Contextual Content Discovery
In the realm of cybersecurity, contextual content discovery refers to the process of identifying and analyzing digital content (data, files, communications, etc.) while simultaneously understanding the surrounding circumstances or context in which that content exists. This context provides critical layers of information that go beyond the content itself, enabling more accurate risk assessment, threat detection, and incident response.
Think of it this way: simply finding a file containing the word "password" might raise a flag. However, understanding the context – where the file is located (a public-facing server vs. an encrypted user drive), who accessed it and when, what other actions were taken around the same time, and the sensitivity of the system on which it resides – paints a much clearer picture of the potential risk.
Here's a more detailed breakdown of the key aspects:
1. Content Identification:
This involves using various techniques to locate and categorize digital assets. This can include:
Keyword searching: Identifying content based on specific terms.
Data loss prevention (DLP) techniques: Recognizing sensitive data patterns (e.g., credit card numbers, social security numbers).
File type analysis: Identifying documents, executables, images, etc.
Metadata analysis: Examining information about the data, such as creation date, author, file size, and access permissions.
Hashing and fingerprinting: Identifying known malicious or sensitive files.
2. Contextual Enrichment:
This is where contextual content discovery truly shines. It involves gathering and correlating various pieces of information around the identified content to build a comprehensive understanding. This context can include:
User Context: Who created, accessed, modified, or shared the content? What are their roles, permissions, and typical behavior? Are there any anomalies in their activity?
Device Context: On what device does the content reside or through which device was it accessed? What is the security posture of that device? Is it managed or unmanaged? Is it known to be compromised?
Network Context: Where is the network traffic originating from or going to? What protocols are being used? Is the communication internal or external? Is it going to a known malicious IP address or domain?
Temporal Context: When was the content created, accessed, or modified? What other events occurred around the same time? Is there a suspicious sequence of events?
Application Context: Which application was used to create, access, or transmit the content? Are there known vulnerabilities in that application?
Process Context: What processes were running when the content was accessed or modified? Are any of these processes known to be malicious?
Location Context: Where is the device or user physically located (if that information is available and relevant)?
Threat Intelligence Context: Does the content, user behavior, or associated network activity align with known threat actor tactics, techniques, and procedures (TTPs) or indicators of compromise (IOCs)?
Business Context: How critical is the system or data associated with the content to the organization's operations? What are the potential business impacts of a security incident involving this content?
3. Analysis and Correlation:
Once the content and its surrounding context are identified and gathered, sophisticated analysis and correlation techniques are employed to:
Identify anomalies: Spot deviations from normal behavior or expected patterns.
Detect threats: Recognize patterns and indicators associated with known attacks.
Assess risk: Determine the potential impact and likelihood of a security incident.
Prioritize alerts: Focus security teams on the most critical issues.
Support investigations: Provide rich information for understanding the scope and impact of incidents.
Why is Contextual Content Discovery Important in Cybersecurity?
Improved Accuracy: Context significantly reduces false positives and negatives in security alerts. Understanding the "why" and "how" behind content access or modification leads to more accurate threat detection.
Enhanced Threat Detection: By correlating content with contextual information, organizations can identify sophisticated and insider threats that might otherwise go unnoticed.
Faster Incident Response: Contextual information provides security teams with a more complete picture of an incident, enabling faster triage, containment, and remediation.
Better Risk Management: Understanding the context of sensitive data helps organizations prioritize security controls and focus on protecting the most critical assets.
Increased Efficiency: By reducing noise and providing richer insights, contextual content discovery helps security teams work more efficiently and effectively.
Improved Compliance: Understanding the context of data access and usage can help organizations meet regulatory requirements and demonstrate due diligence.
Contextual content discovery moves beyond simply identifying data to understanding its significance within the broader security landscape. It's about connecting the dots to gain meaningful insights and make more informed security decisions. As the threat landscape becomes increasingly complex, this contextual approach is becoming indispensable for effective cybersecurity.
Here’s how ThreatNG addresses contextual content discovery in cybersecurity, using the capabilities outlined in the attached document.
ThreatNG performs purely external unauthenticated discovery, meaning it can identify digital assets without needing any internal access or credentials.
This is crucial for contextual content discovery because it establishes the external attack surface, the information visible to potential attackers. This forms a key part of the context: what information is publicly available?
Examples: ThreatNG's discovery capabilities would reveal exposed subdomains, open ports, or cloud services that an attacker could potentially leverage to access sensitive content.
ThreatNG provides various external assessment ratings that heavily rely on contextual information:
Web Application Hijack Susceptibility: Assesses potential entry points for attackers by analyzing externally accessible parts of web applications. The context here encompasses the application's structure and accessibility.
Example: ThreatNG identifies a login page with weak security headers (context) that could be susceptible to hijacking.
Subdomain Takeover Susceptibility: Evaluates the risk of attackers taking control of a website's subdomains. Context is provided by analyzing DNS records, SSL certificate statuses, and other factors related to subdomains.
