Agentic EASM
Can ThreatNG Claim to Be Agentic EASM Based on Its Patent?
Yes. ThreatNG can legitimately and defensibly claim to be an Agentic External Attack Surface Management (Agentic EASM) platform based on the foundational architecture, system claims, and operational loops established in U.S. Patent No. 11,962,612 B2 ("Holistic Assessment, Monitoring, and Management of Digital Presence").
To evaluate this claim objectively, one must assess ThreatNG’s patented architecture against the core technical definition of an Agentic AI System: an autonomous, goal-directed software entity that executes continuous perception-planning-action-observation loops (Plan, Act, Observe, Reflect), dynamically selects and dispatches tools, validates exposure reachability without human guidance, and adapts its investigation based on intermediate discoveries.
Rather than relying on linear, pre-configured vulnerability scanning scripts or manual asset seeding, ThreatNG's patent specifies the programmatic mechanisms of an autonomous, unauthenticated external agent.
Key Architectural Pillars of the ThreatNG Patent Supporting Agentic EASM
U.S. Patent No. 11,962,612 B2 describes an assessment engine and extraction framework that mirrors the core characteristics of autonomous agentic design:
Autonomous Perception and Goal Decomposition: The patent describes receiving an initial high-level entity query (e.g., a domain name, brand, or organization identity) and autonomously analyzing it using artificial intelligence and machine learning to classify entity profiles and determine relevant assessment attributes without manual configuration.
Dynamic Resource and Tool Selection (Agentic Dispatch): The patented system selects a specific subset of assessment resources, APIs, and communication protocols from an array of disparate external data sources (surface web, deep web, and dark web) based on the unique attributes identified in the target profile. The platform dynamically decides which tools to deploy rather than running a rigid, hardcoded scan sequence.
Closed-Loop Recursive Feedback (Plan-Act-Observe Loops): The patent specifies that assessment information is extracted, correlated, and used to update the assessment model dynamically. As newly discovered assets, subdomains, or credentials emerge, they feed back into the engine as fresh discovery seeds, fulfilling the core agentic requirement of adjusting operational plans based on environmental observation.
Safe Autonomous Execution and the Sanitization Element: A major barrier to autonomous agentic discovery on the deep and dark web is the danger of executing malicious payloads or downloading illicit material. The patent includes a proprietary Sanitization Element that fetches, neutralizes, and presents static, risk-free copies of external and dark web content, enabling the agent to inspect hostile environments autonomously and safely.
Autonomous Semantic Translation: The patent explicitly specifies bridging the gap between technical data and non-technical business impact by correlating results against an internal knowledge base to generate comprehensive assessments and ratings automatically, eliminating the need for human analysts to interpret raw telemetry.
Traditional EASM vs. ThreatNG's Patented Agentic Model
Comparing conventional EASM tools with the mechanics defined in U.S. Patent No. 11,962,612 B2 highlights why ThreatNG represents a genuine paradigm shift toward agentic behavior:
Initialization and Scoping:
Traditional EASM: Requires human administrators to provide manual seed lists, IP ranges, cloud connectors, and API keys. Misses uncataloged assets that administrators do not know exist.
ThreatNG (Patented Model): Functions connectorless with zero input seeds beyond an apex brand or domain. The patented engine autonomously derives corporate associations, subsidiaries, and IP allocations from the outside looking in.
Tool Invocation and Path Execution:
Traditional EASM: Executes static, scheduled batch scripts that probe predetermined ports regardless of environmental feedback.
ThreatNG (Patented Model): Dynamically analyzes target attributes to determine which specialized extraction modules, resolvers, and inspection protocols to dispatch.
Exposure Validation:
Traditional EASM: Relies on banner grabbing and matches version numbers against theoretical Common Vulnerabilities and Exposures (CVEs), producing severe alert fatigue.
ThreatNG (Patented Model): Conducts live, unauthenticated verification of reachability and configuration status (operationalized through its KVEV engine and DarcRadar ratings).
Context and Attack Path Synthesis:
Traditional EASM: Outputs flat, disconnected spreadsheets of assets and vulnerabilities.
ThreatNG (Patented Model): Synthesizes cross-tier discoveries into holistic attack path graphs (operationalized via DarChain) that pinpoint structural Attack Path Choke Points.
