Glossary

Plain-language definitions for the scoring, cybersecurity, and AI/ML terms used across Entropy's scores, profiles, and API. For the full scoring breakdown, see the methodology page.

Entropy scoring & verification

Grade: A letter score (A+ through F) representing how a vendor’s security and AI-safety practices compare against Entropy’s rubric.
Rubric: The versioned scoring definition (category → weight → sub-criteria) every grade is computed against. The current rubric is v2.0.0.
Signal: A single observable, automatically-checked practice — for example, a valid security.txt file — that contributes points toward a category.
Implemented max score: The points currently reachable from live signals, below the rubric’s full 100 while some sub-signals are still unclaimed. Shown next to a grade as "what’s reachable now" — but the grade itself is always computed against the fixed 100-point scale, never against this figure.
Claimed / Unclaimed: Whether a vendor has verified ownership of their domain (via a DNS TXT record) and taken control of their Entropy profile. Unclaimed profiles are still scored from public signals.
Verification bonus: A capped set of bonus points — up to +5 — added after the four scoring categories are summed: 3 for a vendor confirming domain ownership by claiming their profile, 2 for having at least one uploaded evidence document admin-verified. A modifier, not a category — the points lift the final score but not the grade denominator (a fixed 100), so a vendor who has not claimed is never marked down for it, and the total is hard-capped at 100.
Evidence: Supporting documentation — a SOC 2 report, ISO 27001 certificate, model card, and so on — that a claimed vendor uploads to substantiate their profile.
Category benchmark: How a vendor’s score in one category compares to other vendors in the same category, shown alongside the absolute grade.
Potential score: The grade a vendor would reach by closing a specific, currently-scored gap — a missing security.txt field, or the verification bonus for claiming a profile and uploading evidence — shown alongside their current grade when the fix would change it.
Dispute: A claimed vendor’s mechanism to flag a specific finding they believe is incorrect, with a required reason and an optional evidence link.
Watchlist: Companies a signed-in user is tracking. Watchlisted companies trigger an email alert if their grade drops.
security.txt: A machine-readable file at /.well-known/security.txt describing how to responsibly report a vulnerability to an organization.
HSTS (HTTP Strict Transport Security): A header that forces browsers to only connect to a site over HTTPS, even if a user types or clicks a plain http:// link.
SOC 2 (Type I / Type II): An independent auditor’s report on a company’s security controls. Type II covers controls operating effectively over a period of months, not just a single point in time — a stronger signal than Type I. Entropy’s Governance score credits a verified SOC 2 Type II report; Type I is not scored on its own.
ISO 27001: The international standard for information security management systems. Entropy accepts current ISO 27001 certification as evidence toward a vendor’s Governance score.
ISO 42001: A newer international standard specifically for AI management systems — governance of how an organization develops and deploys AI, not general information security. Entropy tracks ISO 42001 disclosure as part of a vendor’s Governance score.
HIPAA: The U.S. Health Insurance Portability and Accountability Act of 1996. Its Privacy and Security Rules set national standards for protecting individuals’ health information, applying to “covered entities” (health plans, most healthcare providers, and healthcare clearinghouses) and the vendors that process health data on their behalf. Narrower applicability than SOC 2/ISO 27001 — relevant mainly to vendors handling health-related data — so Entropy weights it lower. Entropy tracks HIPAA compliance attestation as part of a vendor’s Governance score.
ISO 27701: An international standard for privacy information management — the requirements for a PIMS (Privacy Information Management System) covering how an organization handles personal data as a controller or processor. It grew out of ISO 27001 and shares its management-system structure. Entropy tracks current ISO 27701 certification as part of a vendor’s Governance score.
CSA STAR: The Cloud Security Alliance’s Security, Trust, Assurance and Risk registry — a public listing where a cloud provider either self-assesses (Level 1) or undergoes an independent third-party audit (Level 2) against the Cloud Controls Matrix. A continuous-auditing Level 3 has been discussed by CSA but is still in development and not yet available. Entropy tracks a vendor’s CSA STAR listing, including its level, as part of the Governance score.
GDPR (General Data Protection Regulation): The European Union’s comprehensive data protection law, governing how personal data of people in the EU is collected, processed, and stored. It applies to organizations established in the EU and, under Article 3(2), to organizations elsewhere that offer goods or services to people in the EU or monitor their behavior — so a vendor’s location alone doesn’t put it in or out of scope. Entropy tracks a vendor’s GDPR compliance attestation as part of its Governance score.
