Decision Ready Intelligence
Decision-ready intelligence in cybersecurity is analyzed, contextualized, and verified information that enables security stakeholders—from SOC analysts to the Board of Directors—to take immediate, informed action without requiring further processing or validation.
Unlike raw data or generic threat feeds, Decision Ready Intelligence eliminates the need for the recipient to ask "So what?" or "Now what?" It connects specific threats to business impacts, providing a clear path for remediation or strategic planning.
Core Characteristics of Decision Ready Intelligence
For intelligence to be considered "decision-ready," it must satisfy specific criteria that distinguish it from noise or standard information.
High Context: It extends beyond simple indicators of compromise (IOCs) such as IP addresses or file hashes. It explains the "who, why, and how" behind a threat, including actor attribution, campaign objectives, and attack vectors.
Specific Relevance: The intelligence is filtered and tailored to the organization’s specific technology stack, industry, and risk profile. It ignores irrelevant noise (e.g., a vulnerability in software the organization does not use).
Verified Accuracy: It has been vetted to minimize false positives. Decision-makers can trust the data's source and validity without spending valuable time re-verifying it.
Clear Priority: It includes an assessment of severity and urgency, often mapped to business criticality. This helps teams understand which fires to prioritize.
Prescriptive Action: It offers recommended countermeasures or strategic adjustments. The recipient knows exactly what steps to take to mitigate the risk.
The Role of Decision Ready Intelligence in Security Operations
In the fast-paced environment of a Security Operations Center (SOC), Decision Ready Intelligence acts as a force multiplier.
Reducing Mean Time to Respond (MTTR)
Security analysts are often overwhelmed by alert fatigue. Decision-Ready Intelligence automatically enriches alerts, allowing analysts to bypass the research phase and move straight to containment and eradication.
Strategic Risk Management for CISOs
For executive leaders, Decision Ready Intelligence translates technical metrics into business language. Instead of reporting on "increased port scanning activity," it provides intelligence on "elevated risk of ransomware targeting the supply chain," allowing the CISO to justify budget adjustments or policy changes to the board.
Proactive Threat Hunting
Threat hunters use this intelligence to form hypotheses. Instead of searching blindly, they use decision-ready reports on emerging TTPs (Tactics, Techniques, and Procedures) to proactively search the network for adversaries who may have evaded automated defenses.
Decision Ready Intelligence vs. Raw Threat Data
It is critical to distinguish between data, information, and decision-ready intelligence.
Raw Data: Unprocessed facts, such as log files, netflow data, or lists of IP addresses. It has high volume but low value on its own.
Information: Data that has been organized or structured, such as a report showing a spike in login failures. It provides visibility but not necessarily insight.
Decision Ready Intelligence: Information that has been analyzed, contextualized, and prioritized. It informs the user that the login spike is a brute-force attack from a known nation-state actor targeting the finance department and that an immediate password reset and IP block are required.
Common Questions About Decision Ready Intelligence
What is the primary goal of Decision Ready Intelligence?
The primary goal is to accelerate the decision-making cycle (OODA loop—Observe, Orient, Decide, Act). It aims to reduce the time between detection and remediation by removing ambiguity.
Who is the audience for Decision Ready Intelligence?
It serves multiple audiences but in different forms.
Tactical: SOC Analysts and Incident Responders (focus on immediate blocking and remediation).
Operational: Security Managers and Threat Hunters (focus on trends and campaign tracking).
Strategic: CISOs and Board Members (focus on investment, risk appetite, and long-term security posture).
How is Decision Ready Intelligence generated?
It is generated through the Intelligence Cycle:
Planning: Defining the requirements.
Collection: Gathering raw data from internal and external sources.
Processing: Normalizing and structuring the data.
Analysis: Human or AI-driven evaluation to add context and judgment.
Dissemination: Delivering the finished product to the right stakeholder.
Why is Context important in cybersecurity intelligence?
