Crisis of Context

The Crisis of Context in cybersecurity refers to the systemic challenge organizations face when attempting to make fast, accurate, and relevant security decisions because they lack the comprehensive, unified, and timely context needed to understand security alerts and events.

It is not simply an overload of alerts, but rather the difficulty in interpreting why an alert is significant and what action is truly appropriate because the necessary background information is scattered, incomplete, or siloed.

Defining the Core Problem

The crisis stems from the disparity between the volume and velocity of security data generated by modern, complex IT environments and the capacity of analysts and systems to assemble that data into meaningful context.

1. Data Siloes and Fragmentation

Modern security operations centers (SOCs) use a vast array of tools, including SIEMs, EDRs, firewalls, cloud security tools, vulnerability scanners, and identity management systems. Each tool operates as a data silo, generating logs and alerts in its own format, lacking native integration with others.

• Impact: When an alert fires in one system (e.g., EDR), the analyst often lacks immediate access to crucial related information from other systems, such as:

  • User Identity: Who is the user associated with the device (internal employee, contractor, service account)?

  • Asset Criticality: What is the business value of the affected server or workstation? (Is it a development sandbox or a primary financial database?)

  • Network Behavior: What has the user or asset done historically on the network?

  • Vulnerability Status: Is the machine already patched against this exploit, or is the alert about a zero-day on a vulnerable system?

2. Time Sensitivity and Alert Fatigue

Security incidents happen quickly. Analysts are pressured to respond in minutes, but gathering context often involves manually querying multiple disparate tools.

• Impact: The lack of context leads to alert fatigue and inefficient triage. Analysts must either:

  • Over-investigate low-priority alerts to ensure they aren't missing a critical piece of information (which can lead to slow response times to real threats).

  • Under-investigate high-priority alerts because they cannot be quickly confirmed as severe. This increases the risk of false negatives (missing an actual breach) or false positives (wasting resources on non-threats).

3. Lack of Business and Operational Context

A purely technical alert (e.g., "Outbound traffic detected on port 4444") is useless without business context. The Crisis of Context means the security team often doesn't know:

• Configuration: Is this expected traffic from a known, legitimate application, or is it a malicious beacon?

• Compliance: Does this activity violate regulatory requirements for this specific asset?

• Operational Risk: What is the immediate impact on business operations if this asset is isolated?

Consequences in Cybersecurity

The Crisis of Context has direct, negative consequences on security posture:

1. Delayed Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR): Time spent manually stitching data together significantly lengthens the duration of a security event.

2. Ineffective Automation: Security orchestration, automation, and response (SOAR) tools rely on predefined playbooks. If the input data lacks sufficient context (e.g., "Severity: High"), the automation cannot confidently execute complex, practical containment actions, forcing human intervention.

3. Increased Analyst Burnout: The repetitive, high-pressure, and often-frustrating task of manually searching for context contributes significantly to high turnover in SOCs.

Solution Focus

Addressing the Crisis of Context requires moving toward a unified security data model and employing technologies like Extended Detection and Response (XDR) and advanced SIEMs that automatically ingest, normalize, and correlate data from endpoints, networks, clouds, and identity systems to provide analysts with a single, enriched view of a security event. The goal is to present the who, what, when, where, and why instantly, enabling an analyst to use their expertise for high-level decision-making rather than data aggregation.

ThreatNG, as an all-in-one external attack surface management, digital risk protection, and security ratings solution, is designed to comprehensively address the Crisis of Context in cybersecurity by providing unified, decisive external intelligence. It achieves this through a structured approach encompassing discovery, detailed assessment, continuous monitoring, strategic reporting, and enriched repositories.

ThreatNG Capabilities for Addressing the Crisis of Context

1. External Discovery

ThreatNG begins by performing purely external unauthenticated discovery to map an organization's entire digital footprint, operating without requiring any connectors. This creates the initial inventory of assets visible to an attacker.

• Example: For a target company, ThreatNG would autonomously identify all associated subdomains, third-party vendors, mobile applications, domain name permutations, and technology stack components exposed online, building a comprehensive, attacker-centric view of the attack surface.

2. External Assessment and Security Ratings

ThreatNG transforms raw discovery data into actionable risk by performing detailed external assessments and assigning a clear A-F security rating for various risk categories. This immediately provides the necessary context—the severity and risk type—for a discovered asset.

Detailed Examples of External Assessments:

• Subdomain Takeover Susceptibility: This assessment first discovers all associated subdomains, finds CNAME records pointing to third-party services (like Heroku or Amazon/S3 ), and then performs a specific validation check to see if the CNAME points to an inactive or unclaimed resource on that vendor’s platform.

  • Example: If the subdomain test.mycompany.com has a CNAME record pointing to an inactive Heroku app (old-project-2022.herokuapp.com), ThreatNG validates the "dangling DNS" state and rates the susceptibility. This provides the context that the risk isn't a complex hack but a simple configuration oversight that an attacker could use to claim the subdomain.

• Web Application Hijack Susceptibility: The rating is based on assessing the presence or absence of key security headers on subdomains.