EU-US DPF (Data Privacy Framework): A voluntary framework, administered by the U.S. Department of Commerce, letting a U.S. company self-certify that it adheres to the DPF Principles for personal data transferred from the EU, under the European Commission’s adequacy decision for the framework — successor to the Privacy Shield and Safe Harbor frameworks, both invalidated by the Court of Justice of the EU. Entropy tracks DPF self-certification as part of a vendor’s Governance score.
CCPA (California Consumer Privacy Act): California’s state-level consumer privacy law (as amended by the CPRA), giving California residents the right to know what personal information is collected about them, to delete or correct it, to opt out of its sale or sharing, and to limit the use of sensitive personal information. It applies to any business, wherever located, that handles California residents’ data and meets its revenue or data-volume thresholds — the closest U.S. analogue to GDPR. Entropy tracks CCPA compliance attestation as part of a vendor’s Governance score.
FedRAMP (Federal Risk and Authorization Management Program): The U.S. federal government’s program for a standardized security assessment and authorization of the cloud services federal agencies use. Authorizations come at Low, Moderate and High impact levels; High is the level for systems where a compromise could have a severe or catastrophic effect — such as law-enforcement, emergency-services, financial and health data — and is the level Entropy tracks. Authorized services are listed publicly on the FedRAMP Marketplace. It matters mainly to vendors selling cloud services to federal agencies, so Entropy counts it toward a vendor’s Governance score only when an admin has marked it as applicable to that vendor.
GovRAMP (formerly StateRAMP): A nonprofit program that verifies the security of cloud services for U.S. state and local government and education customers, using a risk-based framework modeled on the federal FedRAMP approach. It was known as StateRAMP before being renamed GovRAMP. It matters mainly to vendors selling cloud services to those public-sector buyers, so Entropy counts it toward a vendor’s Governance score only when an admin has marked it as applicable to that vendor.
IRAP (Information Security Registered Assessors Program): An Australian government program, run by the Australian Signals Directorate’s Australian Cyber Security Centre, under which endorsed independent assessors evaluate a cloud service or system against the Australian Government Information Security Manual (ISM) and report the results. It is an assessment by a registered assessor rather than a certificate the government issues. It matters mainly to vendors selling to Australian government agencies, so Entropy counts it toward a vendor’s Governance score only when an admin has marked it as applicable to that vendor.
TISAX (Trusted Information Security Assessment Exchange): The automotive industry’s standardized information-security assessment and exchange mechanism, governed by the ENX Association and used across manufacturers and their suppliers. An assessment produces a TISAX label, valid for three years, that a company shares with its partners through the ENX portal. There is no public lookup, so Entropy records a vendor’s Scope ID and Assessment ID as reference details only and does not validate them. It matters mainly to vendors in the automotive supply chain, so Entropy counts it toward a vendor’s Governance score only when an admin has marked it as applicable to that vendor.
PCI DSS (Payment Card Industry Data Security Standard): The security standard maintained by the PCI Security Standards Council for every entity that stores, processes or transmits payment card data — merchants, processors, issuers and service providers. Compliance is validated by a Qualified Security Assessor’s report or by a self-assessment questionnaire, depending on the entity’s role and transaction volume. A vendor that routes payments through a processor such as Stripe usually does not need to hold it itself, so Entropy counts it toward a vendor’s Governance score only when an admin has marked it as applicable to that vendor.
DORA (Digital Operational Resilience Act): Regulation (EU) 2022/2554, which sets ICT risk-management, incident-reporting, resilience-testing and third-party-risk requirements for EU financial entities — banks, insurers, investment firms, payment providers and similar — and has applied since 17 January 2025. ICT vendors to those firms are drawn in through the contractual requirements the firms must impose, and the most critical ones fall under direct EU oversight. It is a regulation to comply with rather than a certificate someone issues, so Entropy tracks a vendor’s DORA compliance attestation, and counts it toward the Governance score only when an admin has marked it as applicable to that vendor.

