Remediation Labs combines application lifecycle context, AI agents, attack-path reasoning, active response, remediation, and verification into one platform.
Automate security and operations work while continuously identifying and disrupting agentic attacks, chained vulnerabilities, unknown attack paths, and active incidents across code, software delivery, cloud, and production.
Actors
Application lifecycle
Signals entering the platform
Remediation Labs intelligence & control layer
Modern security systems generate enormous amounts of evidence — individually, these signals may appear unrelated.
Fragmented evidence
Remediation Labs asks
Platform flow
Security decisions require application context.
Traditional security tools understand findings. Remediation Labs understands the application, its lifecycle, its state, and the changes occurring around it.
Code & Supply Chain
Delivery & Infrastructure
Identity & Runtime
Application Lifecycle Context Engine
Continuously updated contextual model
A continuously updated model — not a static asset inventory.
Question
“What exists and how is it connected?”
Understand applications, code, artifacts, deployments, infrastructure, identities, permissions, dependencies, and network relationships.
Capabilities
Question
“What changed and what did the change enable?”
Track changes over time across code, deployments, infrastructure, permissions, and runtime state.
Capabilities
Question
“Was the action appropriate for this actor and task?”
An action can be technically authorized and still be dangerous. Understand human vs AI-agent actor, assigned task, expected behavior, application scope, policy, current system state, and resulting capability.
Capabilities
Use application context and specialized AI agents to automate high-volume security, compliance, delivery, and operations work.
Capability 01
Capability 02
Cross-tool correlation across the lifecycle. The platform consolidates fragmented evidence into a single, actionable risk.
Example
SAST
Vulnerable code
DAST
Exploitable endpoint
SCA
Vulnerable dependency
Deployment
Running in production
Runtime
Externally reachable
One contextualized, exploitable application risk with a defined remediation path.
Capability 03
Automate
Capability 04
Determine
Use cases
Capability 05
Generate or coordinate
Then verify
The attack may not exist until the attacker starts creating it.
Traditional security looks for known vulnerabilities or known attack signatures.
Modern attackers — and increasingly autonomous agents — can construct attacks dynamically by combining:
No individual step needs to appear critical.
The danger emerges from the chain.
The most dangerous attack may not be a single CVE.
It may be the chain.
Example attack path
Platform assesses
Why this matters
Traditional tools score individual nodes.
Remediation Labs assesses the capability created by the path.
Each in isolation
Critical Attack Path
Individually acceptable. Collectively dangerous.
Core principle
Risk lives in the path,
not only in the node.
AI agents increasingly interact with:
An agent may be authorized to perform each individual action.
But the sequence of actions may create dangerous system state.
The platform asks
The critical distinction
Not enough
Permitted Action
Technically authorized
What we require
Appropriate Action
Right for the actor, task, and state
Potential
A theoretical path exists.
Feasible
Current system state makes the path possible.
Progressing
Observed activity is moving through the path.
Active
The path is being exercised.
Contained
A defensive action interrupts the path.
Verified
The dangerous capability has been removed.
Instead of treating every event equally, Remediation Labs identifies material changes that can alter important attack paths. These become watchpoints.
Example events
When a watchpoint triggers
Every material change becomes a security decision.
Continue monitoring when confidence or risk is low.
Present the safest remediation or containment option.
Escalate higher-impact actions to a human.
Reduce privileges or agent capabilities.
Interrupt an active path.
Remove the underlying vulnerability or condition.
Reverse an unsafe deployment or change.
Response authority is based on:
Traditional incident response requires humans to manually assemble evidence across many tools. Remediation Labs reconstructs it automatically.
Reconstructs
Then coordinate
The goal is not simply closing an incident.
The goal is restoring a known safe state.
Inputs
Reconstruct
Identify
Determine response using
Response
Confirm
The verified outcome
Continuous
Protect human-written and AI-generated code and the agents creating it.
Capabilities
Protect the systems that build and deploy software.
Capabilities
Protect the deployed application and its operating environment.
Capabilities
Understand and resolve security and operational failures.
Capabilities
Not every response should be autonomous. Remediation Labs supports progressive levels of response authority.
Authority depends on:
Autonomous where safe.
Human-governed where necessary.
Verified always.
LAYER 1
Actors
LAYER 2
Application Lifecycle
LAYER 3
Active Defense & Automation
LAYER 4
Intelligence
LAYER 5
Data & Control Systems
Reason about applications and deployed occurrences, not isolated assets.
Understand how code became a running system.
Understand what changed and what capability the change created.
Evaluate risk across paths instead of isolated findings.
Determine whether an authorized action is appropriate.
Select the correct intervention point.
Contain and remediate dangerous progression.
Prove that the resulting state is safer.
Automate security and operations work today.
Detect and disrupt agentic, chained, and emerging attacks as they develop.
Restore and verify the safe state of applications across code, cloud, and production.
Or email us at info@remediationlabs.com