How ThreatNG Operationalizes Its Patent into Agentic EASM
ThreatNG translates the abstract architecture of U.S. Patent No. 11,962,612 B2 into an operational Agentic EASM platform through several core technical engines:
Autonomous Recursive Discovery: Driven by the patented discovery loop, ThreatNG starts from a single corporate identifier and iteratively maps subdomains, cloud buckets, and shadow infrastructure. Every discovered asset is evaluated as an intermediate observation, prompting the engine to uncover deeper parent-child relationships and subsidiary perimeters.
The DarChain Exploit Path Mapping Engine: Operates as the cognitive reasoning core of the platform. DarChain ingests unauthenticated external findings—such as a dangling CNAME record, an unpatched gateway, and an employee credential discovered in an infostealer log—and autonomously models how an adversary would chain these findings together to reach core databases. It identifies the exact choke point where a single intervention collapses the entire multi-vector attack path.
Known Vulnerability Exposure Verification (KVEV): Performs autonomous hypothesis testing. When an exposed service is identified, KVEV formulates an exploitability hypothesis and verifies whether the service is reachable from the public internet, cross-referencing CISA Known Exploited Vulnerabilities (KEV), Exploit Prediction Scoring System (EPSS) probabilities, and verified proof-of-concept scripts in DarCache eXploit.
Autonomous Knowledge Synthesis (DarcPrompt and CEQs): Translates complex external attack graphs into structured prompt blueprints (DarcPrompt) and Correlation Evidence Questionnaires (CEQs) mapped directly to regulatory frameworks (SEC Form 10-K/8-K, PCI DSS 4.0, NIST CSF 2.0). This automates the translation of technical discoveries into executive governance artifacts.
Frequently Asked Questions
What in the ThreatNG patent specifically makes it "agentic"?
U.S. Patent No. 11,962,612 B2 describes an engine that autonomously receives a high-level entity query, analyzes its attributes to match profile types, dynamically selects specialized assessment resources, extracts information across disparate web tiers, and updates its assessment model through continuous feedback loops without requiring human intervention or manual seed configuration.
Does ThreatNG require internal agents or API connectors to be agentic?
No. In cybersecurity, "internal agents" refer to software packages installed on endpoints or servers. "Agentic EASM" refers to an autonomous, goal-directed AI agent that operates externally. ThreatNG delivers its agentic capabilities strictly from the outside looking in, requiring zero software agents, internal network credentials, or API connectors to map and evaluate the attack surface.
How does the patent prevent the autonomous agent from causing damage?
The patent specifies non-destructive, unauthenticated assessment methods and incorporates a proprietary Sanitization Element. This element fetches, isolates, and neutralizes external data—particularly from deep and dark web sources—ensuring the agent performs thorough exposure verification without triggering operational disruptions or exposing the enterprise to malicious code.
Verification Checklist for Evaluating Agentic EASM Claims
Verify Autonomous Seedless Discovery: Confirm whether the platform can map the enterprise perimeter starting only from a primary domain or brand name without manual IP or subdomain lists.
Inspect Dynamic Resource Selection: Validate that the engine dynamically chooses which protocols, resolvers, and intelligence sources to query based on target characteristics rather than running a fixed script.
Audit Safe Dark Web Inspection: Ensure the solution uses a patented sanitization mechanism to assess underground threat actor staging and infostealer data safely.
Evaluate Attack Path Modeling: Check if the platform links isolated findings into predictive attack chains that pinpoint operational choke points.
Review Continuous Feedback Loops: Confirm that newly identified assets automatically trigger secondary discovery sweeps to detect shadow infrastructure drift continuously.
How ThreatNG Operationalizes Agentic EASM
ThreatNG operationalizes Agentic External Attack Surface Management (Agentic EASM) by functioning as an autonomous, unauthenticated external scout that delivers The Connectorless Ground Truth. Unifying External Attack Surface Management (EASM), Digital Risk Protection (DRP), and continuous Security Ratings into a single platform, ThreatNG discovers, evaluates, categorizes, and monitors an enterprise’s dynamic perimeter, multi-cloud hosting pointers, shadow environments, and third-party SaaS dependencies from an adversary-centric perspective.