Context determines the severity of a threat. A high-severity vulnerability (CVSS 10) on a disconnected test server has a lower risk context than a medium-severity vulnerability (CVSS 5) on a public-facing payment gateway. Decision Ready Intelligence accounts for this difference.
ThreatNG and Decision Ready Intelligence
ThreatNG facilitates Decision-Ready Intelligence by transforming the chaotic, high-volume data from an organization's external attack surface into prioritized, actionable verdicts. Rather than providing a static list of vulnerabilities, it uses a "Context Engine" and "External Contextual Attack Path Intelligence" (DarChain) to correlate technical findings with business impact, regulatory pressure, and active threat landscapes. This allows security leaders to move immediately from observation to remediation without the typical analysis paralysis caused by false positives or lack of context.
External Discovery: The Foundation of Intelligence
Decision-Ready Intelligence cannot exist without a complete asset inventory. ThreatNG’s External Discovery provides a comprehensive "outside-in" view of the infrastructure, operating purely as an unauthenticated external adversary.
This module creates intelligence by identifying:
Shadow IT: Uncovering assets created by employees outside of central IT control, which often lack standard security controls.
Forgotten Infrastructure: Locating abandoned subdomains or legacy cloud environments that are no longer monitored but remain accessible to attackers.
Third-Party Connections: Mapping the digital supply chain to reveal risks introduced by vendors, partners, or connected SaaS applications.
External Assessment: From Finding to Strategic Narrative
ThreatNG elevates assessment from simple vulnerability scanning to strategic risk analysis. By grouping technical findings into broader risk categories, it provides the "so what?" factor necessary for decision-making.
Detailed Assessment Examples
1. Subdomain Takeover Susceptibility
The Intelligence: This assessment identifies "dangling DNS" records where a subdomain points to an unclaimed third-party resource.
The Decision: Immediate revocation of the DNS record or reclaiming the cloud resource.
Detailed Example: ThreatNG identifies a subdomain pointing to an unclaimed AWS S3 bucket. The DarChain intelligence path identifies this as Subdomain Control for Phishing and Credential Harvesting. It reveals that an attacker could claim this bucket, host a phishing page on the legitimate subdomain, and leverage the organization's trust to harvest employee credentials.
2. Web Application Hijack Susceptibility
The Intelligence: This assesses the risk of client-side attacks based on the absence of headers such as Content-Security-Policy (CSP).
The Decision: Implementation of strict security headers on specific high-value subdomains.
Detailed Example: ThreatNG flags
subdomains_missing_csp. The intelligence narrative explains that this specific gap allows Cross-Site Scripting (XSS) via CSP Bypass. It details how attackers can exploit this to inject malicious scripts, leading to session hijacking and credential theft, effectively bypassing other authentication controls.
Investigation Modules: Deep-Dive Context
When a high-level risk is identified, Investigation Modules provide the granular evidence required to validate the threat and resource a response.
Domain Intelligence & Web3 Discovery
This module investigates the traditional and decentralized web presence. It uniquely supports Web3 Domain Discovery, checking domain availability and ownership (e.g., .eth and .crypto). This provides intelligence on brand impersonation risks in the blockchain space, allowing legal or security teams to decide on defensive registrations or takedowns.
Social Media & Reddit Discovery
ThreatNG manages "Narrative Risk" by monitoring platforms like Reddit. It transforms public chatter into intelligence by identifying:
Conversational Attack Surface: Discussions that reveal security flaws or employee dissatisfaction.
Insider Threat Signals: Posts that may leak internal tools, upcoming layoffs, or sensitive project codenames.
Social Engineering Pretexts: Information that attackers could use to craft highly credible spear-phishing campaigns targeting executives.
Intelligence Repositories (DarCache)
ThreatNG enriches every finding with data from its DarCache repositories, ensuring decisions are based on real-world severity rather than theoretical risk.
DarCache Vulnerability: This resolves the "Contextual Certainty Deficit" by integrating data from the National Vulnerability Database (NVD), the Exploit Prediction Scoring System (EPSS), and Known Exploited Vulnerabilities (KEV). This tells a CISO not just that a vulnerability exists, but that it is actively being exploited in the wild and has a high probability of targeting their specific stack.
