{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"aikido-security","slug":"aikido-security","name":"Aikido Security","type":"product","url":"https://www.aikido.dev","page_url":"https://unfragile.ai/aikido-security","categories":["code-review-security"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"aikido-security__cap_0","uri":"capability://code.generation.editing.static.application.security.testing.sast.with.multi.language.ast.parsing","name":"static-application-security-testing-sast-with-multi-language-ast-parsing","description":"Performs static code analysis across multiple programming languages by parsing source code into abstract syntax trees (AST) and pattern-matching against vulnerability signatures. The system scans repositories without executing code, identifying injection flaws, hardcoded secrets, unsafe API usage, and logic errors. Results are returned within 30 seconds for typical codebases by leveraging incremental scanning and caching of previously analyzed files.","intents":["I need to find security vulnerabilities in my source code before deployment","I want to catch injection flaws, XSS, and authentication bypasses in my codebase","I need to scan code in CI/CD pipelines automatically on every commit"],"best_for":["development teams using Git-based workflows","organizations requiring continuous security scanning in CI/CD","teams building web applications and APIs with multiple language codebases"],"limitations":["Supported programming languages not explicitly documented — scope unknown","AST-based analysis may miss vulnerabilities in dynamically-generated code or eval() patterns","Scan time scales with codebase size; performance on monorepos >1M LOC not documented","Cannot detect vulnerabilities that only manifest at runtime or under specific execution paths"],"requires":["Git repository access (GitHub, GitLab, Bitbucket, or self-hosted)","Source code must be committed to repository (does not scan uncommitted local changes)","Aikido account with SAST scanning enabled"],"input_types":["source code files in repository","repository metadata (commit history, branch information)"],"output_types":["vulnerability findings with file path, line number, and severity","code snippets showing vulnerable patterns","remediation suggestions"],"categories":["code-generation-editing","security-scanning","static-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_1","uri":"capability://data.processing.analysis.software.composition.analysis.with.sbom.generation.and.cve.matching","name":"software-composition-analysis-with-sbom-generation-and-cve-matching","description":"Scans open-source dependencies declared in package managers (npm, pip, Maven, Go modules, etc.) and matches them against a continuously-updated CVE database to identify known vulnerabilities. Generates Software Bill of Materials (SBOM) in standard formats, tracks dependency versions, and identifies outdated packages. The system performs transitive dependency analysis to detect vulnerabilities in indirect dependencies that may not be explicitly declared.","intents":["I need to know which open-source libraries in my project have known security vulnerabilities","I want to generate an SBOM for compliance and supply-chain security audits","I need to identify and update outdated dependencies before they become critical security risks"],"best_for":["teams managing projects with 50+ dependencies","organizations requiring SBOM generation for compliance (SLSA, NIST, etc.)","development teams in regulated industries (healthcare, finance, government)"],"limitations":["Dependency scanning limited to declared package managers — custom or vendored dependencies may not be detected","CVE database lag: newly-disclosed vulnerabilities may take hours to appear in scanning results","Transitive dependency analysis may miss vulnerabilities in dependencies loaded dynamically or at runtime","License scanning scope not documented — unclear which license types are flagged or how conflicts are resolved"],"requires":["Package manifest files (package.json, requirements.txt, pom.xml, go.mod, etc.) committed to repository","Aikido account with SCA scanning enabled","Internet connectivity for CVE database queries"],"input_types":["package manager manifests (npm, pip, Maven, Gradle, Go, Rust, etc.)","lock files (package-lock.json, Pipfile.lock, pom.xml, etc.)","container image manifests"],"output_types":["list of vulnerable dependencies with CVE IDs and severity scores","SBOM in CycloneDX or SPDX format","dependency tree showing transitive relationships","remediation guidance (upgrade recommendations, patch availability)"],"categories":["data-processing-analysis","security-scanning","supply-chain-security"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_10","uri":"capability://safety.moderation.runtime.application.firewall.zen.with.injection.attack.blocking","name":"runtime-application-firewall-zen-with-injection-attack-blocking","description":"Deploys an in-application firewall (Zen) that monitors and blocks injection attacks (SQL injection, command injection, etc.) and enforces rate limiting at runtime. The firewall instruments the application to intercept dangerous