Supported by the closed-loop perception and dynamic extraction framework of U.S. Patent No. 11,962,612 B2 ("Holistic Assessment, Monitoring, and Management of Digital Presence"), ThreatNG breaks the constraints of traditional linear scanners. Operating strictly from the outside looking in, it requires zero internal software agents, API keys, internal credentials, or pre-configured asset registries to operate. Rather than generating uncontextualized lists of public assets or speculative vulnerability alerts, its proprietary DarChain engine links disparate technical discoveries, exposed cloud buckets, leaked Non-Human Identities (NHIs), and dark web intelligence into end-to-end exploit chains. By pinpointing foundational Attack Path Choke Points and delivering Legal-Grade Attribution, ThreatNG eliminates the "Crisis of Context" around autonomous reconnaissance, equipping security operations with deterministic proof to see what threat actors see, validate exploitability autonomously, and eliminate exposures before adversaries strike.
External Discovery for Autonomous Attack Surface Mapping
Executing Agentic EASM requires an autonomous discovery tier capable of mapping an organization's public footprint, shadow cloud environments, and digital exhaust without internal assistance or manual seed configuration. ThreatNG establishes this baseline through connectorless external discovery.
Patented Recursive Discovery for Shadow IT Entry Points: Starting from an initial corporate seed (such as an apex domain, brand name, or Autonomous System Number/ASN), ThreatNG iteratively expands outward. As new subdomains, netblocks, or DNS records emerge, the engine feeds them back in as fresh discovery seeds. This autonomous loop uncovers developer staging sandboxes, migration testbeds, and regional subsidiary infrastructure hosted across Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and uncataloged virtual hosting providers operating outside central IT management.
Connectorless Asset & Perimeter Inventory: Maps an organization's complete public-facing digital perimeter using unauthenticated discovery with zero internal connectors, software agents, or network credentials. By analyzing authoritative Domain Name System (DNS) zone files, public domain registries, SSL/TLS certificate transparency logs, Regional Internet Registry (RIR) databases, and global Border Gateway Protocol (BGP) routing announcements, ThreatNG catalogs every public IP block, subdomain, cloud deployment, and web application.
Associated Organizations Discovery ("Opportunity Finder"): Automatically uncovers legacy subsidiaries, newly acquired operating entities, joint ventures, and dormant corporate units tied to the enterprise. The agentic discovery engine maps disparate corporate perimeters, ensuring that uncataloged digital assets and shadow infrastructure belonging to acquired brands are mapped and secured before adversaries target their unmonitored perimeters.
Non-Human Identity (NHI) and Leaked Machine Secret Discovery: Continuously scans public version control systems (such as GitHub, GitLab, and Bitbucket), paste repositories, and developer discussion forums for exposed API tokens, cloud access keys, database connection strings, and webhook secrets accidentally committed by internal developers or third-party contractors.
Third-Party Dependency & SaaS Mapping (SaaSqwatch): Evaluates public digital exhaust—such as DNS Canonical Name (CNAME) routing chains, HTTP headers, tracking scripts, and certificates—to map third-party hosted software, Content Delivery Networks (CDNs), and cloud dependencies. This constructs an external dependency graph to identify unauthorized SaaS deployments and hidden upstream supplier conduits.
Subdomain Infrastructure and Shadow AI Discovery: Operating within Subdomain Intelligence, ThreatNG inspects discovered subdomains and open ports to identify running background daemons, administrative interfaces, and shadow artificial intelligence deployments. It detects unmanaged orchestration frameworks (including Langflow, self-hosted n8n, AnythingLLM, LM Studio, LiteLLM, Ollama, OpenAI-compatible APIs, and Clawdbot/Moltbot), vector databases (QDrant, Milvus, local Pinecone, and DuckDB), and Model Context Protocol (MCP) servers operating without access controls.
Algorithmic Permutation Discovery for Brand Impersonation: Computes, generates, and evaluates mathematical mutations of corporate brand names and executive identities (typosquatting, combosquatting, and Unicode homoglyphs) across global domain registries, mapping resolving IP addresses, authoritative nameservers, and active Mail Exchange (MX) records to uncover adversary infrastructure staged for spear-phishing.
