that make it possible for guests to connect with communities in a more authentic way.
Company Details
airbnb
58,281
3,074,256
5112
airbnb.com
189
AIR_1562828
Completed
Between 800 and 849

Airbnb Global Score (TPRM)XXXX

Description: The article discusses how Airbnb, a major tech sharing economy platform, is vulnerable to scammers who use delusive speech to deceive users. Scammers create fake listings and reviews, luring victims into financial and physical danger. Victims have experienced assaults, robberies, and even more severe crimes. The platform's trust mechanisms have flaws, allowing scammers to bypass verifications and continue their fraudulent activities.


Airbnb has 127.27% more incidents than the average of same-industry companies with at least one recorded incident.
Airbnb has 56.25% more incidents than the average of all companies with at least one recorded incident.
Airbnb reported 1 incidents this year: 1 cyber attacks, 0 ransomware, 0 vulnerabilities, 0 data breaches, compared to industry peers with at least 1 incident.
Airbnb cyber incidents detection timeline including parent company and subsidiaries

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays, experiences and services that make it possible for guests to connect with communities in a more authentic way.


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Explore insights on cybersecurity incidents, risk posture, and Rankiteo's assessments.
The official website of Airbnb is http://airbnb.com.
According to Rankiteo, Airbnb’s AI-generated cybersecurity score is 810, reflecting their Good security posture.
According to Rankiteo, Airbnb currently holds 0 security badges, indicating that no recognized compliance certifications are currently verified for the organization.
According to Rankiteo, Airbnb is not certified under SOC 2 Type 1.
According to Rankiteo, Airbnb does not hold a SOC 2 Type 2 certification.
According to Rankiteo, Airbnb is not listed as GDPR compliant.
According to Rankiteo, Airbnb does not currently maintain PCI DSS compliance.
According to Rankiteo, Airbnb is not compliant with HIPAA regulations.
According to Rankiteo,Airbnb is not certified under ISO 27001, indicating the absence of a formally recognized information security management framework.
Airbnb operates primarily in the Software Development industry.
Airbnb employs approximately 58,281 people worldwide.
Airbnb presently has no subsidiaries across any sectors.
Airbnb’s official LinkedIn profile has approximately 3,074,256 followers.
Airbnb is classified under the NAICS code 5112, which corresponds to Software Publishers.
No, Airbnb does not have a profile on Crunchbase.
Yes, Airbnb maintains an official LinkedIn profile, which is actively utilized for branding and talent engagement, which can be accessed here: https://www.linkedin.com/company/airbnb.
As of November 27, 2025, Rankiteo reports that Airbnb has experienced 1 cybersecurity incidents.
Airbnb has an estimated 26,594 peer or competitor companies worldwide.
Incident Types: The types of cybersecurity incidents that have occurred include Cyber Attack.
Detection and Response: The company detects and responds to cybersecurity incidents through an containment measures with trust and safety mechanisms, containment measures with rapid response teams, containment measures with travel insurance for guests, and remediation measures with machine learning technology to stop fake listings..
Title: Airbnb Scams and Delusive Speech
Description: Big tech sharing economy platforms like Airbnb and Uber are marketed as trustworthy, but a new book by a South African media scholar argues that they are highly vulnerable to scammers who spread delusive speech (a form of disinformation, designed to deceive by criminal intent).
Type: Disinformation and Scams
Attack Vector: Phantom listing scamBait and switch scamsFake positive reviewsMisleading property imagesDelusive tactics
Vulnerability Exploited: Trust in the platform's review system and verification processes
Threat Actor: Scammers and criminal hosts
Motivation: Criminal intent or nefarious financial gain
Common Attack Types: The most common types of attacks the company has faced is Cyber Attack.
Identification of Attack Vectors: The company identifies the attack vectors used in incidents through Fake listings and reviews.