Cybersecurity & vendor risk

NIST AI RMF: The U.S. National Institute of Standards and Technology’s AI Risk Management Framework — an increasingly common reference framework security teams cite when defining AI vendor risk requirements.
CVE / NVD: CVE (Common Vulnerabilities and Exposures) identifiers name individual publicly known vulnerabilities. NVD (National Vulnerability Database) is where they’re catalogued along with severity scores.
CVSS: Common Vulnerability Scoring System — the 0–10 severity score attached to a CVE.
Penetration test ("pentest"): An authorized, simulated attack against a system to find exploitable vulnerabilities before an attacker does.
Red team: An internal or external group simulating adversarial attacks against an organization — typically broader and more adversarial in scope than a standard penetration test.
Bug bounty: A program that pays external researchers for responsibly disclosing vulnerabilities they find.
Responsible disclosure: A vendor’s published process for how outside researchers should report a security vulnerability, rather than disclosing it publicly or exploiting it. See security.txt, the standard machine-readable file format for publishing this.
SPF / DKIM / DMARC: Email authentication standards that make it harder to forge a domain’s outgoing mail. Their presence or absence is a common lightweight signal of an organization’s overall security hygiene.
Subprocessor: A third party a vendor uses to process data on its behalf — for example, an AI startup’s subprocessor might be OpenAI or AWS. Subprocessor transparency is central to how Entropy scores AI-specific risk.
DPA (Data Processing Agreement): The contract governing how a vendor handles a customer’s data, often required for GDPR compliance.
TPRM (Third-Party Risk Management): The enterprise security discipline of assessing vendor risk before and during a vendor relationship — the buyer workflow Entropy is built to support.
Zero-day: A vulnerability being actively exploited before a patch exists for it.
Supply chain attack: An attack that compromises a target through a trusted vendor or dependency, rather than attacking the target directly.

AI & ML

Model card: A published document describing a model’s training data, intended use, limitations, and evaluation results. Originated as an AI transparency norm; Entropy treats its presence as a disclosure signal.
Hallucination: A model generating plausible-sounding but false or fabricated output.
Prompt injection: An attack where malicious input manipulates a model into ignoring its instructions or leaking data it shouldn’t.
Jailbreak: A prompt technique designed to bypass a model’s built-in safety guardrails.
Guardrails: The technical and policy measures that constrain a model’s outputs — content filters, system prompts, and refusal training among them.
RAG (Retrieval-Augmented Generation): A system that retrieves external data to ground a model’s response, rather than relying only on what the model learned during training.
Fine-tuning vs. base/foundation model: Fine-tuning adapts an existing large model to a narrower task. Many self-described "AI-native" startups are actually a thin interface layer over an unmodified foundation model — a key signal to check for when evaluating an AI-safety claim.
Training data provenance: Disclosure of what data was used to train or fine-tune a model, and under what rights.
Opt-in vs. opt-out (data training use): Whether a vendor uses customer data or prompts to train its models by default (opt-out — unfavorable) or only with a customer’s explicit permission (opt-in — favorable).
AI red-teaming: Adversarial testing specifically aimed at surfacing a model’s unsafe, biased, or exploitable behaviors — distinct from general security red-teaming.
Alignment: The broader research problem of ensuring a model’s behavior matches its intended human goals and values.
Shadow AI: AI tools adopted by employees or teams without formal security or procurement review — a named, growing concern for security teams.
Data poisoning: An attack that corrupts a model’s training data in order to manipulate its behavior.
Differential privacy: A mathematical technique for limiting what can be learned about any single individual from a training dataset.