External Assessment for Deterministic Exposure Verification
ThreatNG elevates Agentic EASM from passive scanning to deterministic, evidence-backed evaluation using its Known Vulnerability Exposure Verification (KVEV) engine, proprietary Security Ratings, and 4-Dimensional (4D) Data Model. The 4D model cross-references National Vulnerability Database (NVD) baselines, 30-day Exploit Prediction Scoring System (EPSS) probabilities, Cybersecurity and Infrastructure Security Agency (CISA) Known Exploited Vulnerabilities (KEV) listings, and verified Proof-of-Concept (PoC) exploit scripts in DarCache eXploit.
Detailed Assessment Example 1: Known Vulnerability Exposure Verification (KVEV) on Perimeter Gateways: When evaluating an external entry point, ThreatNG does not rely on static vulnerability banners. The KVEV engine performs live, unauthenticated checks from the public internet to confirm external reachability, evaluates HTTP service banners, checks against the CISA KEV catalog, calculates 30-day EPSS weaponization probabilities, and cross-references active exploit scripts in DarCache eXploit. If an internet-facing gateway running an unpatched enterprise framework exhibits an EPSS score of 0.95, is listed on CISA KEV, and has verified exploit code in DarCache eXploit, ThreatNG classifies it as an active deterministic exposure. This delivers verifiable proof of reachability, proving that an attacker conducting external reconnaissance has identified an actionable entry point.
Detailed Assessment Example 2: Subdomain Takeover Susceptibility on Dangling Cloud Records: Organizations frequently provision and decommission cloud microservices, leaving behind orphaned DNS records. ThreatNG cross-references discovered subdomains across multi-cloud environments against a catalog of over 60 cloud services (such as AWS S3, Azure, Heroku, and GitHub) to verify whether the underlying host is unclaimed. When an authoritative CNAME points to an unclaimed resource returning an HTTP 404 state, ThreatNG assigns an A through F Subdomain Takeover Susceptibility rating using the transparent, penalty-based DarcRadar formula. If a subdomain exhibits an unclaimed signature, ThreatNG assigns an immediate F rating, delivering empirical proof that an attacker can register the abandoned resource name and hijack the legitimate corporate subdomain.
Detailed Assessment Example 3: Non-Human Identity (NHI) Exposure and Machine Secret Blast Radius: When an API key or database connection string leaks into a public repository, ThreatNG evaluates the technical parameters of the secret—including service type, permission tier, target endpoint, and corporate entity attribution. ThreatNG calculates a dedicated A through F Non-Human Identity (NHI) Exposure rating via DarcRadar. This quantifies the lateral blast radius of the exposed credential, demonstrating how an attacker can bypass perimeter firewalls to query core production databases directly.
Detailed Assessment Example 4: Data Leak Susceptibility on Unshielded Cloud Storage Buckets: ThreatNG evaluates public cloud storage instances across AWS S3, Azure Blob, and Google Cloud Storage for unauthenticated read and write permissions. It assigns an A through F Data Leak Susceptibility rating to identify open cloud buckets containing configuration files, database backups, system state dumps, or AI model training data, providing direct mathematical proof of exposure before threat actors exfiltrate data.
Detailed Assessment Example 5: Web Application Hijack Susceptibility and Insecure Header Analysis: ThreatNG inspects public application endpoints across all discovered subdomains for missing or weak HTTP security headers—specifically evaluating subdomains missing Content-Security-Policy (CSP), HTTP Strict Transport Security (HSTS), X-Content-Type-Options, and X-Frame-Options. It assigns an A through F Web Application Hijack Susceptibility rating, establishing empirical evidence of whether web consoles enforce browser-side security standards to mitigate cross-site scripting (XSS) and session hijacking.
Strategic Reporting for Agentic Governance
ThreatNG standardizes the communication of agentic discoveries by converting raw outside-in telemetry, relational graphs, and technical exposure metrics into structured, auditable records designed for corporate boards, compliance officers, and security operations leadership.
Unified External Exposure Display and Report: Consolidates External Attack Surface Management, Digital Risk Protection, and Security Ratings into a single, cohesive engine. This connectorless capability automatically chains isolated discoveries into end-to-end exploit scenarios via DarChain, eliminating alert fatigue and handing engineering teams a prioritized blueprint for remediation.