Brand Reputation Impact: Potential damage to Airbnb's brand reputation
Payment Information Risk: Guests redirected to alternative payment methods

Entity Name: Airbnb
Entity Type: Sharing Economy Platform
Industry: Travel and Accommodation
Location: Global
Customers Affected: Multiple victims from around the world

Containment Measures: Trust and safety mechanismsRapid response teamsTravel insurance for guests
Remediation Measures: Machine learning technology to stop fake listings
Prevention of Data Exfiltration: The company takes the following measures to prevent data exfiltration: Machine learning technology to stop fake listings, .
Handling of PII Incidents: The company handles incidents involving personally identifiable information (PII) through by trust and safety mechanisms, rapid response teams, travel insurance for guests and .

Lessons Learned: Airbnb's review curation mechanisms should be revamped according to internationally recognised human rights frameworks that protect freedom of speech. Protocol for swiftly removing offending listings should be developed.

Recommendations: Travellers should be extra cautious, seek recommendations from trusted sources, consider established hotels, check property locations on Google Street View, have a Plan B, and always buy travel insurance.
Key Lessons Learned: The key lessons learned from past incidents are Airbnb's review curation mechanisms should be revamped according to internationally recognised human rights frameworks that protect freedom of speech. Protocol for swiftly removing offending listings should be developed.
Implemented Recommendations: The company has implemented the following recommendations to improve cybersecurity: Travellers should be extra cautious, seek recommendations from trusted sources, consider established hotels, check property locations on Google Street View, have a Plan B and and always buy travel insurance..

Source: The Conversation
Additional Resources: Stakeholders can find additional resources on cybersecurity best practices at and Source: The ConversationUrl: https://theconversation.com.

Entry Point: Fake listings and reviews

Root Causes: Flaws in Airbnb's verification processes and review curation mechanisms
Corrective Actions: Revamp review curation mechanisms and develop a protocol for removing offending listings
Corrective Actions Taken: The company has taken the following corrective actions based on post-incident analysis: Revamp review curation mechanisms and develop a protocol for removing offending listings.
Last Attacking Group: The attacking group in the last incident was an Scammers and criminal hosts.
Containment Measures in Most Recent Incident: The containment measures taken in the most recent incident was Trust and safety mechanismsRapid response teamsTravel insurance for guests.
Most Significant Lesson Learned: The most significant lesson learned from past incidents was Airbnb's review curation mechanisms should be revamped according to internationally recognised human rights frameworks that protect freedom of speech. Protocol for swiftly removing offending listings should be developed.
Most Significant Recommendation Implemented: The most significant recommendation implemented to improve cybersecurity was Travellers should be extra cautious, seek recommendations from trusted sources, consider established hotels, check property locations on Google Street View, have a Plan B and and always buy travel insurance..
Most Recent Source: The most recent source of information about an incident is The Conversation.
Most Recent URL for Additional Resources: The most recent URL for additional resources on cybersecurity best practices is https://theconversation.com .
Most Recent Entry Point: The most recent entry point used by an initial access broker was an Fake listings and reviews.
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Forge (also called `node-forge`) is a native implementation of Transport Layer Security in JavaScript. An Uncontrolled Recursion vulnerability in node-forge versions 1.3.1 and below enables remote, unauthenticated attackers to craft deep ASN.1 structures that trigger unbounded recursive parsing. This leads to a Denial-of-Service (DoS) via stack exhaustion when parsing untrusted DER inputs. This issue has been patched in version 1.3.2.
Forge (also called `node-forge`) is a native implementation of Transport Layer Security in JavaScript. An Integer Overflow vulnerability in node-forge versions 1.3.1 and below enables remote, unauthenticated attackers to craft ASN.1 structures containing OIDs with oversized arcs. These arcs may be decoded as smaller, trusted OIDs due to 32-bit bitwise truncation, enabling the bypass of downstream OID-based security decisions. This issue has been patched in version 1.3.2.
Suricata is a network IDS, IPS and NSM engine developed by the OISF (Open Information Security Foundation) and the Suricata community. Prior to versions 7.0.13 and 8.0.2, working with large buffers in Lua scripts can lead to a stack overflow. Users of Lua rules and output scripts may be affected when working with large buffers. This includes a rule passing a large buffer to a Lua script. This issue has been patched in versions 7.0.13 and 8.0.2. A workaround for this issue involves disabling Lua rules and output scripts, or making sure limits, such as stream.depth.reassembly and HTTP response body limits (response-body-limit), are set to less than half the stack size.
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