Claims-Based Assessments
In cybersecurity and third-party risk management (TPRM), a claims-based assessment is an evaluation method that relies on an organization's self-reported information about its security controls, policies, and posture. Instead of using independent technical verification, the assessing party reviews "claims" made by the target company to determine their level of risk or compliance.
What is a Claims-Based Assessment?
A claims-based assessment is a subjective security review in which an organization describes its internal environment. These assessments are typically conducted through detailed questionnaires or surveys where IT and security teams attest to the presence and effectiveness of specific security measures, such as encryption standards, multi-factor authentication (MFA) usage, and incident response plans.
Standard Formats of Claims-Based Assessments
These assessments are standard in vendor risk management and regulatory compliance. Common formats include:
Security Questionnaires: Standardized lists of questions (such as the SIG or CAIQ) sent to vendors to understand their security practices.
Self-Attestations: Legal or formal statements signed by an officer of the company claiming that the organization meets a specific security standard.
Compliance Checklists: Internal reviews in which teams check off requirements for frameworks such as SOC2, HIPAA, or PCI DSS based on their internal understanding of their controls.
Narrative Descriptions: Written explanations of how an organization handles data protection, backup recovery, and employee training.
The Limitations of Claims-Based Security Reviews
While claims-based assessments are widely used due to their low technical barrier, they have significant drawbacks in a modern threat landscape:
Subjectivity and Bias: Responses are provided by the organization being assessed, which can lead to unintentional optimism or "checking the box" to maintain business relationships.
Point-in-Time Nature: A questionnaire only reflects the state of security on the day it was completed and does not account for configuration drift or new vulnerabilities that appear shortly after.
Lack of Technical Evidence: These assessments do not verify if a control is actually working. For example, a company may claim it uses MFA, but the evaluation does not confirm that MFA is enforced across all critical systems.
Human Error: Personnel filling out the forms may not have complete visibility into each department's technical implementation, leading to inaccurate or incomplete data.
Claims-Based vs. Evidence-Based Assessments
The primary alternative to a claims-based approach is an evidence-based (or observation-based) assessment.
Claims-Based: Relies on what a company says it does (e.g., "We have a firewall in place").
Evidence-Based: Relies on what a security tool or auditor can see (e.g., "A scan shows an active Web Application Firewall protecting the primary domain").
Modern cybersecurity strategies are shifting away from purely claims-based models toward continuous monitoring and automated evidence collection to ensure a more accurate representation of risk.
Frequently Asked Questions
Why do companies still use claims-based assessments?
They remain popular because they are cost-effective, require no technical integration between companies, and allow for a broad overview of administrative and physical security controls that cannot be easily scanned from the outside.
Can a claims-based assessment lead to a data breach?
By itself, an assessment does not cause a breach. However, relying on inaccurate or outdated claims can lead to a "contextual certainty deficit," where a company assumes its vendors are secure when they actually have critical, unmonitored exposures.
How can organizations improve claims-based reviews?
Organizations can improve these reviews by pairing them with external attack surface management (EASM) tools to verify technical claims with real-world, observed evidence.
ThreatNG serves as a comprehensive external attack surface management (EASM) and digital risk protection platform, providing a proactive shield against Claims-Based Assessment risks. By providing objective, unauthenticated, and observed evidence of an organization's digital posture, it replaces subjective self-reporting with irrefutable technical facts.
Proactive External Discovery and Contextual Evidence
ThreatNG uses purely external unauthenticated discovery—meaning it requires no internal connectors or agents—to identify the entire breadth of an organization's digital footprint. This "outside-in" perspective is vital for validating claims made in security questionnaires, as it uncovers what an attacker can actually see and exploit4444.
Shadow IT Discovery: ThreatNG scans the public internet to find subdomains, cloud buckets, and code repositories that may have been omitted from a vendor's internal inventory or claims-based report.
Automated Asset Inventory: The platform maintains an inventory of all discovered assets, including those hosted on major cloud providers such as AWS, Azure, and Google Cloud, ensuring the scope of an assessment aligns with reality.
Detailed External Assessments and Security Ratings
ThreatNG performs a variety of specialized assessments that assign A-F security ratings based on observed data. These ratings provide a direct counterpoint to claims-based assessments by providing empirical scores for technical controls.
Examples of Technical Assessments
Web Application Hijack Susceptibility: Instead of trusting a claim that a site is secure, ThreatNG assesses the presence or absence of key security headers like Content-Security-Policy (CSP) and HSTS.
Subdomain Takeover Susceptibility: The platform performs DNS enumeration to find CNAME records pointing to inactive or unclaimed third-party services, identifying "dangling DNS" risks that manual questionnaires often miss.