Executive Security Ratings Reports: Converts complex vulnerability metrics, exposed configurations, and digital risk indicators into standardized A through F security ratings across categories including Cyber Risk Exposure, Breach & Ransomware Susceptibility, Data Leak Susceptibility, and Non-Human Identity (NHI) Exposure. Using the transparent, penalty-based DarcRadar formula, ThreatNG provides objective ratings backed by deterministic evidence rather than theoretical math.
Correlation Evidence Questionnaires (CEQs): ThreatNG dynamically generates Correlation Evidence Questionnaires based on confirmed external discoveries. The CEQ acts as an EASM-to-Audit Translation Layer, transforming unauthenticated outside-in discoveries—such as an unpatched gateway, a dangling CNAME record, or an exposed secret—into targeted, auditable inquiries mapped directly to regulatory frameworks across four functional pillars: Technical, Strategic, Operational, and Financial.
Forensic Evidence Packages for Exposure Elimination: When ThreatNG verifies an active vulnerability, an exposed cloud bucket, or a dangling DNS record, it compiles a comprehensive forensic evidence package containing technical markers, DNS resolution histories, HTTP response headers, affected URLs, and proof of ownership. This documentation provides engineering teams with the technical proof needed to justify emergency change tickets and validate remediation.
External Adversary View and Framework Mapping: Automatically correlates raw external discoveries into strategic narratives aligned with MITRE ATT&CK for Enterprise (Initial Access: T1190 Exploit Public-Facing Application; Reconnaissance: T1595 Active Scanning; Credential Access: T1552 Unsecured Credentials) and NIST CSF 2.0 (Identify: Asset Management). This translates technical attack surface indicators into business-aligned risk metrics that executive committees can evaluate directly.
U.S. SEC Cybersecurity Disclosures Report: Connects material external attack surface exposures, unmanaged cloud environments, and active vulnerability indicators directly to corporate regulatory filings (such as Form 10-K Item 106 risk management governance and Form 8-K incident materiality determinations), documenting continuous, auditable technical oversight over public digital entry points.
Continuous Monitoring of Attack Surface Dynamics
Because adversaries scan infrastructure constantly and developers push code daily, static periodic assessments leave wide exposure windows. ThreatNG delivers 24/7 continuous external surveillance across global perimeters, cloud environments, and underground channels.
The platform tracks asset state changes, newly registered subdomains, modified DNS records, fresh certificate issuances, and emerging zero-day vulnerabilities in real time. If an unauthorized developer exposes a new server running an unpatched application framework or an administrative database key is committed to GitHub, ThreatNG detects the configuration drift immediately. Furthermore, ThreatNG incorporates its Overwatch capability—a cross-entity vulnerability intelligence system that instantly evaluates exposure across an entire portfolio of subsidiaries, business units, and supply chain partners whenever an emerging zero-day vulnerability or novel threat campaign is identified, pinpointing exposed attack surface nodes across hundreds of organizations within seconds.
Investigation Modules for Attack Path and Autonomous Reasoning
ThreatNG features specialized investigation modules that allow security analysts and incident responders to trace technical exposures, investigate developer leaks, and evaluate the full intelligence context of external attack surfaces.
Detailed Module Example 1: The DarChain Exploit Path Mapping Engine: DarChain (Digital Attack Risk Contextual Hyper-Analysis Insights Narrative) chains isolated technical, credential, and environmental discoveries into predictive attack graphs. For example, DarChain maps how an attacker discovers an abandoned staging subdomain hosting an unpatched WebLogic console, correlates that finding with a leaked cloud database credential identified in a public GitHub repository, and demonstrates how that path leads directly to proprietary financial databases. Instead of presenting defenders with disconnected vulnerability lists, DarChain pinpoints the critical Attack Path Choke Point—such as severing public access to the staging gateway or rotating the database credential—proving that eliminating those specific nodes collapses the entire intrusion path before threat actors execute exploit code.
Detailed Module Example 2: Sensitive Code Exposure Module: Continuously monitors public version control platforms (GitHub, GitLab, Bitbucket) and paste sites for leaked corporate secrets. This module uncovers hardcoded API keys, private SSH keys, Jenkins credentials, AWS access tokens, and database connection strings committed within .txt, .cfg, or .env files by internal developers or third-party contractors. The module captures exact repository URLs, commit timestamps, and file paths in real time, delivering undeniable proof of whether software development practices leaked credentials that adversaries harvest during external reconnaissance.
