Secure your apps faster and smarter with Jit’s AI Agents

Learn how to collaborate with Jit’s AI Agents to mitigate AppSec risk as fast as it appears.

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Jit’s AI Agents offload tasks that could otherwise take hours or days

Here are examples of what they actually do

Jit AI Agent (SERA)

Triaging vulnerabilities in “Payments” app

Query vulnerability backlog

Determine exploitability of new security issues

Map against internal security policies

New critical finding: Path Traversal

• Internet-facing
• Exploitable
• Violates 3 internal security policies

AppSec Team

Determine next steps

Review and validate risk

Direct action: Create Jira ticket for the relevant development team

Jit AI Agent (COTA)

Close remediation loop

Create Jira ticket for the “Front-end” team

Enrich tickets with context

Create and present code fix for mitigation

Notified the Jitto Operation Agent to monitor remediation progress

Jit AppSec AI Agent

Secure a new code change in GitHub

Initiate scanners: SAST and secrets detection

Security issue detected: SQL injection

Enrich finding with runtime context

Generate remediation code

SQL injection vulnerability detected

Actions:
• Accept remediation code change
• Explain vulnerability
• Accept risk

Developer

Confirm decisions and direct action

Prompt

Jitto AppSec Agent

Vulnerability explanation:

This vulnerable code is being deployed to an internet-facing service that handles sensitive data

Jit AppSec AI Agent

Evaluate application against OWASP ASVS Level 2 standard:

Study OWASP ASVS Level 2

Map OWASP ASVS Level 2 requirements against “Payments” app & internal policies

32 OWASP ASVS violations detection:

• 2 missing controls
• 25 vulnerabilities that violate guidelines
• 5 missing policies

AppSec Team

Confirm decisions and next steps

Next step: Create a report of the compliance findings

Next step: Create Monday.com tickets for the open vulnerabilities

Jitto Compliance Agent

Outcome: Create OWASP ASVS Level 2 report for “Payments” application

Jitto Compliance Agent

Outcome: Create Monday.com tickets and enrich with context

Automated follow-up with tickets until remediation

Jit AppSec AI Agent

Create threat model for “Payments” application

Build application architecture based on GitHub and AWS environments

Evaluate architecture against selected threat modeling framework: STRIDE

Evaluate open vulnerabilities and current controls in place

Threat model summary:
• Application architecture diagram
• Highlight top 10 attack vectors
• Suggest 3 new security controls

AppSec Team

Confirm decisions and next steps

Next step: Create a complete threat model report

Next step: Update this threat model every day, and notify me of significant changes

Jit AppSec AI Agent

Close remediation loop

Map data flow and trust boundaries for the application and third-party dependencies

Classify data assets

Correlate attack vectors with open vulnerabilities

Suggest 3 new security controls to mitigate attack vector risks

“With Jit’s AI Agents we are able to delegate a lot of the tedious work of performing constant risk assessment, and it’s shockingly good at surfacing what needs to be dealt with.”

Dudu Yosef
Director of Security at LinearB

A new way to work: Jit’s AI Agents operate within your stack using MCP

Model Context Protocol (MCP) enables seamless collaboration between AI Agents and your tooling

MCPs provide a standardized way for AI Agents to interact with everyday tools for developers and security teams, enabling users to operate within their existing toolset without leaving the Jit UI.

Automate any AppSec process across your stack without leaving Jit

Rather than bouncing across tools to complete AppSec tasks, simply direct Jit’s AI Agents to execute processes within your existing stack, like reconfiguring a Lambda in AWS or closing a ticket in Jira.

Make data-driven AppSec decisions in seconds

Rather than bouncing across tools to gather information and complete AppSec tasks, simply direct Jits AI Agents to pull data or execute tasks within your existing stack using Model Context Protocol.

See all integrations

All Agentic analysis and actions are rooted in the context of your business

Runtime context: determine the real risk of security issues

Integrate with your Source Code Manager, cloud environment, and existing security stack to determine the risk of all scanner-detected security issues in runtime.

Business context: determine business impact of security issues

Upload internal security policies to help Jit’s AI Agents understand how to operate within the context of your business and risk strategy.

Compliance context: determine compliance impact of security issues

Teams with the highest security scores for their services can be displayed on leaderboards and sent to Slack channels.