Discover without exfiltration
Local and CI scanners send masked findings and fingerprints, never plaintext keys or raw repository content.
Built for secure AI teams in Bengaluru, India
Competitors govern the session.RaksHex governsthe action.
Runtime authorization for autonomous AI agents. Semantic actions, delegated authority with parent-to-child attenuation, a hash-chained tamper-evident Action Ledger, and credential mediation so a DENY is enforced, not just logged.
$ financial.refund({ amount: 40, orderId })
1,000+ tests passing26 migrations, rollback-verifiedHash-chained Action Ledger
Works perfectly withOpenAI
bash — agent firewall
Recent Action Ledger
data.exportALLOW
infra.deployALLOW
financial.refundDENY
Live Decision
Agent identified
finance-support-prod
Authority checked
parent scope ≤ $50
Decision reached
DENY — exceeds limit
Ledger recorded
hash-chained entry
EVALUATING…
OpenAI
Claude
GitHub
VS Code
Postman
Slack
Express
FastAPI
Django
Gemini
Mistral
OpenAI
Claude
GitHub
VS Code
Postman
Slack
Express
FastAPI
Django
Gemini
Mistral
Coverage vs Enforcement
Visibility Isn't Control. Enforcement Is.
Where RaksHex sits relative to logging, alerting, and session-scoped approaches teams already run today.
Blast Radius (Narrow vs Broad) Decision Granularity →
Coarse & ManualManual Review
Human-in-the-loop approval queues
Periodic access reviews
RaksHex
Fine-Grained & Automated
Agent Firewall
Each semantic action is authorized against attenuated authority in real time — no queue, no broad session grant.
Narrow blast radiusEnforced, not advisory
Coarse & BroadStatic API Keys
One key, every action it can technically reach
Rotation is the only real control lever
No per-action authorization
Fine-Grained but BroadLogging / Observability
Detailed traces of what happened, after the fact
Alerting, not blocking
Architecture Comparison
Session-Level vs Action-Level Control
Drag the handle to compare governing who has a session against governing what each individual action is actually allowed to do.
RaksHex Agent FirewallAction-Level
Enforcement Active
Semantic action authorizationEnforced at the credential
Delegated AuthorityActive
Parent-to-child attenuation — a child authority can never exceed its parent's scope.
Enforced
Credential MediationBroker
A DENY blocks the credential itself — the secret never reaches a denied caller.
Fail-closed
Action LedgerHash-chained
Every decision is recorded tamper-evidently for audit and dispute resolution.
Tamper-evident
:::
Why Teams Move Past Session-Level Auth To RaksHex
A valid API key or session token proves who is calling — not whether this specific action, right now, should be allowed.
Govern the action, not the session
Every semantic action is evaluated against the caller's actual delegated authority, not just whether the session is valid.
A DENY that actually denies
Enforcement happens at the credential broker, so a blocked action can't fall back to a raw API key that still works.
Evidence you can hand to an auditor
The hash-chained Action Ledger gives you a tamper-evident record of every authorization decision, not a log you have to trust.
The credential broker mediates every brokered request. A DENY blocks the secret from ever reaching the caller — enforcement lives at the same layer as the credential, not in a dashboard someone has to watch.
Built-in capabilities
The Agent Firewall core, piece by piece: how an action gets authorized, delegated, enforced, and recorded.
Semantic actions
Policy is written against what an agent is doing, not the HTTP call underneath it.
- Actions like financial.refund, not raw endpoints
- One policy model across providers
- SDK-based integration into your agent's call path
- No proxy re-architecture required to get started
Semantic Action Authorization
Evaluated// Authorize a semantic action
const decision = await firewall.authorize({
action: "financial.refund",
authority: delegatedAuthority,
});
Supported Providers
One Policy Model, Every Provider
The same semantic action and delegated-authority model applies regardless of which LLM provider or coding agent is making the call.