operations (database queries, system commands, etc.), validates inputs against attack patterns, and blocks or logs suspicious requests. This provides runtime protection for vulnerabilities that may not be caught by static or dynamic testing.","intents":["I need runtime protection against injection attacks for vulnerabilities that slip through testing","I want to enforce rate limiting to prevent brute-force attacks and API abuse","I need to detect and block attack attempts in production without modifying application code"],"best_for":["organizations running applications with known or suspected injection vulnerabilities","teams that need runtime protection while remediating code-level vulnerabilities","applications exposed to high-volume attacks or brute-force attempts"],"limitations":["Zen integration method not documented — unclear if it requires code instrumentation, middleware, or reverse proxy","Performance overhead of runtime monitoring not documented — may add latency to requests","Attack pattern detection may produce false positives (blocking legitimate requests) or false negatives (missing sophisticated attacks)","Rate limiting configuration scope not documented — unclear if limits are per-IP, per-user, per-endpoint, etc.","Cannot protect against attacks that don't involve injection or rate-limiting (e.g., logic flaws, privilege escalation)"],"requires":["Running application instance","Aikido Zen agent installation (method and language support not documented)","Aikido account with runtime protection enabled"],"input_types":["application runtime environment","request/response traffic","application configuration"],"output_types":["blocked request logs with attack details","rate-limiting alerts and enforcement logs","attack pattern analysis and trends","recommendations for remediation"],"categories":["safety-moderation","automation-workflow","runtime-security"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_11","uri":"capability://safety.moderation.bot.protection.and.api.abuse.prevention.with.behavioral.analysis","name":"bot-protection-and-api-abuse-prevention-with-behavioral-analysis","description":"Detects and blocks bot traffic and API abuse by analyzing request patterns, behavioral signatures, and anomalies. The system identifies automated attacks (credential stuffing, account enumeration, scraping, DDoS) by recognizing patterns like identical requests from different IPs, rapid-fire requests from single sources, and requests that deviate from normal user behavior. Blocking can be enforced through rate limiting, CAPTCHA challenges, or request rejection.","intents":["I need to prevent credential stuffing and account enumeration attacks against my login endpoints","I want to block API scraping and abuse while allowing legitimate API clients","I need to detect and mitigate DDoS attacks and bot traffic in real-time"],"best_for":["applications with public APIs or login endpoints exposed to the internet","organizations experiencing high volumes of bot traffic or API abuse","teams that need to protect against credential stuffing and account takeover attacks"],"limitations":["Behavioral analysis accuracy depends on baseline traffic patterns — new applications may have high false positive rates","Cannot distinguish between legitimate automated clients (e.g., monitoring tools) and malicious bots without configuration","Blocking mechanisms (rate limiting, CAPTCHA) may degrade user experience for legitimate users","Bot detection evasion techniques not documented — unclear how sophisticated bots are handled","Integration with application or API gateway not documented — unclear how blocking is enforced"],"requires":["Running application or API instance","Aikido bot protection agent installed or API gateway integration configured","Aikido account with bot protection enabled"],"input_types":["request traffic (HTTP headers, body, IP, timing)","user behavior baselines","application configuration"],"output_types":["bot detection alerts with confidence scores","blocked request logs with bot classification","behavioral analysis reports showing attack patterns","recommendations for blocking rules or rate limits"],"categories":["safety-moderation","automation-workflow","api-security"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_12","uri":"capability://automation.workflow.ci.cd.pipeline.integration.with.automated.scanning.and.gating","name":"ci-cd-pipeline-integration-with-automated-scanning-and-gating","description":"Integrates Aikido scanning into CI/CD pipelines to automatically scan code, dependencies, and infrastructure on every commit or pull request. The integration includes policy enforcement gates that block merges if findings exceed configured thresholds, automated remediation through pull request creation, and detailed scan reports in CI/CD logs. Supports GitHub Actions, GitLab CI, Jenkins, and other CI/CD platforms through webhooks and API integrations.","intents":["I want to automatically scan every pull request for security vulnerabilities before merge","I need to enforce security policies in CI/CD that block merges if vulnerabilities are found","I want to automatically create pull requests with security