Most email attacks begin by convincing recipients they are communicating with someone they already trust. RMail ICES analyses sender identity, authentication, behavioural signals, and lookalike indicators to protect against BEC, executive impersonation, vendor fraud, account takeover, fake IT support, and lookalike identities.
Attackers increasingly hide behind lookalike domains, DNS swaps, newly registered sites, cloud hosting, and shared-link infrastructure. RMail ICES reveals where links actually lead and identifies hidden infrastructure risks before users click, protecting against credential theft, malicious redirects, DNS manipulation, fake portals, phishing kits, and attacker-controlled file links.
Threats are often concealed within message content, attachments, metadata, QR codes, shared documents, or embedded files. RMail ICES analyses these elements to uncover malware delivery, document fraud, AI-generated attachments, hidden prompts, confidential data exposure, and fraudulent invoice indicators that traditional scanning may overlook.
Sophisticated attacks target business processes rather than technical vulnerabilities. RMail ICES evaluates the intent behind every message to determine whether requested actions align with expected business workflows to identify social engineering, BEC, payment diversion, payroll fraud, credential harvesting, vendor workflow abuse, and process bypass.
AI enables attackers to create increasingly convincing, adaptive, multilingual phishing campaigns. RMail ICES detects AI-assisted attacks before employees or AI assistants trust, summarise, forward, or act on them to protect against AI-generated phishing, polymorphic lures, prompt injection, deepfake meeting risk, AI-polished impersonation, and AI-driven account takeover.
As employees and AI agents increasingly interact with business email, organisations need visibility into where AI introduces governance, compliance, or data leakage concerns. RMail ICES surfaces AI-related signals across messages, attachments, recipients, links, summaries, and workflows for shadow AI leakage, strategic data exposure, confidential content reuse, AI-generated outbound mistakes, and compliance blind spots.