RaksHex Agent Firewall
Action Authorization & Policy Engine
OpenAI
LLM ProviderAzure OpenAI
LLM ProviderAWS Bedrock
LLM ProviderGoogle Vertex / Gemini
LLM ProviderGitHub Copilot
Coding AgentCursor
Coding AgentOpenAI-Compatible
Self-Hosted / CustomHead-to-Head Comparison Matrix
How RaksHex Compares 1-on-1
Select a competitor below to see detailed side-by-side feature capabilities, security coverage, and operational differences.
Category: Static Code & Dependency Scanner
Full Snyk ReportRaksHex vs Snyk
Snyk scans repos and dependencies for known CVEs before code ships. It doesn't evaluate what an already-running AI agent is authorized to do at call time.
Capability
RaksHex Control Plane
Snyk
Primary Security Focus
Runtime action authorization for AI agents
Static code vulnerabilities (SAST/SCA)
Semantic Action Authorization
Evaluates each action against delegated authority
No runtime action model
Credential Mediation
Broker enforces DENY at the credential
No credential brokering
Tamper-Evident Action Ledger
Hash-chained record of every decision
No runtime decision ledger
MCP Tool Governance
Adversarial-intent scanning on tool calls
Scans hardcoded secrets in source
Agent Firewall
Semantic action authorization evaluated against delegated authority, in real time.
Learn more →Credential Broker
Fail-closed mediation. A DENY blocks the credential, not just the log line.
Learn more →Delegated Authority
Parent-to-child attenuation — a child scope can never exceed its parent's.
Learn more →Action Ledger
Hash-chained, tamper-evident record of every authorization decision.
Learn more →Shadow API Discovery
Static route extraction across Express, FastAPI, Flask, Django, and Spring.
Learn more →Credential Scanner
Finds exposed AWS, GitHub, OpenAI, and Stripe keys in scanned repositories.
Learn more →Audit Evidence
Exportable JSON/CSV/PDF evidence packs built from the Action Ledger.
Learn more →MCP Governance
Adversarial-intent scanning and tool allowlisting for MCP-connected agents.
Learn more →One system of record
Security, FinOps, and developer access should agree on what AI is running.
Point tools solve isolated pieces. RaksHex connects discovery, ownership, policy, and evidence so the same answer holds up in an engineering review, a finance review, and an audit.
Govern API and subscription access
Track credentials separately from provider accounts, cloud resources, plans, seats, owners, and renewal evidence.
Enforce at runtime
Evaluate provider and model rules, budgets, tool policies, PII redaction, injection signals, and kill switches before execution.
Changelog
See what's new in RaksHex
July 2026
View all changesPublished customer legal, privacy, and security documentation
May 2026Interactive demo scanner with Postman parsing
May 2026Waitlist system with email confirmation
April 2026Credential broker kill-switch controls added
Adoption without theater
Evaluate RaksHex with evidence you can inspect.
We do not publish invented customer logos, quotations, or comparative scores. Pilot teams receive a scoped rollout plan, permission map, test cases, and an exportable audit trail for their own environment.
Frequently Asked Questions
Questions? We've got answers. If you don't find what you need, feel free to read our docs.
or check out our DocumentationRaksHex is an Agent Firewall: runtime authorization for autonomous AI actions. It evaluates semantic actions against delegated authority, mediates the credentials those actions need, and writes every decision to a hash-chained Action Ledger — so a DENY is enforced, not just logged.
OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Google Vertex/Gemini, GitHub Copilot, Claude Teams, Cursor, self-hosted models, and OpenAI-compatible endpoints.
Enforcement happens at the credential broker. A DENY blocks the secret itself, so a denied action can't fall back to a raw API key that still works elsewhere.
Any team building with AI agents, LLMs, or AI-powered APIs who needs security visibility, cost control, and compliance evidence.
Platform Statistics
Metrics will appear here once the platform has usage data.