Stop your agents
from going rogue
Prismor gives enterprises a security control plane for AI agents. Full traceability of every tool call with security guardrails in production
Opus 5
~/prismor-web
Dashboard/Overview
cursor4
claude-code4cursor6
langchain-api2cursor2Dashboard/Policies
Alice Chenclaude-codeMacBook Pro
Sam OrtizcursorMacBook Air
Maya IyercursorCI runner
Dan Brooks
codexLinux desktop
Priya Nair
windsurfMacBook Pro
Tom Nakamura
copilotMacBook Pro
Lena Fischerlangchain-apiGPU node
Omar Haddadclaude-codeMacBook AirDashboard/Audit logAn immune layer for every agent action
Your agents run hundreds of tool calls a session. Prismor catches each one before it executes, blocks the destructive ones, and strips secrets out before they reach the model. Every call lands in an audit trail you can read back later. Works with the OpenAI Agents SDK, MCP agents like Claude Code and Cursor, LangChain, and CrewAI
Every tool call intercepted, masked, and loggedSecurity rules your whole team can version
Write your security rules once and apply them from the CLI. Set defaults for the org, override them per team, grant exemptions per person. You pull, lint, and apply the same way you ship infra config, and every change sits in git for review
Policies versioned, linted, and applied like infraEvery agent action, on the record
Your agents run in the background. You see the output. Prismor captures what happened before it: every tool call at interception, what Prismor blocked, what it masked, who triggered the session. The full timeline is live in your dashboard while the agent is still running. Your security team can pull an export any time
Full session timeline, tool by toolSecure by default Prismor plugs into existing workflows, enabling enterprises to get policy enforcement and a full audit trail on every agent action
One security layer for every agent your team uses
Connect Prismor once and keep the same runtime policy, secret protection, and audit trail across coding agents, SDKs, and custom MCP workflows.
A closed loop that gets safer with every decision
Export agent activity to your observability stack, involve a human when policy needs context, then turn approvals, denials, and incident outcomes into better policy recommendations.
Send traces, policy outcomes, and audit events into the tools your security team already monitors.
Datadog
OpenTelemetry
New Relic
Splunk
GrafanaNotify the right owner, request approval, or route an exception without stopping the entire workflow.
SlackPrismor uses guided decisions and recurring patterns to recommend tighter rules, reviewed before they are applied.
What developers are saying
Love the MCP gateway angle. One policy layer across everything is the right abstraction
bro this is actually clean, i've had claude code almost run rm -rf on my server once. policy checks would've saved me
the observe mode is the part i'd want tested: how often does it flag legitimate shell commands, and who maintains those policies when the repo changes?
Honestly, AI trading bots need this more than humans
gm, open source control plane that gates every tool call sounds like the missing guardrail. how heavy is the latency?
enforce mode saves wallets tbh
the enforce vs observe switch is smart! teams can see the blast radius before
This is a real gap. The agent part gets all the attention, but visibility and control are what make it usable in production
nice take on agent iam, the guardrail scoping feels solid. how do you handle secret rotation across delegated sub agents?
Local first security for agents is a strong direction. Secret redaction is table stakes, but policy enforcement around tool calls and package installs is where this gets really interesting
this is genuinely needed. most agent stacks rn are a black box once you deploy them, and the "we'll add observability later" crowd finds out the hard way when something exfiltrates a token
Open source is the way to go! Superb demo and great product
super cool product!
so cool!
Tried it for 3 of my repositories. Super awesome man!
This is awesomeee
This is spot on. Most devs know security matters, it just never feels urgent enough. Auto PRs feel like the right approach.
I think this is a very solid approach
too good
interesting tool, does it run across all commit history, or just latest commit?
Just checked out @prismor_dev, This is actually sick. Prismor scans your GitHub repo, finds security issues, and just… opens a PR. Kudos to the team, love the idea for solving a real pain point without overcomplicating it. 🚀
Hats off for providing us with this!!
security is key especially as models become increasingly capable!
I was seeing openclaw and its cousins everywhere didn't know they had so many vulnerabilities. As prismor is free I'll try it and maybe post my feelings.
Oh thanks, I will check for those issues🫡🫶
As enterprises are adapting agents into their workforce, security becomes very crucial part of the workflow. Looking forward for great work
@prismor_dev is a standout. It's a "Security and Compliance Autopilot" that helps you ship faster with fewer bugs. You just connect it to your GitHub and let it work
@prismor_dev built a tool to help team catch security issues in your code by scanning your repo directly. You should check it out. It could really help you save time and a lot of money.
From agent chaos to auditable control
Connect
Wrap your agent framework with Prismor in one step. MCP, the OpenAI Agents SDK, LangChain, CrewAI. Your existing agents keep working.
Intercept
Every tool call routes through Prismor before it executes. The agent has no path around it.
Enforce
Your active policy decides each call: allow, block, or mask. Secrets never reach the model. Destructive commands never run.
Audit
Read the full timeline of every agent action in the dashboard: arguments, outcome, user, session. Export it when compliance asks.
Improve
Update policies from the CLI as your conventions change. Every rule is versioned and reviewed by a teammate, same as infra config.