fixes from Aikido scans"],"best_for":["development teams using GitHub, GitLab, Bitbucket, or Jenkins for CI/CD","organizations implementing shift-left security practices","teams that want to enforce security gates in their deployment pipelines"],"limitations":["CI/CD platform support limited to major platforms — unclear if all platforms are equally supported","Policy enforcement scope not documented — unclear what thresholds and rules can be configured","Scan latency in CI/CD pipelines not documented — may slow down build times","Integration setup complexity not documented — unclear if configuration is simple or requires extensive setup","Cannot block merges for vulnerabilities that require manual review (e.g., architectural security issues)"],"requires":["CI/CD platform (GitHub Actions, GitLab CI, Jenkins, etc.)","Repository with CI/CD pipeline configured","Aikido account with CI/CD integration enabled","API token or webhook configuration for Aikido"],"input_types":["pull request or commit information","source code changes","CI/CD pipeline configuration"],"output_types":["scan results in CI/CD logs","pass/fail status for merge gates","pull requests with security fixes","detailed scan reports linked from CI/CD"],"categories":["automation-workflow","tool-use-integration","security-scanning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_13","uri":"capability://code.generation.editing.ide.plugin.and.developer.experience.integration.with.real.time.feedback","name":"ide-plugin-and-developer-experience-integration-with-real-time-feedback","description":"Provides IDE plugins (VS Code, JetBrains IDEs, etc.) that show security vulnerabilities inline as developers write code. The plugin displays vulnerability warnings, provides quick-fix suggestions, and integrates with Aikido's AI triaging to show only relevant findings. Developers can view detailed vulnerability information, see remediation suggestions, and apply fixes directly from the IDE without leaving their development environment.","intents":["I want to see security vulnerabilities in my IDE as I write code, not after scanning","I need quick-fix suggestions for vulnerabilities directly in my editor","I want to understand why a finding is important and how to fix it without leaving my IDE"],"best_for":["development teams using VS Code or JetBrains IDEs","organizations implementing shift-left security with developer-first tools","individual developers who want real-time security feedback while coding"],"limitations":["IDE plugin support limited to VS Code and JetBrains — other IDEs (Vim, Emacs, etc.) not supported","Real-time scanning performance not documented — may add latency or resource overhead to IDE","Plugin functionality scope not documented — unclear which Aikido features are available in IDE vs. dashboard","Offline functionality not documented — unclear if plugin works without internet connectivity","Scope of quick-fix suggestions not documented — unclear which vulnerability types have automated fixes"],"requires":["VS Code or JetBrains IDE (IntelliJ, PyCharm, WebStorm, etc.)","Aikido IDE plugin installed from marketplace","Aikido account with IDE integration enabled","Internet connectivity for real-time scanning"],"input_types":["source code in IDE editor","IDE configuration and project metadata"],"output_types":["inline vulnerability warnings with severity","quick-fix suggestions with code snippets","detailed vulnerability information and remediation guidance","links to Aikido dashboard for full scan results"],"categories":["code-generation-editing","tool-use-integration","developer-experience"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_14","uri":"capability://safety.moderation.malware.detection.and.threat.intelligence.powered.scanning","name":"malware-detection-and-threat-intelligence-powered-scanning","description":"Detects malware and malicious code in source code, dependencies, and binaries using proprietary threat intelligence (Aikido Intel) combined with pattern matching and behavioral analysis. The system identifies known malware signatures, suspicious code patterns (e.g., cryptominers, backdoors, data exfiltration), and dependencies with malicious intent. Findings include threat classification, severity, and remediation guidance.","intents":["I need to detect if any of my dependencies contain malware or malicious code","I want to identify suspicious code patterns that might indicate a compromised dependency","I need to protect against supply chain attacks where dependencies are compromised"],"best_for":["organizations concerned about supply chain security and dependency compromise","teams using open-source dependencies from untrusted sources","enterprises with strict security requirements for third-party code"],"limitations":["Malware detection accuracy depends on threat intelligence database — new or sophisticated malware may not be detected","Threat intelligence source and update frequency not documented — unclear how current the malware signatures are","Cannot detect malware that is obfuscated or uses advanced evasion techniques","Behavioral analysis may produce false positives (e.g., legitimate code that looks suspicious)","Scope