Ship with AI.
Don't ship blind.

BlastRadius continuously maps your application, cloud infrastructure, secrets, APIs and AI agents to answer one question: what can go wrong if this changes?

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SECURITY POSTURE
Production
Healthy
Security score
92
+4 this week
Blast radius
3.2
low exposure
Active agents
4
all policy-bound
Needs attention 2 findings
Production API can reach customer data
Unauthenticated path detected
High
Claude Code has excessive permissions
Production database access is not required
Medium

The new security problem

AI made software faster.
It also made the attack surface move.

Vibe coding lets a small team create production systems in days. AI agents can read repositories, execute commands, call APIs, modify infrastructure and deploy code. Traditional security tools were designed around humans writing code, not autonomous systems changing the environment.

AI writes the code

Code can move from prompt to production before anyone has manually reviewed the full system.

Agents get access

Terminals, GitHub, cloud accounts, databases, MCP servers and secrets become part of the agent's operating environment.

Small mistakes scale

One unsafe permission or endpoint can create an attack path into production data and infrastructure.

How it works

From security scanning
to security understanding.

01 1

Connect

Connect GitHub and your infrastructure. BlastRadius discovers the components, identities, secrets, APIs and agents that matter.

02 2

Map

Everything becomes a continuously updated security graph: who can reach what, through which path, with which privilege.

03 3

Simulate

Before risky changes ship, the system evaluates new attack paths and estimates how the blast radius changes.

04

Fix

BlastRadius explains the problem in plain language and can create a remediation PR for safe, deterministic fixes.

The security graph

Don't show vulnerabilities.
Show the path.

A vulnerability matters because of what it can reach. BlastRadius connects code, endpoints, identities, credentials, infrastructure and data into attack paths.

EXAMPLE ATTACK PATH
Internet
↓
POST /api/import
↓
No authentication
↓
Service role credential
↓
Production customer data
LIVE SECURITY GRAPH monitoring
INTERNET
API
SECRET
AGENT
CLOUD
CUSTOMER DATA critical • reachable
attack path possible path

Security-aware CI/CD

Every PR gets a
security impact report.

PULL REQUEST
#482 — Add AI-powered customer import
Security impact: HIGH
BLAST RADIUS CHANGE
Before
3.2
After
7.8
AI SECURITY REVIEW

This PR introduces an unauthenticated endpoint that can write to the production database.

Internet → /api/import
→ service role → production DB

Agent firewall

Your AI gets an identity.
Not the keys to the kingdom.

Give every AI agent explicit permissions and enforce them at runtime. Agents can work autonomously without receiving unnecessary access to production systems.

Claude Code
agent_7f91
● Active
ALLOWED
Read source code
Create PRs
Run tests
Dev database
BLOCKED
Production database
Production secrets
IAM changes
BLOCKED REQUEST
Agent requested production DB credentials.
Reason: outside assigned task scope.

One security layer

Everything connected.

Attack surface mapping

Discover internet-facing endpoints, services, dependencies, identities and sensitive resources.

Attack path analysis

Connect seemingly small issues into the actual path an attacker could use.

PR security impact

See how every code change affects production exposure before deployment.

Agent identity

Give Claude, Codex, Cursor and other agents scoped identities and permissions.

Runtime guardrails

Block dangerous actions when an agent exceeds its assigned policy.

Autonomous remediation

Turn findings into reviewable fixes instead of another endless security backlog.

Security replay

Understand how your security posture changes over time.

Every deployment becomes part of a security timeline. See when exposure increased, what caused it and which change brought the blast radius back down.

SECURITY REPLAY / LAST 24 HOURS
09:14
PR #421 merged — new public API
Blast radius 3.1 → 4.7
10:02
Agent requested production credentials
Request blocked
11:31
Security fix PR created
Authentication + authorization checks
11:42
Fix deployed
Blast radius 4.7 → 2.9

Built for the new software team

For teams that move too fast to have a security department.

FOUNDERS

"I need to know we're safe."

Ship your product without becoming an expert in IAM, CVEs, Kubernetes and cloud security.

CTOs

"Show me the blast radius."

Understand the real business impact of a code, infrastructure or agent change.

DEVELOPERS

"Don't slow me down."

Security should fit inside the existing GitHub workflow, not create another ticket queue.

FAQ

Questions, answered.

No. Vulnerability scanners find individual weaknesses. BlastRadius models relationships between code, APIs, identities, secrets, infrastructure, agents and sensitive data, then evaluates the attack paths created by those relationships. The goal is to understand impact, not simply count findings.

Blast radius describes how much of your system could potentially be affected if a component, identity, agent or endpoint is compromised or behaves incorrectly. A public endpoint that can only read harmless data has a small blast radius. An unauthenticated endpoint with a path to production customer records has a much larger one.

Agents can act rather than merely display information. A coding agent may read files, execute shell commands, modify code, call APIs and interact with cloud infrastructure. That makes identity, least privilege, action policies and runtime enforcement first-class security concerns.

It is designed to sit above and alongside existing tools. SAST, dependency scanners, cloud security tools and runtime controls produce useful signals. BlastRadius connects those signals into a system-level model and prioritizes them according to reachable impact.

The product is designed for safe autonomous remediation. For deterministic fixes, it can prepare a GitHub PR with the proposed changes and regression tests. Higher-risk changes remain reviewable and policy-controlled rather than silently modifying production.

The architecture is intended to span the modern startup stack: GitHub, cloud providers, containers, serverless functions, databases, API gateways, SaaS services, secrets, CI/CD systems and AI agent runtimes. Integrations can expand as the security graph becomes richer.

The intended architecture minimizes unnecessary data movement. Security decisions should be grounded in a structured security graph and deterministic policy engine wherever possible, with AI reasoning used selectively for explanation, correlation and ambiguous cases. Exact data-handling behavior depends on the deployed product architecture and customer configuration.

The initial focus is AI-native startups and small engineering teams that ship quickly with tools such as Claude Code, Codex, Cursor and MCP-enabled workflows, but need security visibility without building a full security organization.

Ship faster.
Know the blast radius.

Security should be part of the agentic development loop—not a review that happens after everything is already in production.