Compare Criminal IP ASM vs. ThreatProwler

Criminal IP's Attack Surface Management (ASM) is an intelligence-driven platform designed to continuously identify, catalog, and oversee all internet-connected assets linked to an organization, including overlooked and shadow resources, enabling teams to understand their actual external exposure from the perspective of potential attackers. This solution integrates automated asset detection with open-source intelligence (OSINT) methods, artificial intelligence enhancements, and sophisticated threat intelligence to reveal exposed hosts, domains, cloud services, IoT devices, and other internet-facing entry points, while also collecting evidence such as screenshots and metadata, and linking findings to known vulnerabilities and attacker techniques. By evaluating exposures through the lens of business relevance and risk, ASM emphasizes vulnerable elements and misconfigurations, providing instantaneous alerts and interactive dashboards that facilitate quicker investigations and remediation efforts. Furthermore, this comprehensive tool empowers organizations to proactively manage their security posture, ensuring that they remain vigilant against emerging threats.

ThreatProwler serves as a continuous threat exposure management (CTEM) solution that thoroughly examines your digital landscape, information assets, and applications to uncover every potential threat that may jeopardize your operations. By integrating the latest in threat intelligence, along with insights from the dark web and data breach information, it stands out as the most all-encompassing threat management tool designed specifically for small and medium-sized enterprises. Additionally, ThreatProwler boasts enterprise-level capabilities such as automatic asset identification and scoping, which helps in revealing shadow assets while allowing users to exclude certain assets from scanning. It also features comprehensive prioritization by threat severity metrics (CVSS, EPSS, KEV) and asset-specific configurations, including the option to set annualized loss expectancy. Furthermore, users benefit from an AI-driven Attack Likelihood Score (ALS), which is supported by the world's largest repository of cyber incidents and mapped to MITRE ATT&CK frameworks to estimate potential impacts accurately. This combination of features ensures that businesses can effectively manage and mitigate their cybersecurity risks.