Security Agents

AI-powered agents for vulnerability remediation and deployment failure analysis; Zero Day Remediation for CVE-based fixes across repos, and Manifest Remediator for Kubernetes and Helm deployment failu

Harness Security agents help teams identify and remediate vulnerabilities and deployment failures using AI. The Zero Day Remediation agent scans for and fixes critical CVEs across multiple repositories, while the Manifest Remediator analyzes Kubernetes and Helm deployment failures to generate remediation YAML.

Zero Day Remediation Agent

The Zero Day Remediation agent identifies and remediates critical vulnerabilities (0-day) across multiple repositories. It scans codebases and vulnerability databases, validates package safety, and generates fix PRs to downgrade or upgrade to safe versions.

Capabilities

• Scans across multiple repositories (controlled by maxRepos parameter)

• CVE-based or component-based remediation

• Validates package rollout states, targeting rules, and activity patterns

• Supports Java, JavaScript, TypeScript, Python, Go, and C#

• Creates fix PRs with version updates to safe releases

• Requires Harness Supply Chain Security module

Key inputs

Input	Type	Description
anthropicKey	secret	Anthropic API key for Claude AI
harnessKey	secret	Harness API key for platform operations
repoAccessToken	secret	Token for repository access across orgs
cveId	string	CVE identifier to remediate (e.g., CVE-2024-1234)
componentName	string	Package/component name (alternative to cveId)
fixedVersion	string	Target safe version to upgrade/downgrade to
currentVersion	string	Current vulnerable version
harnessOrgId	string	Harness organization identifier
harnessProjectId	string	Harness project identifier
targetBranch	string	Branch to target for PRs (default: main)
maxRepos	string	Maximum number of repositories to scan
branchPrefix	string	Prefix for fix branches (default: fix/)
authorName	string	Git author name for commits (default: AI Workflow)
authorEmail	string	Git author email for commits (default: [e-mail])
search	string	Filter repositories by name pattern

Pipeline configuration

pipeline:
  stages:
    - name: zero_day_remediation
      steps:
        - name: remediate_vulnerabilities
          run:
            container:
              image: harness/vulnerability-remediation-plugin:latest
            with:
              cve_id: <+inputs.cveId>
              component_name: <+inputs.componentName>
              fixed_version: <+inputs.fixedVersion>
              current_version: <+inputs.currentVersion>
              harness_org_id: <+inputs.harnessOrgId>
              harness_project_id: <+inputs.harnessProjectId>
              target_branch: <+inputs.targetBranch>
              branch_prefix: <+inputs.branchPrefix>
              author_name: <+inputs.authorName>
              author_email: <+inputs.authorEmail>
              max_repos: <+inputs.maxRepos>
              search: <+inputs.search>
              working_directory: /harness
              detailed_logging: "true"
            env:
              ANTHROPIC_API_KEY: <+inputs.anthropicKey>
              HARNESS_API_KEY: <+inputs.harnessKey>
              REPO_ACCESS_TOKEN: <+inputs.repoAccessToken>
      platform:
        os: linux
        arch: amd64
  inputs:
    anthropicKey:
      type: secret
      description: Anthropic API key for Claude LLM analysis
    harnessKey:
      type: secret
      description: Harness PAT token for API operations
    repoAccessToken:
      type: secret
      description: Git access token for repository operations
    cveId:
      type: string
      description: CVE identifier to remediate (e.g., CVE-2021-44228)
    componentName:
      type: string
      description: Vulnerable component name to upgrade
    fixedVersion:
      type: string
      description: Target version to upgrade to
    currentVersion:
      type: string
      description: Current vulnerable version
    harnessOrgId:
      type: string
      required: true
      description: Harness organization ID
    harnessProjectId:
      type: string
      required: true
      description: Harness project ID
    targetBranch:
      type: string
      default: main
      description: Target branch for pull requests
    branchPrefix:
      type: string
      default: "fix/"
      description: Prefix for fix branches
    authorName:
      type: string
      default: "AI Workflow"
      description: Git author name for commits
    authorEmail:
      type: string
      default: "[e-mail]"
      description: Git author email for commits
    maxRepos:
      type: string
      default: "0"
      description: Maximum repositories to process (0 for unlimited)
    search:
      type: string
      description: Filter repositories by name pattern

Supported languages

Language	Package Manager	File
Java	Maven / Gradle	pom.xml / build.gradle
JavaScript	npm / yarn	package.json
TypeScript	npm / yarn	package.json
Python	pip / poetry	requirements.txt / pyproject.toml
Go	go modules	go.mod
C#	NuGet	*.csproj

SUPPLY CHAIN SECURITY REQUIRED

The Zero Day Remediation agent requires the Harness Supply Chain Security module. Ensure this module is enabled in your Harness account before configuring this agent.

