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This comprehensive explanation has been generated from 78 GitHub source documents. All source documents are searchable here.
Last updated: October 7, 2025
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Zero-trust computing is a security architecture based on the principle "never trust, always verify," requiring continuous cryptographic verification of all entities, data, and communications without relying on network location, prior authentication, or trusted intermediaries.
Zero-trust computing represents a fundamental paradigm shift in cybersecurity architecture, moving from perimeter-based "castle-and-moat" security models to a comprehensive verification-centric approach. The core principle is deceptively simple: assume all networks are hostile, both internally and externally, and verify every interaction cryptographically.
This concept emerged from the recognition that traditional security models—which establish trust based on network location (inside vs. outside the firewall)—are fundamentally inadequate in modern distributed computing environments. Once an attacker breaches the perimeter through phishing, zero-day exploits, or compromised credentials, the entire "soft underbelly" of internal systems becomes vulnerable.
Zero-trust computing establishes several key properties:
Universal Verification: Every network interaction, data flow, and system access must be authenticated and authorized using cryptographic best practices, regardless of source location or previous authentication status.
End-to-End Security: All inter-host communication must be cryptographically signed and encrypted, with data protected both in motion (during transmission) and at rest (during storage).
Continuous Authentication: Trust is never assumed or cached—verification occurs for every transaction, creating what Samuel Smith calls "verify every-time for every-thing."
Behavioral Authorization: Authentication and authorization policies adapt dynamically based on observed behavior and reputation rather than relying solely on static credentials.
Diffuse Trust: The architecture explicitly rejects single points of trust, instead distributing trust across multiple parties through end-verified distributed consensus mechanisms.
Locked-Down Hosts: Systems executing security-critical logic must be comprehensively secured, including key management operations, cryptographic functions, and protection against common vulnerabilities.
The zero-trust concept emerged from multiple converging developments in cybersecurity:
Implementing zero-trust computing with KERI requires adherence to seven core principles:
1. Network Hostility Assumption: Design all systems assuming networks are hostile both internally and externally. Implement mitigations for man-in-the-middle attacks, DNS hijacking, and BGP attacks at the protocol level rather than relying on network security.
2. End-to-End Security: All inter-host communication must be cryptographically signed and encrypted. Data must be protected both in motion and at rest. Use KERI's signing capabilities for authenticity and implement confidentiality overlays using ECIES/HPKE or similar schemes.
3. End-to-End Provenance: Every data transformation must be tracked using verifiable data structures. Use ACDCs to create verifiable chains of custody for data flows, ensuring every change is cryptographically attributable.
4. Universal Verification: Implement "verify every-time for every-thing" by checking cryptographic signatures on every message and validating key state against KELs for every interaction. Never cache trust decisions.
5. Behavioral Authorization: Implement dynamic authorization policies that adapt based on observed behavior and reputation. Use KERI's interaction events to track behavior and adjust trust levels accordingly.
6. Diffuse Trust: Avoid single points of trust by using witness pools with appropriate thresholds. Implement watcher networks to enable independent verification of key state. Use KAACE (KERI's Agreement Algorithm for Control Establishment) for distributed consensus.
7. Host Lockdown: Protect key management operations using TEEs (Trusted Execution Environments), TPMs (Trusted Platform Modules), or HSMs (Hardware Security Modules). Implement comprehensive security testing for all changes across hardware/software platform combinations.
Zero-trust computing places significant emphasis on key management:
Key Generation: Use cryptographically strong random number generators (CSPRNGs) with at least 128 bits of entropy. Generate keys in secure environments (HSMs, secure enclaves) when possible.
Key Storage: Store private keys encrypted at rest. Use hardware-backed keystores on mobile devices. Implement key splitting or threshold schemes for high-value keys.
Key Rotation: Leverage KERI's pre-rotation mechanism to enable secure key rotation. Commit to next rotation keys in advance through cryptographic digests, enabling recovery from compromise without breaking the trust chain.
Perimeter Security Failures: Traditional firewall-based security proved inadequate as organizations adopted cloud computing, mobile devices, and remote work. The "network perimeter" became increasingly porous and difficult to define.
Advanced Persistent Threats: Sophisticated attackers demonstrated the ability to breach perimeters and maintain long-term access to internal networks, exploiting the implicit trust granted to internal systems.