Example: ThreatNG detects a subdomain with an expired SSL certificate and outdated DNS records (context), making it vulnerable to takeover.
BEC & Phishing Susceptibility: This is derived from multiple contextual factors:
Sentiment and Financials Findings
Domain Intelligence (DNS Intelligence capabilities, which include Domain Name Permutations and Web3 Domains that are available and taken; and Email Intelligence that provides email security presence and format prediction)
Dark Web Presence (Compromised Credentials)
Example: ThreatNG identifies domain name permutations that are available for registration (context from Domain Intelligence) and also detects compromised credentials on the dark web (context), thereby increasing the organization's susceptibility to BEC and Phishing.
Brand Damage Susceptibility: Assesses the risk to an organization's reputation using context from:
Attack surface intelligence
Digital risk intelligence
ESG Violations
Sentiment and Financials (Lawsuits, SEC filings, SEC Form 8-Ks, and Negative News)
Domain Intelligence (Domain Name Permutations and Web3 Domains that are available and taken)
Example: ThreatNG discovers negative news articles and social media sentiment (context) related to a potential security breach, indicating a high risk of brand damage.
Data Leak Susceptibility: Assesses the potential for sensitive data exposure using context from:
Cloud and SaaS Exposure
Dark Web Presence (Compromised Credentials)
Domain Intelligence (DNS Intelligence capabilities which include Domain Name Permutations and Web3 Domains that are available and taken; and Email Intelligence that provides email security presence and format prediction)
Sentiment and Financials (Lawsuits and SEC Form 8-Ks)
Example: ThreatNG identifies exposed cloud storage buckets (context) and compromised credentials on the dark web (context), indicating a high risk of data leaks.
Cyber Risk Exposure: Assessed using parameters from the Domain Intelligence module:
Certificates
Subdomain headers
Vulnerabilities
Sensitive ports
Example: ThreatNG discovers exposed sensitive ports and outdated certificates (context), contributing to the cyber risk exposure score.
Code Secret Exposure: Assesses the risk of sensitive information being exposed in code repositories. The context is the exposure level of code repositories and the presence of sensitive data within them.
Example: ThreatNG identifies an exposed code repository (context) containing API keys and passwords (context), indicating a high risk of code secret exposure.
Cloud and SaaS Exposure: Evaluates the security posture of cloud services and SaaS solutions. The context includes the configuration and security settings of these services.
Example: ThreatNG identifies unsanctioned cloud services (context) being used by employees, increasing the organization's risk.
ESG Exposure: Rates an organization based on discovered environmental, social, and governance (ESG) violations. The context is the nature and severity of these violations.
Example: ThreatNG identifies a history of environmental offenses (context) that impacts the organization's ESG rating.
Supply Chain & Third Party Exposure: Assesses risks associated with vendors and suppliers using context from:
Domain Intelligence (Enumeration of Vendor Technologies from DNS and Subdomains)
Technology Stack
Cloud and SaaS Exposure
Example: ThreatNG identifies a third-party vendor with a vulnerable technology stack (context), posing a supply chain risk.
Breach & Ransomware Susceptibility: Assesses the likelihood of a successful breach or ransomware attack using context from:
External attack surface and digital risk intelligence
Domain intelligence (exposed sensitive ports, exposed private IPs, and known vulnerabilities)
Dark web presence (compromised credentials, ransomware events, and gang activity)
Sentiment and financials (SEC Form 8-Ks)
Example: ThreatNG identifies compromised credentials on the dark web and exposed private IP addresses (context), significantly increasing the ransomware susceptibility score.
Mobile App Exposure: Evaluates the exposure of an organization's mobile apps by discovering them in marketplaces and analyzing their content for sensitive information. The context is the presence of access credentials, security credentials, and platform-specific identifiers within the apps.
Example: ThreatNG identifies a mobile app in an app store (context) that contains hardcoded API keys (context), indicating a high risk.
Positive Security Indicators: Identifies and highlights an organization's security strengths. Context is used to validate the effectiveness of security controls.
Example: ThreatNG detects the presence of a web application firewall (context) and validates its effectiveness from the perspective of an external attacker.
3. Reporting
ThreatNG provides various reports, including executive, technical, prioritized, and security ratings reports.
Crucially, these reports embed a knowledge base that provides context to the findings. This context includes:
Risk levels to help prioritize security efforts
Reasoning to explain the identified risks
Recommendations for risk reduction
Reference links for further investigation
Example: A report on a vulnerable web server (content) includes the risk level (high), the reasoning (it allows for potential code execution), recommendations (patch the server), and links to CVE details (context).
ThreatNG continuously monitors the external attack surface, digital risk, and security ratings.
This continuous monitoring provides temporal context, enabling organizations to observe how their security posture evolves and identify anomalies or emerging trends.
Example: ThreatNG detects a sudden increase in exposed subdomains (content) compared to the previous week (temporal context), which could indicate a misconfiguration or attack.