of threat intelligence not documented — unclear which malware families and attack vectors are covered"],"requires":["Source code, dependencies, or binaries to scan","Aikido account with malware detection enabled","Internet connectivity for threat intelligence database queries"],"input_types":["source code files","dependency packages","binary files","container images"],"output_types":["malware detection alerts with threat classification","suspicious code pattern analysis","threat intelligence reports with context","remediation guidance (remove dependency, report to maintainer, etc.)"],"categories":["safety-moderation","security-scanning","threat-intelligence"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_15","uri":"capability://data.processing.analysis.license.compliance.scanning.and.open.source.governance","name":"license-compliance-scanning-and-open-source-governance","description":"Scans open-source dependencies to identify license types and detect license compliance violations. The system maintains a database of common open-source licenses (MIT, Apache 2.0, GPL, AGPL, etc.) and flags dependencies with restrictive or incompatible licenses. Provides reports showing license distribution across the codebase and recommendations for replacing incompatible dependencies.","intents":["I need to ensure my project complies with open-source license requirements","I want to avoid GPL-licensed dependencies that would require open-sourcing my code","I need to generate license compliance reports for legal and audit purposes"],"best_for":["organizations with strict open-source license policies","commercial software companies concerned about GPL contamination","teams that need to generate license compliance reports for audits"],"limitations":["License detection accuracy depends on package metadata — some packages may have unclear or missing license information","License compatibility analysis scope not documented — unclear which license combinations are flagged as incompatible","Cannot detect license violations in custom or vendored code (only declared dependencies)","License policy customization scope not documented — unclear if users can define custom license policies"],"requires":["Package manifest files (package.json, requirements.txt, pom.xml, etc.) committed to repository","Aikido account with license scanning enabled"],"input_types":["package manager manifests","lock files","dependency declarations"],"output_types":["list of dependencies with license types","license compliance violations with severity","license distribution report","recommendations for replacing incompatible dependencies"],"categories":["data-processing-analysis","security-scanning","compliance"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_2","uri":"capability://code.generation.editing.infrastructure.as.code.scanning.with.policy.enforcement","name":"infrastructure-as-code-scanning-with-policy-enforcement","description":"Analyzes Infrastructure-as-Code files (Terraform, CloudFormation, Kubernetes manifests) to detect misconfigurations, insecure defaults, and policy violations before infrastructure is deployed. The scanner parses IaC syntax, validates against built-in security policies (e.g., requiring encryption, restricting public access), and identifies deviations from compliance frameworks. Results include specific line numbers and remediation guidance for each misconfiguration.","intents":["I need to prevent insecure cloud infrastructure from being deployed (e.g., public S3 buckets, unencrypted databases)","I want to enforce organizational security policies across all infrastructure code before it reaches production","I need to scan Kubernetes manifests for RBAC misconfigurations and pod security violations"],"best_for":["DevOps and infrastructure teams using Terraform or CloudFormation","organizations deploying to Kubernetes with security compliance requirements","teams implementing Infrastructure-as-Code in CI/CD pipelines"],"limitations":["IaC support limited to Terraform, CloudFormation, and Kubernetes — other IaC tools (Ansible, Pulumi, CDK) not documented as supported","Cannot detect misconfigurations that only manifest after infrastructure is deployed (e.g., runtime permission issues)","Policy customization scope unknown — unclear if users can define custom security policies or only use built-in rules","Multi-cloud policy coverage not documented — unclear if all AWS, Azure, GCP services are covered equally"],"requires":["IaC files (Terraform .tf, CloudFormation .yaml/.json, Kubernetes .yaml) committed to repository","Aikido account with IaC scanning enabled","For Terraform: state files may be required for full context (not documented)"],"input_types":["Terraform configuration files (.tf)","CloudFormation templates (.yaml, .json)","Kubernetes manifests (.yaml)","Terraform state files (optional, for enhanced analysis)"],"output_types":["misconfiguration findings with file path and line number","policy violation details with severity and compliance framework reference","remediation code snippets showing secure configuration","impact assessment (e.g., 'This S3 bucket is publicly