DarCache Ransomware: Tracks over 100 ransomware gangs (e.g., LockBit, BlackCat) and their specific tactics. If a specific port or vulnerability is identified, ThreatNG can correlate it with the known entry vectors of these groups, thereby elevating remediation priority.
Reporting and Continuous Monitoring
Intelligence is only useful if it reaches the right stakeholder at the right time.
Strategic Reporting: ThreatNG generates reports tailored to specific audiences, such as Executive Summaries with A-F ratings for the Board, and detailed technical inventories for engineering. It also maps findings to GRC frameworks like PCI DSS, HIPAA, and GDPR, automating the "evidence gathering" phase of compliance audits.
Continuous Monitoring: The platform provides ongoing surveillance of the external attack surface. This ensures that "decision-ready" intelligence is dynamic; if a developer accidentally opens a port or exposes a cloud bucket today, the system detects it and updates the risk score immediately, triggering a new decision cycle.
Cooperation with Complementary Solutions
ThreatNG acts as a reconnaissance engine that enhances the efficacy of other security tools. Providing high-fidelity, outside-in data enables complementary solutions to focus on their core competencies with better intelligence.
Complementary Solutions for Security Operations (SIEM/SOAR)
ThreatNG complements Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) platforms by feeding them validated external alerts.
Cooperation Example: ThreatNG detects a Subdomain Takeover risk. It passes this high-confidence intelligence to the SOAR platform, which can automatically trigger a ticket for the cloud engineering team to reclaim the resource, drastically reducing the Mean Time to Remediate (MTTR).
Cooperation Example: When ThreatNG identifies Compromised Credentials in its DarCache Rupture repository, it can signal the SIEM to monitor anomalous login activity from those specific accounts, shifting the posture from reactive to proactive.
Complementary Solutions for Governance, Risk, and Compliance (GRC)
ThreatNG complements GRC platforms by automating the technical validation of compliance controls.
Cooperation Example: A GRC platform manages GDPR-related administrative policies. ThreatNG’s External GRC Assessment continuously verifies the technical implementation, including checks for specific cookie consent headers and encryption standards. This provides the GRC tool with "proof of compliance" rather than just "attestation of compliance."
Complementary Solutions for Identity and Access Management (IAM)
ThreatNG complements IAM solutions by identifying external exposures that threaten identity security.
Cooperation Example: ThreatNG’s Non-Human Identity (NHI) Exposure module detects leaked API keys or service account credentials in public code repositories. This intelligence informs the IAM team to immediately rotate those keys and review access logs for the compromised service account.
Complementary Solutions for Cloud Security (CSPM/CNAPP)
ThreatNG complements Cloud Security Posture Management (CSPM) tools by providing the adversary's perspective.
Cooperation Example: While a CSPM tool monitors internal cloud configurations, ThreatNG validates if those configurations effectively block external access. If a CSPM shows a "Private" bucket policy but ThreatNG discovers Files in Open Cloud Buckets via a misconfigured ACL or public link, it provides a critical check-and-balance that internal tools might miss.
Common Questions
How does ThreatNG prioritize which risks to fix first?
ThreatNG uses a "Context Engine" to score risks based on proven exploitability (using EPSS and KEV data), business impact (such as brand damage or data leak potential), and the presence of verified Proof-of-Concept exploits.
Does ThreatNG help with third-party vendor risk?
Yes. The Supply Chain & Third-Party Exposure rating analyzes vendors' and partners' digital footprints. This allows organizations to make informed decisions about which vendors pose a security risk before integrating them into the network.
What is the "Contextual Certainty Deficit" that ThreatNG resolves?
This refers to the industry-wide problem where security teams have too much data but not enough truth. ThreatNG resolves this by using Legal-Grade Attribution to confirm that a finding is not just a theoretical anomaly, but a verified exposure linked to a specific asset and threat vector.
