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Q-PAM enforces least privilege across admins, contractors, service accounts, and AI workloads with just-in-time access, approval workflows, and session monitoring — all backed by the same post-quantum cryptography as QuantCert.
The numbers that matter to security teams evaluating a PAM solution.
Plaintext credentials shared with contractors or vendors — ever.
Percent audit coverage across human and machine privileged sessions
Most PAM solutions solve yesterday's problem.
CyberArk and BeyondTrust were built for an era where the perimeter was the boundary, humans were the only privileged users, and a 12-month deployment was acceptable. That era is over.
Today's threat surface includes service accounts with standing access, AI agents calling APIs with embedded credentials, contractors with shared passwords, and CI/CD pipelines with hardcoded secrets. Traditional PAM platforms were not designed for any of these.
Q-PAM was.
Every privileged session — human or machine — is authenticated with ML-DSA-44, monitored by the AI Trust Engine, and written to a tamper-evident audit trail. Credentials are never shared in plaintext. Access is never standing. Every grant has an expiry.
Q-PAM covers the full privileged access lifecycle from just-in-time provisioning to session monitoring and automatic revocation.
Contractors, vendors, and CI/CD pipelines get time-limited credentials that auto-expire after 1 hour, 8 hours, 24 hours, or 7 days. No shared passwords. No cleanup tasks. No credential sprawl. Every ephemeral grant is logged with the recipient, purpose, duration, and access type.
When the AI Trust Engine assigns a risk score above 0.6 or detects a policy violation, it queues an approval request instead of blocking outright. Admins review the request in the Q-PAM dashboard and approve or deny with an optional note. Every decision is logged to the audit trail immediately.
Every privileged session produces a timeline of authentication events, vault accesses, and risk scores grouped by user. Flagged users surface automatically. Admins can drill into any session to see domains accessed, Trust Engine flags, and policy violations — and link directly to the full audit log.
When a user is locked out during a confirmed incident, admins can grant temporary vault access that bypasses normal ZK authentication. Every break-glass event requires a mandatory reason entry, has a hard time limit (1 hour to 24 hours), and is logged to the audit trail immediately with the granting admin's identity.
Q-PAM continuously evaluates each user's access level against their actual usage patterns. Over-privileged accounts — users whose access level exceeds their authentication history — are flagged automatically with a recommended action. PQC enrollment status and Trust Engine risk scores are surfaced per user.
Share a vault credential with a time-limited, view-only access token. The recipient never receives the plaintext value — they access it through a time-limited token that expires automatically. Sharing requires a reason. All access is logged. Shares can be revoked instantly.
Standing access is the problem. Just-in-time access is the answer.
Traditional PAM gives privileged users standing access to systems — access that exists 24 hours a day whether or not it is being used. Standing access is the reason credential theft is so damaging. Once an attacker has the credential, they have access until someone notices.
Q-PAM operates on a just-in-time model. Access is granted for a specific purpose, for a specific duration, to a specific user. It expires automatically. There is no standing access to steal.
The flow:
User or system requests access to a privileged resource.
Request is evaluated by the AI Trust Engine. Risk score is assigned.
Low-risk requests are granted immediately with a time-limited token.
High-risk requests queue for admin approval before access is granted.
Access expires at the end of the time window. No manual revocation required.
Every step is written to the audit trail.
Q-PAM is purpose-built for the modern privileged access surface — not retrofitted onto a perimeter-era architecture.
Third-party vendors and contractors get ephemeral credentials scoped to specific vaults for specific time windows. Access is granted, monitored, and automatically revoked — without a shared password ever being transmitted in plaintext.
GitHub Actions, GitLab CI, and other pipeline tools pull secrets at runtime via the QuantCert SDK or CLI. Every pipeline run is authenticated as a machine identity and logged as a privileged session event. No secrets in environment variables. No secrets in repository configuration.
AI agents and LLM-powered workflows that need privileged access authenticate via headless vault API using M2M credentials. Session duration is enforced by DynamoDB TTL. Every agent access is logged with the agent identifier, the vault accessed, and the risk score assigned by the Trust Engine
Database administrator credentials, cloud console access, and infrastructure secrets are stored in Q-PAM vaults with automated rotation schedules. Access is always time-limited. Admins see who accessed which system, when, and from where — in one unified audit trail.
Q-PAM vs. traditional PAM platforms.
CyberArk and BeyondTrust are the market leaders in privileged access management. They are powerful, proven, and expensive — in licensing, implementation, and ongoing maintenance.
Q-PAM is not trying to replace CyberArk for the Fortune 500 enterprise with a dedicated PAM team and an 18-month runway. Q-PAM is built for the organization that needs enterprise-grade privileged access control now, without a seven-figure implementation budget.
Where Q-PAM differs:
Deployment: CyberArk requires dedicated infrastructure and a professional services engagement measured in months. Q-PAM deploys on AWS in hours.
Machine identity: Traditional PAM platforms were designed for human privileged users. Q-PAM treats service accounts, CI/CD pipelines, and AI agents as first-class identities with the same cryptographic protections as human users.
Post-quantum: Neither CyberArk nor BeyondTrust offer ML-KEM or ML-DSA protection. Q-PAM uses both by default.
AI risk scoring: Q-PAM evaluates every authentication with an AI risk model. Traditional PAM platforms rely on rules-based detection that cannot adapt to novel attack patterns.
For enterprises already running CyberArk: Q-PAM complements your existing infrastructure — particularly for machine identity, AI agent access, and post-quantum credential protection.
