[24]7.ai Company Cyber Security Posture

247.ai

[24]7.aiโ„ข customer engagement solutions use conversational artificial intelligence to understand customer intent, enabling companies to create personalized, predictive, and effortless customer experiences across all channels; attract and retain customers; boost agent productivity and satisfaction; and drive revenues while lowering costs. The worldโ€™s largest and most recognizable brands use [24]7.ai intent-driven technologies to serve several hundred million visitors through billions of conversations annually, most of which are automated. The result is an order of magnitude improvement in digital adoption, customer satisfaction, and revenue growth. For more information, visit: www.247.ai. [24]7.ai is based in San Jose, California. [24]7.ai is a registered trademark of 24/7 Customer, Inc.

[24]7.ai Company Details

Linkedin ID:

24-7-ai

Employees number:

10843 employees

Number of followers:

222702.0

NAICS:

511

Industry Type:

Software Development

Homepage:

247.ai

IP Addresses:

Scan still pending

Company ID:

[24_7179656

Scan Status:

In-progress

AI score[24]7.ai Risk Score (AI oriented)

Between 900 and 1000

This score is AI-generated and less favored by cyber insurers, who prefer the TPRM score.

globalscore[24]7.ai Global Score
blurone
Ailogo

[24]7.ai Company Scoring based on AI Models

Model NameDateDescriptionCurrent Score DifferenceScore
AVERAGE-Industry03-12-2025

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

[24]7.ai Company Cyber Security News & History

Past Incidents
0
Attack Types
0
EntityTypeSeverityImpactSeenUrl IDDetailsView

[24]7.ai Company Subsidiaries

SubsidiaryImage

[24]7.aiโ„ข customer engagement solutions use conversational artificial intelligence to understand customer intent, enabling companies to create personalized, predictive, and effortless customer experiences across all channels; attract and retain customers; boost agent productivity and satisfaction; and drive revenues while lowering costs. The worldโ€™s largest and most recognizable brands use [24]7.ai intent-driven technologies to serve several hundred million visitors through billions of conversations annually, most of which are automated. The result is an order of magnitude improvement in digital adoption, customer satisfaction, and revenue growth. For more information, visit: www.247.ai. [24]7.ai is based in San Jose, California. [24]7.ai is a registered trademark of 24/7 Customer, Inc.

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newsone

[24]7.ai Cyber Security News

2025-04-30T07:00:00.000Z
Top 10: AI-Powered Cybersecurity Solutions

Top 10: AI-Powered Cybersecurity Solutions ยท 1. Microsoft Defender ยท 2. IBM QRadar Suite ยท 3. CrowdStrike Falcon ยท 4. Palo Alto Networks Cortexย ...

2025-03-24T07:00:00.000Z
Microsoft unveils Microsoft Security Copilot agents and new protections for AI

We are excited to announce the next evolution of Security Copilot with AI agents designed to autonomously assist with critical areas such as phishing, dataย ...

2025-03-14T07:00:00.000Z
GenAI in cyber security

AI transforms cybersecurity operations by accelerating detection, streamlining workflows, and empowering understaffed teams to do more with less.

2025-01-08T08:00:00.000Z
WatchGuard Acquires ActZero to Add Scalable and Open-Platform AI Security to Deliver Simplified 24/7 MDR Services

WatchGuard acquired ActZero, known for delivering simplified cybersecurity services, to further expand and mature its innovative 24/7 MDRย ...

2025-04-18T07:00:00.000Z
From Copilot to agent โ€“ AI is growing up, and CISOs need to be ready

Agentic AI offers both opportunities and challenges that could redefine how CISOs, CIOs, and their teams defend against cyber threats.

2025-04-07T07:00:00.000Z
MSPs: AI is your answer to the $12 trillion cyber threat

MSPs can leverage AI-powered threat detection to become more proactive in their cybersecurity approach.

2025-01-30T08:00:00.000Z
SOC Analysts - Reimagining Their Role Using AI

SOC analysts face alert fatigue and AI-driven threats. AI-powered SOCs automate triage and speed up response times.

2025-04-29T18:40:21.000Z
DFIR With Breach Readiness

See why leading organizations rely on SentinelOne's DFIR for advanced forensics, relentless response, and resilient outcomes against cyber threats.

2025-03-24T07:00:00.000Z
AI agents swarm Microsoft Security Copilot

Essentially, these agents use the natural language capabilities of generative AI to automate the summarization of high-volume data like phishingย ...

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faq

Frequently Asked Questions (FAQ) on Cybersecurity Incidents

[24]7.ai CyberSecurity History Information

Total Incidents: According to Rankiteo, [24]7.ai has faced 0 incidents in the past.

Incident Types: As of the current reporting period, [24]7.ai has not encountered any cybersecurity incidents.

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 [24]7.aiโ„ข customer engagement solutions use conversational artificial intelligence to understand customer intent, enabling companies to create personalized, predictive, and effortless customer experiences across all channels; attract and retain customers; boost agent productivity and satisfaction; and drive revenues while lowering costs. The worldโ€™s largest and most recognizable brands use [24]7.ai intent-driven technologies to serve several hundred million visitors through billions of conversations annually, most of which are automated. The result is an order of magnitude improvement in digital adoption, customer satisfaction, and revenue growth. For more information, visit: www.247.ai. [24]7.ai is based in San Jose, California. [24]7.ai is a registered trademark of 24/7 Customer, Inc..

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: As of now, the company has not encountered any reported incidents involving common cyberattacks.

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

Ransomware Logo

Incident 1: Ransomware Attack

Regulations Violated: {Regulations_Violated}

Fines Imposed: {Fines_Imposed}

Legal Actions: {Legal_Actions}

Regulatory Notifications: {Regulatory_Notifications}

Data Breach Logo

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

Incident 1: Ransomware Attack

Source: {Source}

URL: {URL}

Date Accessed: {Date_Accessed}

Incident 2: Data Breach

Source: {Source}

URL: {URL}

Date Accessed: {Date_Accessed}

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?

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Incident
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Finding
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Grade
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Digital Assets

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:

Network Security

Identify exposed access points, detect misconfigured SSL certificates, and uncover vulnerabilities across the network infrastructure.

SBOM (Software Bill of Materials)

Gain visibility into the software components used within an organization to detect vulnerabilities, manage risk, and ensure supply chain security.

CMDB (Configuration Management Database)

Monitor and manage all IT assets and their configurations to ensure accurate, real-time visibility across the company's technology environment.

Threat Intelligence

Leverage real-time insights on active threats, malware campaigns, and emerging vulnerabilities to proactively defend against evolving cyberattacks.

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