Regulatory Pressure: Standards bodies like NIST and CISA began recommending zero-trust approaches, particularly following high-profile breaches that exposed the limitations of perimeter-based security.
Cryptographic Maturity: Advances in public-key cryptography, particularly the development of efficient signature schemes like Ed25519 and encryption protocols like ECIES/HPKE, made universal cryptographic verification practical.
The term "zero trust" itself is somewhat misleading—as Samuel Smith notes, there's no such thing as actual zero trust. The more accurate term is "diffuse trust", representing a perimeter-less security model where trust is distributed across multiple independent verification points rather than concentrated in perimeter defenses.
Traditional implementations of zero-trust principles include:
Google's BeyondCorp: One of the earliest large-scale zero-trust implementations, eliminating VPN requirements by verifying every access request regardless of network location.
Software-Defined Perimeters (SDP): Creating dynamic, identity-based network perimeters rather than static network boundaries.
Microsegmentation: Dividing networks into small, isolated segments with strict access controls between segments.
However, these implementations often still rely on centralized identity providers, certificate authorities, or other trusted infrastructure—limitations that KERI's approach addresses.
KERI implements zero-trust computing principles at a fundamental level through its cryptographic infrastructure, providing what Samuel Smith calls "end-verified diffuse trust perimeter-less security" or "autonomic trust basis."
Cryptographic Root-of-Trust: KERI's Autonomic Identifiers (AIDs) establish trust through self-certifying cryptographic identifiers rather than administrative authorities. The identifier itself is derived from the controller's public key, creating an unbreakable cryptographic binding that requires no external trust.
Key Event Logs as Verifiable History: Every change to an identifier's key state is recorded in an append-only, cryptographically chained Key Event Log (KEL). This creates an immutable audit trail that any party can verify independently, eliminating reliance on trusted infrastructure for key state verification.
Pre-Rotation for Key Compromise Recovery: KERI's pre-rotation mechanism commits to future rotation keys through cryptographic digests, enabling recovery from key compromise without breaking the chain of trust. This provides post-quantum security and eliminates the traditional PKI vulnerability where key rotation breaks the trust chain.
Duplicity Detection: KERI's architecture makes duplicitous behavior (publishing conflicting versions of key event logs) cryptographically evident. Witnesses and watchers maintain independent copies of KELs, enabling ambient duplicity detection—any party can detect if a controller attempts to present different key histories to different verifiers.
End-to-End Verifiability: KERI implements ambient verifiability—the principle that any data, anywhere, at any time can be verified by anybody. This eliminates the need to trust intervening infrastructure, as verification depends only on cryptographic proofs embedded in the data itself.
Witness Pools for Distributed Consensus: Rather than relying on centralized authorities, KERI uses witness pools to provide distributed consensus on key events. Controllers designate their own witnesses, and verifiers can independently confirm that sufficient witnesses have signed key events, implementing diffuse trust without shared governance.
OOBI for Trust-Minimized Discovery: Out-Of-Band Introductions (OOBI) enable discovery of service endpoints without requiring trust in the discovery mechanism itself. The OOBI provides only an initial introduction—all subsequent verification uses KERI's cryptographic protocols.
BADA Policy for Asynchronous Security: The Best Available Data Acceptance (BADA) mechanism provides replay attack protection in non-interactive scenarios, enabling zero-trust authentication without requiring synchronous challenge-response protocols.
Separation of Concerns: KERI separates the authenticity overlay (proving who said what) from the confidentiality overlay (protecting content) and privacy overlay (managing identifier correlation). This modular approach allows each security property to be optimized independently while maintaining zero-trust principles across all layers.
The key difference from traditional zero-trust implementations is that KERI provides cryptographic verification independent of infrastructure. Traditional zero-trust still relies on certificate authorities, identity providers, or blockchain consensus—all of which represent potential points of compromise. KERI's autonomic trust basis eliminates these dependencies through self-certifying identifiers and end-verifiable data structures.
Healthcare Data Exchange: The RACK (Routing, Authentication and Confidentiality with KERI) project demonstrates zero-trust principles in healthcare integration engines. Rather than relying on VPNs and perimeter security, RACK implements "Sign Everything" and "Keys at the Edge" paradigms, where every message is cryptographically signed and verified regardless of network location.
