ProofPoint: MDM Providers

Add app threat intelligence and defense to MDM Solutions.

AppHawk and MDM Providers partner to provide a tightly integrated solution that allows enterprises to identify and manage the risk of Android and iOS apps on empoyees' devices. By integrating with ProofPoint, MDM Solutions mobile device management solution becomes a real-time app intelligence and defense tool.

  • Identifies apps that steal user identities, leak corporate data, and other risky behaviors
  • Fuses layers of advanced app analysis with external threat intelligence feeds to determine app risk
  • Provides multiple, automatic remediation options for dangerous apps
  • Allows companies to safely roll out BYOD programs, as well as company-owned devices, to employees with iOS and Android devices

Dynamic scoring of app risk

AppHawk analyzes and applies a dynamic risk score for each app, enabling IT administrators to use MDM App Security and Access Control to create policies that restrict network access to devices, or remove apps, that exceed acceptable risk levels.

  • ProofPoint automates the analysis of each app against more than 500 dangerous behaviors and provides the composite ProofPoint Mobile Risk Scoreâ„¢ (MMRS) for each device
  • The MMRS is a comprehensive mobility security metric, uniquely factoring the risk of each user's behavior, individual apps, wireless and cellular networks, and devices
  • Administrators easily tune risk tolerance for their business, setting policies to automatically remediate threats, allowing enterprises to trust users, devices, networks and apps, even in a BYOD environment

Comprehensive app analysis

ProofPoint Labs, the research and response team of analysts behind AppHawk, has analyzed 2 million Android and iOS apps, testing for more than 500 dangerous behaviors, including malware, spyware, and apps that take users to phishing sites or communicate with botnet command and control servers. ProofPoint Labs conducts a combination of static, dynamic and behavioral analysis on public, paid and private apps.

  • Static app analysis reveals and analyzes the developer's code, third party software, libraries, API calls, and app functions
  • Behavioral app analysis entails running apps in an instrumented kernel to simulate user behavior in a run-time environment, collecting thousands of key risk metrics, such as whether an app exfiltrates data, attempts to perform prohibited behaviors, and where network connections are made
  • Dynamic app analysis periodically re-tests apps to ensure that behavior does not maliciously change over time
  • A critical level of testing, dynamic analysis can reveal whether an app changes its operating characteristics over time or combines with other apps to perform malicious behaviors