Cyber Risk Exposure: This assessment aggregates findings across invalid certificates, exposed open cloud buckets, and leaked code secrets to provide a technical reality check on an organization's overall hygiene.
ESG and GRC Exposure: ThreatNG goes beyond technical leaks to monitor for publicly disclosed environmental, social, and governance (ESG) violations and maps findings to frameworks like PCI DSS, HIPAA, and GDPR.
Specialized Investigation Modules
ThreatNG provides granular investigation modules that transform raw discovery into deep-dive intelligence, helping investigators verify or debunk specific security claims.
Sensitive Code and Cloud Exposure
Code Repository Scans: This module discovers public code repositories and identifies leaked access credentials, such as Stripe API keys, AWS secret access keys, and GitHub access tokens. For example, if a vendor claims to have a "no-secrets-in-code" policy, ThreatNG can provide direct evidence of a leaked RSA private key in a public GitHub Gist.
SaaSqwatch (Cloud/SaaS Exposure): This module identifies both sanctioned and unsanctioned SaaS implementations, such as Salesforce, Slack, or Snowflake, ensuring that the "claims" made about third-party data storage are accurate.
Social Media and Narrative Risk
Reddit and LinkedIn Discovery: ThreatNG monitors the "Conversational Attack Surface" by scanning public chatter on Reddit to identify emerging threats or threat actor plans before they mature.
Username Exposure: This module performs reconnaissance across over 1,000 sites—including social media, developer forums, and gaming sites—to see if sensitive corporate usernames or service accounts are exposed or being impersonated.
Continuous Monitoring and Strategic Reporting
A primary weakness of claims-based assessments is their "point-in-time" nature. ThreatNG solves this through persistent oversight.
Continuous Monitoring: ThreatNG provides 24/7 monitoring of the external attack surface and digital risk, ensuring that security ratings reflect real-time changes rather than an annual survey.
Prioritized Reporting: The platform generates Executive and Technical reports that prioritize risks (High to Informational), allowing leaders to focus on the most critical discrepancies between claims and reality.
Correlation Evidence Questionnaire (CEQ): This dynamically generated tool leverages the Context Engine™ to replace static surveys with irrefutable, observed evidence of risk, resolving the "Contextual Certainty Deficit".
Intelligence Repositories (DarCache)
ThreatNG maintains the DarCache repositories—continuously updated databases that provide context to discovered risks.
DarCache Dark Web: Tracks mentions of defined people, places, or things on the dark web, identifying if threat actors are targeting an organization.
DarCache Ransomware: Monitors the activities of over 70 ransomware gangs, providing immediate insight if a vendor has been involved in a recent extortion event.
DarCache Vulnerability: Integrates NVD, KEV, and EPSS data to identify which technical vulnerabilities on the attack surface are actively being exploited in the wild.
Cooperation with Complementary Solutions
ThreatNG functions as an essential intelligence feeder that empowers other security tools to move beyond claims-based assumptions.
Security Orchestration, Automation, and Response (SOAR): ThreatNG provides the "Legal-Grade Attribution" and irrefutable evidence needed for SOAR platforms to automatically trigger incident response playbooks when an external exposure is discovered.
Governance, Risk, and Compliance (GRC) Tools: By feeding continuous, outside-in evaluation data into internal GRC platforms, ThreatNG ensures that compliance dashboards reflect real-world technical evidence rather than just human attestation.
Endpoint Detection and Response (EDR): While EDR protects the internal network, ThreatNG identifies the external "Attack Path Choke Points" that adversaries use to bypass those defenses, allowing teams to disrupt breach narratives before they reach the endpoint.
Identity and Access Management (IAM): ThreatNG identifies compromised credentials and non-human identity (NHI) exposures on the dark web, allowing IAM systems to proactively mandate password resets or adjust access levels based on external risk.
Frequently Asked Questions
How does ThreatNG solve the "Contextual Certainty Deficit"?
It uses the Context Engine™ to fuse technical security findings with decisive legal, financial, and operational context. This provides "Legal-Grade Attribution," which is the absolute certainty required to justify security investments and prioritize remediation.
Can ThreatNG detect vulnerabilities in my specific technology stack?
Yes. The platform's Technology Stack Investigation Module provides unauthenticated discovery of nearly 4,000 technologies—from databases to AI models—and cross-references them with its vulnerability intelligence repository to identify real-world risks.
What is DarChain?
DarChain (Digital Attack Risk Contextual Hyper-Analysis Insights Narrative) correlates technical, social, and regulatory findings into a narrative-driven map. It reveals the exact sequence an attacker would follow from initial discovery to crown-jewel impact, weaponizing data like Web3 brand permutations and NHI exposures.