Supply Chain Security: Zero-trust computing enables verifiable supply chain provenance through Authentic Chained Data Containers (ACDCs). Each transformation in the supply chain is cryptographically signed and chained, creating an end-to-end verifiable audit trail without requiring trust in intermediary systems.
Organizational Identity: The vLEI (verifiable Legal Entity Identifier) system implements zero-trust principles for organizational identity. Legal entities receive cryptographically verifiable credentials that can be independently verified without contacting issuing authorities, eliminating reliance on centralized verification services.
IoT and Edge Computing: Zero-trust computing is particularly valuable in IoT environments where devices may operate in hostile networks. KERI's lightweight cryptographic verification enables resource-constrained devices to participate in zero-trust architectures without requiring constant connectivity to central authorities.
Benefits:
Trade-offs:
Complexity: Implementing comprehensive cryptographic verification requires sophisticated key management and careful protocol design. However, KERI's architecture significantly reduces this complexity compared to traditional PKI.
Key Management Burden: Users must manage cryptographic keys, though modern secure enclaves, TPMs, and HSMs make this increasingly practical. KERI's pre-rotation mechanism provides robust key compromise recovery.
Performance Overhead: Cryptographic operations add computational cost, though modern hardware acceleration and efficient algorithms like Ed25519 minimize this impact.
Cultural Shift: Organizations must move from "trust but verify" to "never trust, always verify," requiring changes in operational procedures and mindset.
Initial Bootstrap: Zero-trust systems still require some initial trust establishment, though KERI's OOBI mechanism minimizes this to simple out-of-band introductions that can be verified cryptographically.
The fundamental insight of zero-trust computing, as implemented in KERI, is that it's much easier to protect one's private keys than to protect everyone else's internet infrastructure. By establishing cryptographic roots-of-trust at the edges and verifying everything end-to-end, zero-trust architectures achieve security properties that perimeter-based approaches cannot provide.
Key Compromise Recovery: Implement monitoring for duplicity detection. Maintain watcher networks to detect if compromised keys are used to create conflicting key event logs. Use pre-rotated keys for recovery.
Implement systematic verification workflows:
1. Identifier Verification: When receiving a message signed by an AID, retrieve the KEL for that identifier. Verify the KEL's internal consistency (hash chains, signatures). Check for duplicity by comparing against watcher-maintained copies.
2. Key State Validation: Determine the current key state by processing all establishment events in the KEL. Verify that the signing key used matches the current authoritative key set. Check that thresholds are met for multi-sig identifiers.
3. Signature Verification: Verify the cryptographic signature on the message using the current public key(s). Ensure the signature scheme matches the derivation code in the identifier.
4. Freshness Validation: Check timestamps or sequence numbers to prevent replay attacks. Implement BADA policies appropriate for your use case (monotonic sequence numbers, timestamps, or nullification).
5. Authorization Checking: Verify that the signing identifier has appropriate authorization for the requested operation. Check delegation chains if the identifier is delegated.
Zero-trust computing can be implemented efficiently:
Caching Strategies: While trust decisions should not be cached, KELs and key state can be cached with appropriate invalidation strategies. Implement watcher-based cache invalidation to detect key state changes.
Batch Verification: When processing multiple messages from the same identifier, verify the KEL once and reuse the key state for all messages (within appropriate time windows).
Witness Selection: Choose witnesses with good network connectivity and reliability to minimize verification latency. Use geographically distributed witnesses to improve availability.
Cryptographic Acceleration: Leverage hardware acceleration for Ed25519 signature verification. Modern CPUs can verify thousands of signatures per second.
Zero-trust architectures require clear governance:
Witness Policies: Define policies for witness selection, rotation, and threshold requirements. Document the security assumptions underlying witness configurations.
Watcher Networks: Establish watcher networks appropriate for your security requirements. Public watchers provide ambient duplicity detection; private watchers provide targeted monitoring.
Key Rotation Schedules: Define policies for routine key rotation vs. emergency rotation. Establish procedures for detecting and responding to key compromise.
Delegation Policies: If using delegated identifiers, clearly define delegation authority and constraints. Implement appropriate monitoring of delegated identifiers.
Incident Response: Establish procedures for responding to detected duplicity, key compromise, or other security incidents. Define escalation paths and recovery procedures.