Manifest Remediator Agent

The Manifest Remediator agent analyzes Kubernetes and Helm deployment failures by examining execution logs from failed pipelines. It uses AI to identify root causes and generates a manifest_remediation_results.yaml file with specific fixes and step-by-step remediation instructions.

How it works

1. Fetch Logs: Retrieves execution logs from the failed K8sRollingDeploy or HelmDeploy steps via the Harness API.

2. AI Analysis: Claude AI analyzes the logs to identify the root cause of the deployment failure.

3. Generate Remediation: Produces a structured YAML file with root cause analysis, recommended fixes, and configuration updates.

Unique characteristics

• Does not clone a repository; works purely from pipeline execution logs

• Outputs a YAML file with structured remediation guidance

• Supports K8sRollingDeploy and HelmDeploy failure types

• Uses Harness API to fetch pipeline execution details

Key inputs

Input	Type	Description
anthropicKey	secret	Anthropic API key for Claude AI
harnessKey	secret	Harness API key for fetching execution logs
harnessExecutionId	string	Failed pipeline execution ID
harnessPipelineId	string	Pipeline identifier
harnessBaseUrl	string	Harness API base URL
harnessProjectId	string	Harness project identifier
harnessOrgId	string	Harness organization identifier
harnessAccountId	string	Harness account identifier

Pipeline configuration

pipeline:
  stages:
    - name: manifest_remediation
      steps:
        - name: PrintEnv
          run:
            shell: bash
            script: |
              echo "Harness Execution ID: <+inputs.harnessExecutionId>"
              echo "Harness Pipeline ID: <+inputs.harnessPipelineId>"
              echo "Harness Base URL: <+inputs.harnessBaseUrl>"
              echo "Harness Project ID: <+inputs.harnessProjectId>"
              echo "Harness Org ID: <+inputs.harnessOrgId>"
              echo "Harness Account ID: <+inputs.harnessAccountId>"
              printenv
        - name: Manifest Remediator
          run:
            container:
              image: rajpatel2/manifest-remediator:manifest-remediator
            with:
              detailed_logging: "true"
              harness_api_key: <+inputs.harnessKey>
              working_directory: /harness
              harness_execution_id: <+inputs.harnessExecutionId>
              harness_pipeline_id: <+inputs.harnessPipelineId>
              harness_base_url: <+inputs.harnessBaseUrl>
              harness_project_id: <+inputs.harnessProjectId>
              harness_org_id: <+inputs.harnessOrgId>
              harness_account_id: <+inputs.harnessAccountId>
            env:
              ANTHROPIC_API_KEY: <+inputs.anthropicKey>
        - name: Output
          run:
            script: |-
              echo "=== Manifest Remediation Results ==="
              cat /harness/manifest_remediation_results.yaml
            shell: bash
      platform:
        os: linux
        arch: arm64
  inputs:
    anthropicKey:
      type: secret
      default: autofix_anthropic_api_key
    harnessKey:
      type: secret
      default: harness_api_key
    harnessExecutionId:
      type: string
    harnessPipelineId:
      type: string
    harnessBaseUrl:
      type: string
    harnessProjectId:
      type: string
    harnessOrgId:
      type: string
    harnessAccountId:
      type: string

Example output

root_cause:
  type: ImagePullBackOff
  description: "Container image 'myapp:v2.1.0' not found in registry"
  affected_resource: deployment/myapp
  namespace: production
recommended_fixes:
  - action: "Update image tag to existing version"
    manifest: deployment.yaml
    path: spec.template.spec.containers[0].image
    current_value: "myapp:v2.1.0"
    suggested_value: "myapp:v2.0.9"
    confidence: high
  - action: "Add imagePullSecret for private registry"
    manifest: deployment.yaml
    path: spec.template.spec.imagePullSecrets
    suggested_value:
      - name: registry-credentials
    confidence: medium
remediation_steps:
  - "Verify image 'myapp:v2.1.0' exists in the container registry"
  - "Check registry authentication credentials"
  - "Update deployment manifest with correct image tag"
  - "Re-run the deployment pipeline"

POST-INCIDENT ANALYSIS

The Manifest Remediator is ideal for post-incident analysis. Trigger it automatically when K8s or Helm deployments fail to get immediate, actionable remediation guidance without manual log diving.