readable')"],"categories":["code-generation-editing","security-scanning","infrastructure-security"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_3","uri":"capability://data.processing.analysis.container.image.vulnerability.scanning.with.package.analysis","name":"container-image-vulnerability-scanning-with-package-analysis","description":"Scans OCI-compliant container images (Docker, Podman, etc.) to identify vulnerable packages, outdated base images, and insecure configurations. The scanner extracts the image filesystem, enumerates installed packages, and matches them against CVE databases. It also analyzes image metadata (entrypoint, environment variables, exposed ports) to detect security misconfigurations. Scanning can be triggered on image push to registry or on-demand from the Aikido dashboard.","intents":["I need to prevent container images with known vulnerabilities from being deployed to production","I want to identify outdated base images (e.g., Ubuntu 18.04) that should be rebuilt with newer versions","I need to scan images in my container registry (Docker Hub, ECR, GCR, etc.) for compliance audits"],"best_for":["teams using Kubernetes or container orchestration platforms","organizations with container registries (ECR, GCR, Docker Hub, Artifactory)","DevOps teams implementing container security in CI/CD pipelines"],"limitations":["Scanning limited to OCI-compliant images — non-standard image formats not supported","Cannot detect vulnerabilities in application code within the image (only package-level CVEs)","Base image identification may fail for custom or heavily-modified images","Scanning performance depends on image size; very large images (>5GB) may have extended scan times (not documented)","Registry integration scope not documented — unclear which registries are natively supported vs. requiring manual image uploads"],"requires":["Container image in OCI-compliant format (Docker, Podman, etc.)","Access to container registry (Docker Hub, ECR, GCR, Artifactory, etc.) or ability to push images to Aikido","Aikido account with container scanning enabled"],"input_types":["container image references (image:tag)","container image tarballs","registry credentials for private images"],"output_types":["list of vulnerable packages with CVE IDs and severity","base image analysis with upgrade recommendations","image metadata analysis (exposed ports, environment variables, entrypoint)","SBOM for the container image"],"categories":["data-processing-analysis","security-scanning","container-security"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_4","uri":"capability://safety.moderation.secrets.detection.and.hardcoded.credential.scanning","name":"secrets-detection-and-hardcoded-credential-scanning","description":"Scans source code, configuration files, and commit history to detect hardcoded secrets including API keys, passwords, certificates, encryption keys, and database credentials. Uses pattern matching and entropy analysis to identify potential secrets that may have been accidentally committed. The scanner checks both current code and historical commits to find secrets that were committed but later removed (still present in Git history).","intents":["I need to find accidentally-committed API keys and database passwords before they're exploited","I want to scan my entire Git history to find secrets that were committed months ago","I need to prevent developers from committing secrets in the first place (pre-commit hook integration)"],"best_for":["development teams using Git for version control","organizations with compliance requirements (PCI-DSS, HIPAA, SOC 2) that mandate secret scanning","teams implementing DevSecOps with automated secret detection in CI/CD"],"limitations":["Secret types supported limited to 'API keys, passwords, certificates, encryption keys' — specific patterns/formats not documented","Entropy-based detection may produce false positives (e.g., long random strings in test data)","Cannot detect secrets that are obfuscated or encoded (e.g., base64-encoded credentials)","Git history scanning may be slow for repositories with >10,000 commits (performance not documented)","Scope of secret types unclear — unclear if cloud provider credentials (AWS, GCP, Azure) are specifically detected"],"requires":["Git repository access with full commit history","Aikido account with secrets scanning enabled","For pre-commit integration: Git hooks or IDE plugin installation"],"input_types":["source code files","configuration files (.env, .yaml, .json, etc.)","Git commit history","environment variable definitions"],"output_types":["list of detected secrets with file path, line number, and commit hash","secret type classification (API key, password, certificate, etc.)","remediation guidance (rotate the secret, revoke the key, etc.)","Git history analysis showing when secret was first committed"],"categories":["safety-moderation","security-scanning","credential-management"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_5","uri":"capability://security.scanning.dynamic.application.security.testing.dast.with.automated.web.scanning","name":"dynamic-application-security-testing-dast-with-automated-web-scanning","description":"Performs dynamic security