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What is Cisco Secure Malware Analytics?

Secure Malware Analytics, formerly called Threat Grid, integrates advanced sandboxing technology with in-depth threat intelligence to protect businesses from malware dangers. By tapping into a vast and detailed repository of malware knowledge, users can uncover malware behaviors, evaluate potential threats, and develop robust defense tactics. This solution methodically analyzes files and identifies any suspicious activities across your systems. With access to in-depth malware analytics and actionable threat insights, security teams can effectively understand file behaviors and quickly respond to new threats. Secure Malware Analytics compares a file's activities against millions of samples and a multitude of malware artifacts, allowing it to identify key behavioral indicators associated with various malware and their campaigns. Users are also empowered with the platform’s robust search capabilities, correlations, and thorough static and dynamic analyses, which collectively bolster their security measures. This holistic strategy not only strengthens defenses but also ensures that organizations are constantly alert and ready to tackle the ever-evolving landscape of malware threats. In doing so, it fosters a proactive security culture that can adapt to new challenges as they arise.

What is AppGuard?

Each day, adversaries develop over a million new types of malware. Traditional security solutions heavily rely on historical threat data, employing techniques such as behavioral analytics, artificial intelligence, and pattern recognition to spot malware; however, these methods often fall short in providing adequate real-time defense against new strains that may have unique features not seen before. While current security approaches emphasize malware detection, it raises the question of whether this strategy is indeed the most effective way to ensure safety. A variety of techniques are used for malware identification; for example, antivirus software depends on signature databases from past threats, machine learning algorithms generate predictive models using historical data, and behavioral analytics scrutinizes previous threats to forecast future actions. The main limitation of detection-oriented technologies is their dependency on existing malware information, which means they can only pinpoint threats already recognized and are likely to overlook emerging or adaptive threats. As the cyber threat landscape evolves rapidly, it becomes ever more vital to investigate proactive strategies that can foresee and reduce risks before they occur. Emphasizing prevention over detection may lead to a more robust defense against the continual barrage of new malware.

Media

Media

Integrations Supported

Adobe Acrobat
Check Point IPS
Check Point Infinity
Cisco SecureX
GloveBox
Microsoft 365
Microsoft Excel
ThreatConnect Risk Quantifier (RQ)

Integrations Supported

Adobe Acrobat
Check Point IPS
Check Point Infinity
Cisco SecureX
GloveBox
Microsoft 365
Microsoft Excel
ThreatConnect Risk Quantifier (RQ)

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Cisco

Date Founded

1984

Company Location

United States

Company Website

www.cisco.com

Company Facts

Organization Name

AppGuard

Company Location

Japan

Company Website

www.blueplanet-works.com/en/solution/appguard.html

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