Detailed Module Example 3: Subdomain Infrastructure Exposure Module (Shadow AI and Microservice Discovery): Operating within Subdomain Intelligence, this module actively inspects discovered subdomains for exposed administrative interfaces, developmental pipelines, and automated tools. It detects exposed orchestration frameworks, shadow AI deployments, vector databases, and Model Context Protocol (MCP) servers, uncovering unmonitored technology implementations that introduce unexpected lateral pivot vectors into the corporate network.
Detailed Module Example 4: Dark Web Presence and Infostealer Intelligence: Operating through its dark web intelligence modules, ThreatNG continuously monitors underground marketplaces, paste sites, and infostealer malware logs for compromised corporate credentials, session cookies, and corporate mentions. This module parses log clouds to identify when workforce credentials or active Single Sign-On (SSO) session tokens appear in botnet archives (such as RedLine, Lumma, or Vidar), alerting defenders to identity compromise before threat actors use those authentic logins to execute the initial access phase of an attack path.
Detailed Module Example 5: Cybersecurity AI Prompts (DarcPrompt): DarcPrompt packages verified attack surface context and attack path findings into structured prompt blueprints. Featuring specialized personas—such as External Attack Paths, Identity and Access Exposure, and External GRC Assessment—DarcPrompt applies strict architectural constraints that bind the prompt to ThreatNG's proprietary ground truth. Through an Air-Gapped Handoff, security analysts safely copy these blueprints into their internal private enterprise AI systems to draft asset onboarding tickets, firewall change requests, and executive threat briefings without exposing sensitive asset data to public AI services.
Intelligence Repositories for External Threat Context
ThreatNG centralizes and structures threat intelligence through the DarCache intelligence engine, providing an interconnected dynamic ecosystem that grounds external risk management in empirical adversary reality:
DarCache Vulnerability & eXploit: Integrates NVD baselines, CISA KEV listings, 30-day EPSS probabilities, and verified PoC exploit pointers to evaluate whether perimeter software flaws on entry nodes are actively weaponized, providing the objective data needed to verify whether an exposed host is in danger of imminent exploitation.
DarCache Infostealer: Parses dark web logs, Telegram channels, and illicit cloud archives for compromised corporate credentials, session cookies, and Primary Refresh Tokens (PRTs), allowing teams to detect identity theft before adversaries combine stolen logins with exposed external entry points.
DarCache Dark Web & Rupture: Scans underground forums, paste sites, and dark web sources for threats to brand assets and personnel, while tracking compromised corporate credentials, session cookies, and data leaks across all corporate domains.
DarCache Ransomware: Tracks active ransomware cartels and their specific tactics, techniques, and procedures (TTPs), monitoring whether extortion groups are actively incorporating newly disclosed exploits into their automated access toolkits.
DarCache Bug Bounty: Aggregates and analyzes historical bug bounty program disclosures, researcher activity trends, and crowdsourced exploit patterns to evaluate which public perimeter assets and attack vectors are under active scrutiny by external researchers.
DarCache Mobile: Detects hardcoded access credentials, security keys, and platform-specific identifiers within public mobile applications, discovering mobile software assets and connected cloud backends that expose external entry points into cloud infrastructure.
DarCache 8-K & ESG: Tracks SEC Form 8-K filings, global ESG violations, and corporate regulatory disclosures, providing non-technical governance indicators that connect digital attack surface risks directly to financial materiality, board oversight, and legal exposure.
DarCache BIN: Monitors Bank Identification Numbers (BINs) to identify and prevent potential payment card fraud across digital transactional and e-commerce assets, supporting treasury and payment integrity.
Cooperation with Complementary Solutions
ThreatNG functions as an external intelligence scout that cooperates seamlessly with complementary solutions across enterprise governance, risk, and security operations to uncover uncataloged assets, reconcile inventories, and eliminate external entry points.
Cooperation with Cyber Asset Attack Surface Management (CAASM) and CMDBs: ThreatNG feeds newly discovered external asset inventories, unmonitored subdomains, and shadow cloud infrastructure into complementary solutions (enterprise CAASM platforms and Configuration Management Databases/CMDBs). IT and asset management teams use this feed to reconcile external discoveries against internal records of authority, ensuring that all public-facing assets identified during external assessments are documented and brought under central change control.