testing of running web applications and APIs by sending crafted HTTP requests to identify runtime vulnerabilities such as injection flaws, broken authentication, insecure deserialization, and API security issues. The DAST scanner crawls the application, builds a model of endpoints and parameters, and tests each with payloads designed to trigger vulnerabilities. Results include proof-of-concept demonstrations of vulnerabilities and specific remediation guidance.","intents":["I need to test my running web application for injection flaws, XSS, and authentication bypasses","I want to scan my REST APIs for security issues like broken authentication and insecure data exposure","I need to validate that my security patches actually fixed the vulnerabilities (regression testing)"],"best_for":["teams with running web applications and APIs in staging or test environments","organizations requiring dynamic testing for compliance (OWASP Top 10, PCI-DSS)","teams implementing continuous security testing in CI/CD pipelines"],"limitations":["DAST requires a running application instance — cannot test applications that are not deployed","Scanning may be slow for applications with many endpoints (>1000) or complex workflows","Cannot test functionality behind authentication without proper credential configuration (scope not documented)","May trigger security alerts or WAF blocks if not properly configured (requires allowlisting Aikido IP ranges)","Cannot detect vulnerabilities that only manifest under specific user roles or data states (limited context awareness)"],"requires":["Running web application or API instance (staging or test environment)","Network access from Aikido scanning infrastructure to the application","Application must accept HTTP requests (no client-side-only applications)","Aikido account with DAST scanning enabled"],"input_types":["application URL (http/https)","authentication credentials (optional, for testing authenticated endpoints)","API documentation or OpenAPI spec (optional, for better endpoint discovery)"],"output_types":["list of vulnerabilities found with proof-of-concept payloads","detailed vulnerability descriptions with OWASP Top 10 mapping","remediation guidance with code examples","scan report with timeline and endpoint coverage"],"categories":["security-scanning","dynamic-testing","api-security"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_6","uri":"capability://planning.reasoning.ai.driven.vulnerability.triaging.and.false.positive.reduction","name":"ai-driven-vulnerability-triaging-and-false-positive-reduction","description":"Uses machine learning models to analyze security findings and filter out false positives by evaluating exploitability context, code reachability, and actual attack surface. The system assigns risk scores based on whether a vulnerability is actually reachable in the application code, whether it requires specific preconditions to exploit, and whether the vulnerable code path is actually used. This AI triaging layer sits between raw scanner output and the developer dashboard, reducing noise by 92% according to testimonials.","intents":["I'm overwhelmed by security findings and need to focus on the ones that actually matter","I want to know which vulnerabilities are actually exploitable in my specific application context","I need to reduce time spent investigating false positives and focus on real security issues"],"best_for":["development teams receiving high volumes of security findings (>100 per scan)","organizations with limited security resources that need to prioritize effectively","teams implementing security scanning in CI/CD but struggling with alert fatigue"],"limitations":["AI triaging accuracy depends on code quality and clarity — obfuscated or dynamically-generated code may be misclassified","Model training data and accuracy metrics not documented — unclear how well the model generalizes to different code patterns","Cannot reduce false positives for vulnerabilities that are theoretically exploitable but practically difficult to trigger","Triaging latency not documented — unclear if this adds significant delay to scan results","No transparency into triaging decisions — users cannot see why a finding was deprioritized"],"requires":["Aikido account with AI triaging enabled (may be default or require upgrade)","Source code must be analyzable (not heavily obfuscated)","Sufficient code context for reachability analysis (function calls, data flow, etc.)"],"input_types":["raw security findings from SAST, DAST, SCA, and other scanners","source code for reachability analysis","application architecture and dependency information"],"output_types":["prioritized list of findings with risk scores","exploitability assessment for each finding","reachability analysis (whether vulnerable code is actually called)","recommended remediation order based on risk and effort"],"categories":["planning-reasoning","safety-moderation","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_7","uri":"capability://code.generation.editing.automated.vulnerability.remediation.with.autofix.code.generation","name":"automated-vulnerability-remediation-with-autofix-code-generation","description":"Automatically