  • Example: ThreatNG checks for missing headers such as Content-Security-Policy (CSP) and HTTP Strict-Transport-Security (HSTS) on a web application. A poor rating (e.g., 'F') signals immediately that a simple cross-site scripting (XSS) or protocol downgrade attack is likely possible due to a lack of fundamental preventative controls.

• Cyber Risk Exposure: This comprehensive rating is derived from findings across multiple domains, including Cloud Exposure (exposed open cloud buckets), Sensitive Code Discovery and Exposure (code secret exposure), and Subdomains Intelligence (exposed ports, Private IPs, and missing headers).

  • Example: A poor rating here might be due to finding an exposed open cloud bucket combined with a subdomain exposing a Private IP and sensitive data in a public code repository. This provides the context that multiple technical vulnerabilities are converging to create a severe, multi-vector risk scenario.

• BEC & Phishing Susceptibility: This looks beyond technical assets to digital risk, basing its rating on findings like Domain Name Permutations (available and taken typosquatting domains) and missing DMARC and SPF records.

  • Example: ThreatNG finds that myc0mpany.com (a homoglyph permutation ) is available for registration, and the original company's primary domain is missing a DMARC record. The context is now clear: the organization is highly susceptible to spear-phishing attacks because domain impersonation is easy to execute and difficult for email systems to detect.

3. Continuous Monitoring

ThreatNG continuously monitors the external attack surface, digital risk, and security ratings for all organizations. This ensures the provided context is timely, eliminating the crisis caused by outdated information. If a new subdomain is deployed without HSTS, or a new vulnerability (CVE) is discovered, the risk context is updated instantly.

4. Investigation Modules

The Investigation Modules provide security teams with tools to drill down into high-risk findings, allowing them to fuse discovered vulnerabilities with decisive business and operational context.

Detailed Examples of Investigation Modules:

• Domain Intelligence: This module uses Web3 Domain Discovery to check the availability of domains like proactively .eth or .crypto.

  • Example: An organization's marketing team plans to launch an NFT project. The security team can use Domain Intelligence to find that mycompanyNFT.eth is available and register it, or find that mycompanyNFT.eth is already taken, providing the context for a potential brand impersonation risk before the project launch.

• Subdomain Intelligence: Beyond security headers, this module identifies exposed ports (such as publicly exposed RDP or VNC ports) and Known Vulnerabilities.

  • Example: A subdomain is found with an exposed RDP port and is running a software version with a CVE listed in the Known Exploited Vulnerabilities (KEV) catalog. The context is immediate: this is a highly critical, actively exploitable asset.

• Sensitive Code Exposure: This module scans for secrets and configuration files in public code repositories.

  • Example: A scan uncovers a public GitHub repository containing a hardcoded AWS Access Key ID and Secret Access Key. The context shifts from theoretical risk to an Irrefutable Attribution scenario—the compromise is definitive, and the scope could be the entire AWS environment.

5. Intelligence Repositories

The continuously updated intelligence repositories (branded as DarCache ) provide the deep, multi-source data fusion needed to enrich raw alerts with decisive context.

• Example: When a compromised credential is found in the DarCache Rupture repository, ThreatNG can correlate that technical finding with the DarCache EPSS (Exploit Prediction Scoring System) score from the Vulnerabilities repository. This contextual data allows security leaders to prioritize that leaked credential not just because it's exposed, but because the system it accesses is running software with a high predicted likelihood of being exploited soon.

6. Reporting

ThreatNG provides reporting that translates technical findings into strategic, business-aligned terms.

• Example: Instead of a report listing 50 missing security headers, the Web Application Hijack Susceptibility report is an 'F' security rating. This rating, coupled with the Reasoning and Recommendations from the Knowledgebase, immediately gives leadership the context to understand the risk and justify the investment needed to fix it. Additionally, reports map findings directly to MITRE ATT&CK techniques and GRC frameworks such as PCI DSS and NIST CSF, providing the necessary context for prioritization based on adversary behavior and regulatory requirements.

ThreatNG and Complementary Solutions

ThreatNG's capabilities—particularly the Context Engine™ and Legal-Grade Attribution—are highly complementary to existing security tools by addressing the Contextual Certainty Deficit.

• Security Monitoring (SIEM/XDR) Solutions: ThreatNG can enrich alerts from a security monitoring platform.

  • Example: An XDR system detects a suspicious logon from a new country. Instead of a manual investigation, ThreatNG's Context Engine™ provides enrichment: it immediately reveals that the user's password was found in the Compromised Credentials repository, the login IP is associated with a specific Ransomware Group in the DarCache, and the asset is rated poorly for Cyber Risk Exposure. This rich, external context elevates the ambiguous SIEM alert to a confirmed, high-priority incident, accelerating the response.

• Vulnerability & Risk Management (GRC) Solutions: ThreatNG can validate and prioritize findings for GRC tools.

  • Example: A GRC solution flags a server as having a medium-severity vulnerability (CVE). ThreatNG cross-references the server's technology stack with its DarCache Vulnerability repository, finding that the CVE is on the KEV (Known Exploited Vulnerabilities) list and has an EPSS score indicating high exploitability. ThreatNG feeds this crucial external context back into the CVE, elevating it from "medium" to "critical" for immediate patching, allowing the security team to use their resources more effectively.