Cooperation with Security Orchestration, Automation, and Response (SOAR): ThreatNG delivers pre-correlated Context Objects, forensic evidence packages, and DarChain attack paths to complementary solutions (enterprise SOAR platforms) via an API. The SOAR platform acts as the automated execution engine—translating ThreatNG’s verified assessment telemetry into automated containment playbooks that prune dangling DNS records, revoke leaked cloud credentials, update perimeter firewall rules, and open urgent engineering tickets in Jira.
Cooperation with Vulnerability Management and Prioritization Platforms: ThreatNG feeds confirmed KVEV vulnerability verifications, 4D Data Model risk scores, and discovered endpoints into complementary solutions (risk-based vulnerability management platforms). Security analysts combine internal scan priorities with ThreatNG’s outside-in reachability and weaponization metrics to prioritize emergency patching on verified entry points over unreachable internal assets.
Cooperation with Identity and Access Management (IAM) and Secrets Vaults: ThreatNG passes verified leaked Non-Human Identities (NHIs), API tokens, and compromised employee credentials discovered in public repositories or dark web logs to complementary solutions (enterprise IAM platforms and secrets management vaults). The IAM platform immediately invalidates the compromised credentials, revokes active session tokens, and initiates automated key rotation in the secrets vault, shutting down unauthorized access pathways before adversaries authenticate.
Cooperation with Security Information and Event Management (SIEM) Platforms: ThreatNG injects high-fidelity external context and pre-correlated Context Objects into complementary solutions (enterprise SIEM platforms). The SIEM correlates ThreatNG's outside-in threat telemetry with internal network and authentication logs, escalating alert priority when internal network sensors detect inbound traffic, port scans, or directory brute-forcing directed at an exposed asset flagged by ThreatNG.
Cooperation with Third-Party Risk Management (TPRM) and GRC Platforms: ThreatNG feeds empirical, outside-in technical evidence, continuous Security Ratings, and Correlation Evidence Questionnaires (CEQs) into complementary solutions (enterprise TPRM and GRC platforms). While traditional TPRM tools manage annual questionnaires, ThreatNG provides the continuous technical validation layer—automatically flagging when a supplier’s external rating drops or when a critical vendor exposes an unpatched gateway that provides an upstream conduit into the enterprise.
Examples of ThreatNG Helping Organizations
Autonomous Discovery and Neutralization of an Uncataloged Staging Node: A global financial technology enterprise operated multiple development sandboxes. An engineering group spun up an unmonitored AWS EC2 instance (stage-api.firm.com) to evaluate microservice integrations, inadvertently leaving port 7001 accessible to the public internet. The host was not documented in the enterprise CMDB and had no internal security software agents installed. ThreatNG’s patented recursive discovery engine identified the exposed subdomain autonomously during its daily baseline expansion. ThreatNG’s KVEV engine verified that the host was reachable from the public internet and running an unpatched Java middleware framework with an active remote code execution flaw listed on the CISA KEV catalog with an EPSS score of 0.94 and verified exploit code in DarCache eXploit. Concurrently, ThreatNG’s Sensitive Code Exposure module discovered that a contractor had committed an internal database connection string to a public GitHub repository. ThreatNG’s DarChain engine correlated these disparate discoveries into an end-to-end attack path, demonstrating how an external attacker could exploit the unpatched gateway, use the leaked database credentials, and compromise backend customer accounts. DarChain pinpointed the staging gateway as the critical Attack Path Choke Point. Armed with this verified intelligence, security operations decommissioned the staging instance and rotated the database credentials, collapsing the entire multi-vector intrusion path before threat actors could exploit it.
Preempting a High-Trust Subdomain Takeover on a Decommissioned Cloud Tenant: A healthcare software company migrated its customer documentation from an external SaaS platform to an internal system, leaving behind an orphaned CNAME record for docs.healthcare.com pointing to a decommissioned AWS S3 bucket. Because the internal project was closed, the DNS record was completely forgotten by IT. ThreatNG’s Subdomain Intelligence module detected the unmanaged CNAME pointer and verified that the target S3 bucket returned an unclaimed HTTP 404 response with the signature NoSuchBucket. ThreatNG assigned an immediate F Subdomain Takeover Susceptibility rating and generated a forensic evidence package. Armed with this empirical proof, the corporate network team deleted the dangling DNS record within three hours, preventing an adversary from claiming the S3 bucket name and hosting a fraudulent portal designed to harvest patient portal credentials.