generates code patches to fix detected vulnerabilities in source code, dependencies, and infrastructure configurations. The AutoFix system analyzes each vulnerability, determines the minimal code change required to remediate it, and generates a patch that can be automatically applied or reviewed before merging. For dependencies, it recommends and applies version upgrades; for code vulnerabilities, it generates refactored code; for IaC, it generates corrected configurations.","intents":["I want to automatically fix vulnerabilities without manual code review for each one","I need to quickly patch dependencies to the latest secure versions","I want to generate pull requests with security fixes that developers can review and merge"],"best_for":["development teams with high vulnerability volume that need rapid remediation","organizations implementing automated security patching in CI/CD","teams using GitHub, GitLab, or Bitbucket for version control"],"limitations":["AutoFix scope not documented — unclear which vulnerability types can be auto-fixed vs. requiring manual remediation","Generated patches may not be optimal or may introduce breaking changes (e.g., major version upgrades)","Cannot fix vulnerabilities that require architectural changes or significant refactoring","Dependency upgrade recommendations may conflict with other constraints (e.g., compatibility with other libraries)","No rollback mechanism documented — unclear how to revert auto-applied fixes if they cause issues"],"requires":["Git repository with write access (for creating pull requests)","Aikido account with AutoFix enabled (may require paid tier)","CI/CD integration configured to trigger AutoFix on vulnerability detection"],"input_types":["security findings from Aikido scanners","source code and dependency manifests","IaC files"],"output_types":["pull requests with security fixes","code patches showing before/after changes","dependency upgrade recommendations with version numbers","IaC configuration corrections"],"categories":["code-generation-editing","automation-workflow","security-remediation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_8","uri":"capability://data.processing.analysis.cloud.security.posture.management.cspm.with.runtime.configuration.scanning","name":"cloud-security-posture-management-cspm-with-runtime-configuration-scanning","description":"Continuously monitors cloud infrastructure (AWS, Azure, GCP) for security misconfigurations, compliance violations, and deviations from security baselines. The CSPM system connects to cloud provider APIs, enumerates resources, and evaluates them against security policies. It detects issues like overly-permissive IAM policies, unencrypted storage, exposed databases, and missing security controls. Findings are prioritized by risk and include remediation steps.","intents":["I need to continuously monitor my AWS/Azure/GCP infrastructure for security misconfigurations","I want to ensure my cloud resources comply with security standards (CIS Benchmarks, NIST, etc.)","I need to detect and remediate cloud security issues before they're exploited"],"best_for":["organizations with multi-cloud deployments (AWS, Azure, GCP)","teams implementing cloud security compliance programs","DevOps and cloud infrastructure teams responsible for security posture"],"limitations":["Cloud provider support limited to 'major cloud providers' — unclear if all AWS, Azure, GCP services are covered","Requires cloud provider API credentials — security implications of storing credentials not documented","Scanning frequency not documented — unclear if monitoring is real-time or periodic","Cannot detect misconfigurations that only manifest under specific usage patterns or load conditions","Remediation automation scope not documented — unclear which findings can be auto-remediated vs. requiring manual action"],"requires":["AWS, Azure, or GCP account with API access","Cloud provider credentials (IAM role or service account) with read permissions","Aikido account with CSPM enabled (may require paid tier)"],"input_types":["cloud provider API credentials","cloud resource configuration (via API enumeration)"],"output_types":["list of misconfigurations with severity and compliance framework mapping","cloud resource inventory with security assessment","remediation guidance with specific API calls or console steps","compliance report showing coverage against CIS Benchmarks, NIST, etc."],"categories":["data-processing-analysis","security-scanning","cloud-security"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"aikido-security__cap_9","uri":"capability://planning.reasoning.autonomous.ai.pentesting.with.200.plus.agent.orchestration","name":"autonomous-ai-pentesting-with-200-plus-agent-orchestration","description":"Deploys 200+ AI agents that autonomously perform penetration testing against applications and infrastructure by executing attack scenarios, validating exploitability, and generating patches. Each agent specializes in specific attack vectors (injection, authentication bypass, privilege escalation, etc.) and works in parallel to test every deployment. 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