Compare Armorblox vs. Sublime

Armorblox employs advanced natural language understanding, deep learning algorithms, and statistical methods to safeguard enterprise communications from various inbound threats and mitigate outbound data loss. The platform harnesses a diverse array of data sources, signals, and detection methodologies. It effectively combats issues such as business email compromise, account takeovers, executive impersonation, and other targeted threats. Users can examine in-depth attack analyses designed for human comprehension. The system can automatically delete, quarantine, or label emails according to set policies. It also identifies violations related to personally identifiable information (PII) and payment card information (PCI), as well as any passwords disclosed in emails. Furthermore, it prevents the distribution of outbound emails containing sensitive information. The platform is adept at thwarting lateral data leaks across various communication channels, including email, messaging, and file-sharing services. It can also auto-remediate any reported false positives swiftly. With a single click, users can eliminate similar suspicious emails from multiple user mailboxes. By utilizing dynamic policies, Armorblox enhances its ability to thwart similar attacks in the future, ensuring a robust security posture. In addition, continuous learning and adaptation to emerging threats are integral to the platform's effectiveness.

Sublime transforms the conventional black box email gateways by integrating detection-as-code with community-driven efforts to enhance security. Its binary explosion feature methodically inspects files sent as attachments or those automatically downloaded through links, identifying threats like HTML smuggling, dubious macros, and various malicious payloads. Additionally, Natural Language Understanding assesses the tone and intent of messages while utilizing the sender’s previous interactions to uncover attacks that do not rely on payloads. The Link Analysis tool employs a headless browser to render web pages and utilizes Computer Vision to scrutinize content for counterfeit brand logos, login pages, captchas, and other potentially harmful elements. Moreover, the sender analysis employs organizational context to uncover impersonation attempts targeting high-value users, thereby adding an extra layer of protection. Furthermore, Optical-Character-Recognition (OCR) efficiently extracts important entities from attachments, such as callback phone numbers, which can be crucial in identifying phishing attempts.