Detect Exploits That Have
No Signature to Match
Signature-based detection is definitionally blind to zero-day exploits. TDP's ML engine detects generic zero-day exploits and file-based vulnerabilities through behavioral analysis, flagging anomalies that no signature database contains. The cloud sandbox analyzes 1.2M+ suspicious samples daily. ATI provides the vulnerability intelligence layer: 400,000+ vulnerability entries for context and correlation when a zero-day is confirmed.
Signature-Based Tools Are Blind
to Threats That Don't Have Signatures Yet
The window between a zero-day exploit being deployed in the wild and a signature being published can span days to weeks. Organizations relying exclusively on signature-based detection have zero visibility into their exposure during this window, the exact period when the exploit's impact is highest, because defenders have no countermeasures deployed.
Blind to Zero-Day Exploits
IDS/IPS systems, antivirus engines, and signature-based network detection tools cannot detect what they have no signature for, this is definitional, not a configuration failure. Zero-day exploits and novel malware families operate in this gap. The only way to detect unknown threats is to observe their behavior rather than match their code or traffic against known patterns.
Channels to Avoid Detection
Sophisticated threat actors deploying zero-day exploits route subsequent activity through legitimate protocols, HTTPS, DNS, Windows management channels, to blend into normal enterprise traffic. Even when initial exploitation is successful, post-exploitation activity is designed to look like routine system operations. Without behavioral analysis at the network and host level, these operations are invisible.
Organizations Exposed Pre-Patch
The time between a zero-day being actively exploited and a vendor issuing a patch can run from days to months. Even after a CVE is published, organizations with complex patch approval cycles may remain exposed for weeks. Without detection capabilities that don't depend on patch status, defenders have no way to identify whether exploitation has already occurred during the pre-patch window.
Behavioral Detection at the Network Layer,
Sandbox Confirmation, Vulnerability Context
TDP's ML engine establishes a behavioral baseline for every network asset, normal protocol usage, typical connection patterns, expected traffic volumes, usual lateral communication paths, and flags deviations that match zero-day exploit behavioral signatures: unusual process spawning patterns in network metadata, unexpected lateral movement after a suspicious file execution, or encrypted channels exhibiting command-response timing consistent with remote code execution.
When suspicious files are identified in network traffic, TDP submits them to the cloud sandbox for behavioral analysis, 1.2M+ samples are processed daily, returning a comprehensive behavioral report that confirms whether a file exhibits exploit or malware behavior regardless of whether a signature exists. ATI then cross-references confirmed findings against 400,000+ vulnerability intelligence entries to identify the likely vulnerability class and assess exposure scope.
- ML behavioral analysis detects zero-day exploits through anomaly detection, no signature dependency, no update lag
- Full encrypted traffic visibility catches post-exploitation activity in TLS channels that signature tools cannot inspect
- Cloud sandbox processes 1.2M+ samples daily with behavioral analysis, confirms threat without requiring a known signature match
- ATI's 400,000+ vulnerability intelligence entries provide context when a zero-day is confirmed: vulnerability class, affected systems, known exploitation patterns
- <0.03% false positive rate, behavioral ML detections are actionable, not noise requiring analyst validation before response
Three Detection Layers That Cover
What Signatures Cannot Reach
TDP's ML engine continuously models normal network behavior for every asset, establishing baselines across protocol usage, connection patterns, traffic timing, and lateral communication. Deviations consistent with zero-day exploit behavior, unusual process-to-network correlations, post-exploitation lateral movement, unexpected encrypted channels, are flagged with behavioral confidence scores independent of any signature database.
Suspicious files identified in network traffic are submitted to the TDP cloud sandbox for detonation and behavioral analysis. The sandbox observes actual file behavior, process creation, registry modifications, network callbacks, persistence mechanisms, rather than matching static code patterns. With 1.2M+ samples analyzed daily, the sandbox returns findings within minutes of submission, enabling rapid confirmation without analyst queuing.
ATI's 400,000+ vulnerability intelligence entries provide the context layer when TDP confirms a zero-day or novel exploit: vulnerability class, affected product versions, known exploitation prerequisites, related CVEs, and current exploitation campaign associations from the ATI threat actor database. This context transforms a binary "malicious/benign" sandbox verdict into an actionable incident scope assessment.
From Network Anomaly to
Confirmed Zero-Day in Minutes
TDP's zero-day detection pipeline runs without manual intervention, behavioral baselining, anomaly flagging, sandbox detonation, and ATI vulnerability correlation all execute automatically. Analysts receive a confirmed finding with full context, not a suspicious alert requiring hours of manual investigation.
TDP establishes behavioral baselines across all monitored network assets, normal protocols, typical connection patterns, expected traffic volumes, standard lateral communication paths. Baselining runs continuously, adapting to legitimate changes in network behavior over time without generating false positives from planned maintenance or infrastructure changes.
TDP's ML engine flags traffic deviations consistent with zero-day exploit behavioral patterns, unusual protocol usage after a file download, unexpected lateral movement from a workstation, encrypted command channels with timing patterns inconsistent with legitimate enterprise tools. Each anomaly is scored by confidence and severity before escalation.
Suspicious files associated with anomalous traffic are automatically submitted to the cloud sandbox. Behavioral analysis observes actual execution, process trees, network callbacks, registry activity, persistence mechanisms. Results return within minutes, providing behavioral confirmation independent of signature availability.
Confirmed findings are cross-referenced against ATI's 400,000+ vulnerability intelligence entries, identifying the vulnerability class, affected system scope, known exploitation patterns, and related threat actor campaign associations. The complete finding, network evidence, sandbox report, vulnerability context, and actor associations, is delivered to the analyst in a single alert.
What Security Teams Achieve with ThreatBook
The TDP cloud sandbox's capacity to analyze 1.2M+ samples daily means suspicious files are processed within minutes of TDP flagging them, no queuing delays, no analyst time required to initiate sandbox submission. Behavioral confirmation is automatic.
When TDP confirms a zero-day or novel exploit, ATI's vulnerability intelligence database provides immediate context, vulnerability class, affected systems, exploitation prerequisites, and related threat actor campaign data. Defenders move from detection to scoped response without additional research time.
TDP's <0.03% false positive rate on behavioral detections means analysts can investigate every TDP zero-day flag without false positive fatigue. Unlike signature-based tools where tuning to reduce false positives also reduces detection coverage, TDP's behavioral accuracy delivers both precision and coverage simultaneously.
The ThreatBook Products Behind This Use Case
Intelligence-enriched NDR with ML-based zero-day detection, full encrypted traffic visibility, and cloud sandbox analysis of 1.2M+ samples daily. <0.03% false positive rate. No signature dependency for zero-day detection. Gartner NDR Magic Quadrant 2025.
Learn moreAdvanced Threat Intelligence with 400,000+ vulnerability intelligence entries. Provides context and correlation for confirmed zero-days, vulnerability class, exploitation patterns, actor campaign associations. 99.9% accuracy across 100B+ indicators.
Learn moreDetect the Threats Your
Signatures Will Never See
Book a 30-minute session. We'll demonstrate TDP's behavioral anomaly detection on representative traffic from your network environment type and walk through how the sandbox and ATI vulnerability layer work together to confirm and scope zero-day findings.
No commitment. Response within 1 business day.