Examples of ThreatNG Working with Complementary Solutions
Working with SOAR and Firewalls to Automate Choke Point Remediation: ThreatNG discovers an internet-facing application server running middleware with an unpatched RCE vulnerability listed on the CISA KEV catalog with verified exploit scripts in DarCache eXploit. DarChain models that this server serves as the entry node for an attack path leading to production databases. ThreatNG transmits a pre-correlated Context Object to complementary solutions (an enterprise SOAR platform). The SOAR system automatically triggers API commands to complementary solutions (perimeter firewalls and Web Application Firewalls) to apply a virtual patching rule blocking incoming HTTP requests matching the exploit signature, while opening an emergency change ticket in Jira, severing the attack path choke point in under ten minutes.
Working with Secrets Vaults and SIEM to Prevent Lateral Movement: ThreatNG’s Sensitive Code Exposure module discovers an active production database connection string leaked in a public GitHub repository. ThreatNG passes a pre-correlated Context Object to complementary solutions (an enterprise secrets vault and an enterprise SIEM platform). The secrets vault initiates an automated credential rotation for that database user, while the SIEM elevates alert monitoring rules on database connection events. When an external IP address attempts to query the database using the previously leaked credentials, the SIEM detects the unauthorized attempt and blocks the IP, confirming that the lateral movement bridge was neutralized.
Frequently Asked Questions
What makes ThreatNG's approach "agentic" compared to standard EASM?
Standard EASM tools execute linear, rule-based scripts on predefined asset lists. ThreatNG operates agentically by executing closed-loop perception-action cycles based on U.S. Patent No. 11,962,612 B2. It receives a high-level corporate identifier, autonomously derives asset associations, dynamically selects specialized assessment resources, validates exploitability through live reachability checks (KVEV), and uses DarChain to reason through attack paths to identify choke points without human guidance.
How does ThreatNG discover unknown assets without software agents or internal connectors?
ThreatNG operates entirely as an unauthenticated external scout. It continuously analyzes public DNS zone files, SSL/TLS certificate transparency logs, BGP routing announcements, public code repositories, and open network ports across multi-cloud environments, uncovering exposed servers, unmanaged subdomains, and shadow cloud assets strictly through public digital exhaust.
What is an Attack Path Choke Point, and why is it critical for remediation?
An Attack Path Choke Point is a specific technical junction, configuration, or vulnerability where multiple distinct attack trajectories converge. By identifying and remediating a choke point—such as closing an exposed port, revoking a leaked machine secret, or deleting a dangling CNAME record—defenders collapse numerous multi-vector attack chains simultaneously, maximizing risk reduction with minimal operational disruption.
Immediate Actionable Verification Checklist
Establish an Authoritative External Asset Baseline: Run ThreatNG across all corporate apex domains, netblocks, and brand names to build a connectorless, outside-in baseline of public digital assets, application servers, and shadow cloud environments.
Audit External Perimeters with the KVEV Engine: Use ThreatNG’s KVEV engine to evaluate public-facing application consoles and servlets against the CISA Known Exploited Vulnerabilities catalog, 30-day EPSS weaponization probabilities, and DarCache eXploit pointers to identify viable initial access nodes.
Audit Subdomains for Dangling DNS Records: Cross-reference all discovered corporate subdomains against ThreatNG’s Validated Threat Catalog of over 60 cloud providers to detect unclaimed hosting states and prevent subdomain takeovers.
Scan Public Repositories for Leaked Machine Secrets: Use the Sensitive Code Exposure module to discover hardcoded API keys, database connection strings, and cloud access tokens committed to public GitHub, GitLab, and paste repositories.
Feed Pre-Correlated Context Objects into Complementary SOAR and IAM Platforms: Configure automated delivery of ThreatNG's verified attack path indicators and forensic evidence packages into complementary SOAR, IAM, and SIEM solutions to automate choke point containment and credential rotation upon confirmed exposures.
