RPost Launches RAPTOR AI Cyber Intelligence Division Centered on Threat Intel Attribution

RAPTOR AI Threat Intelligence Identifies Cybercriminal Recon to Pre-empt the Attack.

May 21, 2026 – Los Angeles, CA

RPost announces the launch of its RAPTOR™ AI Cyber Intelligence Division, a specialized threat intelligence and attribution team centered on identifying cybercriminal reconnaissance, infrastructure masking, synthetic browser identities, and transaction-centric fraud campaigns before these activities mature into successful attacks. The new division extends RPost’s RAPTOR™ AI ecosystem deeper into the world of threat intelligence attribution, focusing on what RPost calls PRE-Crime™ cybersecurity -- preemptively and offensively detecting the crime building up beyond one’s endpoints after the hook is in, but before the steal. RAPTOR AI centers on seeing what is currently unseen, outside the purview of other defensive cybersecurity tools that focus on endpoints, perimeters, and internal.

Threat actors often build their attacks from compromised third-party accounts, supplier systems, customer inboxes, consultant email threads, file-share links, and data room interactions. RPost’s approach generates and analyzes new forensic telemetry from communications and digital content interactions -- not only within the enterprise, but also across third- and fourth-party content ecosystems.

“RAPTOR AI Cyber Intelligence gives organizations a way to see what they cannot otherwise see -- cybercriminals conducting reconnaissance beyond their endpoints, often inside compromised third-party systems,” states RPost CEO Zafar Khan. “Once RAPTOR AI identifies the threat actor’s forensic fingerprints, our Cyber Intelligence team can categorize, name, and attribute these patterns by risk type, threat type, cybercriminal objective, sophistication, and origin.”

The RAPTOR AI Cyber Intelligence architecture combines layered AI agents designed to preserve raw protocol-derived telemetry, enrich it with contextual intelligence, apply large language model reasoning, suppress false positives, and recursively hunt for hidden operational fingerprints that may otherwise evade traditional endpoint and rule-based detection systems.

This layered model includes:

Layer 1 - Raw Protocol Data Generation Layer

Layer 2 - Derivative Metadata Intelligence Layer

Layer 3 - Large Language Model Semantic Insight Layer

Layer 4 - Cross-Association False Positive Suppression Layer 

Layer 5 - Recursive Fingerprint Discovery and False Negative Reduction Layer

RAPTOR AI can detect anomalies within behavior that appears normal, while also reducing false positives when deeper context shows suspicious activity is actually expected. By enriching signals with geolocation, network intelligence, recipient behavior, and transaction context, it uncovers hidden risk across high-value workflows such as logistics, escrow, legal settlements, invoices, and sensitive data-room activity.

“Most security tools wait for malware, credential theft, or suspicious endpoint behavior,” adds Khan. “RPost’s PRE-Crime approach is different. RAPTOR AI looks at the reconnaissance and context-harvesting phase -- the stage where cybercriminals learn who is communicating with whom, about what, when, and why. Our goal is to remove that fuel before it becomes the lure.”

RPost has previously been recognized by Gartner Research as a representative vendor, early adopter, visionary, and leading technology innovator for its PRE-Crime™ preemptive cybersecurity solutions in two Emerging Tech Impact Radar reports. Gartner’s cited reports include Emerging Tech Impact Radar: 2025 and Emerging Tech Impact Radar: Preemptive Cybersecurity. 

RPost’s PRE-Crime innovations have also been highlighted by Aragon Research, which identified a new AI category, Preemptive Intelligent Content Security, and named RPost as a Pioneer and Representative Vendor for its PRE-Crime solutions. Aragon Research’s note describes RPost’s unique position in powering enterprise content with RAPTOR AI insights, assistants, agents, and active preemptive security intelligence. 

The new RAPTOR AI Cyber Intelligence Division will focus on turning these discoveries into practical threat intelligence: categorizing and naming threat actor patterns, mapping cybercriminal tradecraft, reducing security operations analyst workload, minimizing false positives, reducing false negatives, and hunting for otherwise masked reconnaissance activity across large-scale communication and transaction ecosystems. “We’re targeting an earlier phase of the cybercrime than what others do, we’re seeing the cross-border handoff of cybercriminal lead generation tools often of Russian origin and then hand off to the wire fraud social engineering specialists often of West African origin; before the attack or impersonation happens,” says Khan.

RPost’s RAPTOR AI ecosystem includes three AI pillars: Intelligent Workflows, Intelligent Content, and Intelligent PRE-Crime Cybersecurity. Its recent release of Agentic Intelligent Workflows with Anthropic MCP-server standards connected RPost content platforms -- RMail®, RSign®, RForms™, RDocs®, and Registered™ -- into AI agent workflows for eSignatures, email encryption, secure file sharing, document rights, proof of delivery compliance, and other content security functions. 

About RPost:

We’re the global leader in premium, feature-rich and more affordable intelligent content security solutions, and we’ve been named by world leading analysts a leader, pioneer, and visionary in part because we are continuously innovating for our customers the world over, since 2000.

From within our three main platforms: RMail® email security, DLP and compliance, RSign® eSignatures and RDocs™ document security and information rights management, we’re everything our customers need when it comes to email, document and form security, compliance, and workplace acceleration — track, prove, eSign, encrypt, share, certify, control, cure — and now all powered up with RAPTOR™ AI PRE-Crime™ preemptive cybersecurity. We do what no other company does — all in one.