ThreatNG's investigation modules are designed to provide in-depth contextual information:
Domain Intelligence: Provides a wealth of information about domains, including:
Domain Overview (Digital Presence Word Cloud, Microsoft Entra Identification and Domain Enumeration, Bug Bounty Programs)
DNS Intelligence (Domain Record Analysis, Domain Name Permutations, and Web3 Domains)
Email Intelligence (Security Presence, Format Predictions, and Harvested Emails)
WHOIS Intelligence (WHOIS Analysis and Other Domains Owned)
Subdomain Intelligence (HTTP Responses, Header Analysis, Server Headers, Cloud Hosting, Content Identification, Ports, Known Vulnerabilities, Web Application Firewall Discovery, and Vendor Types)
Example: During an investigation, the Domain Intelligence module reveals that a suspicious subdomain (content) shares the same IP address as a known malicious server (as indicated in the IP Intelligence context).
IP Intelligence: Provides context about IP addresses, including shared IPs, Autonomous System Numbers (ASNs), country locations, and private IPs.
Example: An investigation reveals that multiple failed login attempts (content) originate from a range of IP addresses associated with a known botnet (IP Intelligence context).
Certificate Intelligence: Provides details about TLS certificates, including status, issuers, and associated organizations.
Example: ThreatNG identifies a certificate issued by an untrusted authority (context) being used on a company server (content), raising security concerns.
Social Media: Gathers and analyzes social media posts related to the organization. The context includes the content of the posts, hashtags, links, and tags.
Example: ThreatNG detects a spike in negative social media mentions (context) following a reported data breach (content), indicating potential reputational damage.
Sensitive Code Exposure: Discovers and analyzes exposed code repositories for sensitive information. The context refers to the type of secrets exposed (e.g., API keys, credentials) and the repository's exposure level.
Example: ThreatNG finds a public GitHub repository (context) containing AWS credentials (content), allowing an attacker to access the organization's cloud resources.
Mobile Application Discovery: Discovers mobile apps in marketplaces and analyzes their content. The context is the presence of access credentials, security credentials, and platform-specific identifiers within the apps.
Example: ThreatNG discovers an old version of a mobile app (context) with known vulnerabilities (context) in an app store.
Search Engine Exploitation: Helps users investigate an organization’s susceptibility to exposing information via search engines. The context refers to the files that are exposed.
Example: ThreatNG finds a robots.txt file (context) that inadvertently allows search engines to index admin directories (context).
Cloud and SaaS Exposure: Identifies sanctioned and unsanctioned cloud services and SaaS implementations. The context is the usage and security of these services.
Example: ThreatNG detects employees using an unsanctioned file-sharing service (context) to store sensitive data (content), creating a data leakage risk.
Online Sharing Exposure: Identifies the presence of an organizational entity on online code-sharing platforms. The context is what code is exposed.
Example: ThreatNG finds snippets of proprietary code (content) on Pastebin (context), potentially exposing intellectual property.
Sentiment and Financials: Provides context from lawsuits, layoff chatter, SEC filings, and ESG violations.
Example: ThreatNG correlates a spike in layoff chatter (context) with an increase in phishing attacks targeting employees (content), suggesting a potential insider threat.
Archived Web Pages: Discovers archived versions of web pages. The context is the content of these archived pages.
Example: ThreatNG identifies an archived version of a website (context) that contains an old admin login page (content).
Dark Web Presence: Monitors for mentions of the organization, ransomware events, and compromised credentials on the dark web.
Example: ThreatNG detects compromised credentials related to the organization (context) being sold on a dark web marketplace (context), indicating a high risk of account takeover.
Technology Stack: Identifies the technologies used by the organization. This provides context for potential vulnerabilities.
Example: ThreatNG identifies an outdated version of a web server (context), highlighting a potential vulnerability.
ThreatNG maintains intelligence repositories that provide valuable context for analysis and informed decision-making. These include:
Dark web data
Compromised credentials
Ransomware events and groups
Known vulnerabilities
ESG violations
Bug bounty programs
SEC Form 8-Ks
Bank Identification Numbers
Mobile Apps (and indicators within them)
Example: When ThreatNG identifies a potential vulnerability, it can cross-reference it with the "Known Vulnerabilities" repository to assess its severity and exploitability in context.
7. Work with Complementary Solutions
The document does not explicitly detail ThreatNG's integrations with specific complementary solutions. However, its capabilities suggest it would work well with:
SIEM (Security Information and Event Management) systems: ThreatNG's findings could be fed into a SIEM to provide external attack surface context to internal security events, improving threat detection and correlation.
SOAR (Security Orchestration, Automation, and Response) platforms: ThreatNG's data can be used to automate responses to external threats, such as blocking malicious IP addresses or taking down exposed web pages.
Vulnerability Management Systems: ThreatNG's external vulnerability assessments can complement internal vulnerability scans, providing a more comprehensive picture of an organization's security posture.
Incident Response platforms: ThreatNG's rich contextual information can significantly aid incident investigations by providing context for the external attack surface.
ThreatNG is designed to provide in-depth contextual content discovery, enabling organizations to understand their external attack surface better, assess risks, and respond to threats effectively.
