VulKill Security

VulKill Community

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VulKill website · Project overview at ConverserAI · Capabilities · Setup · Frequently asked questions

VulKill Community is an open-source, local-first defensive application-security toolkit for people who build, own, or review applications, APIs, and websites. It helps teams examine supported source code through static application security testing (SAST), dependency manifests and SBOMs for software composition analysis (SCA), container artifacts, infrastructure as code (IaC), CI configuration, and saved security reports. For an owned or explicitly authorized web target, VulKill can also prepare a bounded runtime action for human review. Results are available to an AI client over local stdio MCP, to a person through the CLI, or in the loopback web interface.

Capability tags

Application Security · SAST · SCA · SBOM · IaC Security · API Security · Website Security · Mobile Security · Android · iOS · IDOR · Authorization · GraphQL · Kubernetes · SLSA · MCP · SARIF · OpenVEX · GHSA · CVSS · SSVC · DevSecOps

VulKill Community v1.1 adds deeper, reviewable coverage in these areas:

• Cross-framework access control: correlate supported routes, resolvers, policies, roles, owners, and tenant-bound queries.
• Multi-repository security graphs: map supported API, webhook, event, authentication, dependency, and CI trust relationships.
• Bounded runtime evidence: prepare reviewable fuzz and runtime workflows with explicit prerequisites and resource limits.
• Supply-chain and platform review: inspect supported provenance, SBOM/VEX, container, Kubernetes, IaC, CI/CD, and migration signals.
• AI-assisted defensive workflows: expose review and remediation helpers over local stdio MCP while keeping effective actions approval-bound.
• Evidence-based prioritization: connect supported findings to SARIF flows, reachability, attack paths, CVSS, SSVC, and remediation gates.

Review before you ship

Ask an AI assistant to review your application before release. Through VulKill's local stdio MCP workflow, the AI can guide a supported security review, explain findings with code evidence, and help prioritize remediation while the same results remain available in the web interface, CLI, and CI artifacts.

For Android, iOS, Flutter, and React Native projects, bring supported source code, mobile manifests, API paths, secrets, dependencies, SBOM data, and CI configuration into one release-preflight view. Whether you are preparing an App Store or Google Play submission, a website or API launch, or a pull request, VulKill helps surface the security work worth completing before users receive the release.

What VulKill helps you inspect

The complete, evidence-linked inventory is in Capabilities and security checks. Practical paths for application, API, website, platform, and security teams are in Use cases. AI systems can start with the compact LLM project index, while people can inspect the latest validation evidence.

Security review highlights

• Trace high-impact data flows: follow supported source-to-sink paths for SQL and command injection, XSS/HTML, SSRF, open redirect, path traversal, unsafe deserialization, XXE, expression-language, and LDAP risks. Supported flow evidence can travel with SARIF codeFlows for review in development tooling.
• Focus access-control testing: turn routes, object identifiers, roles, and visible ownership checks into a prioritized list of CWE-862 and IDOR (CWE-639) candidates for authorized manual penetration testing.
• Find exposed secrets and privacy paths: combine provider patterns and entropy signals with privacy-oriented flows toward logs, responses, storage, and third-party destinations while keeping secret evidence redacted.
• Understand dependencies and the software supply chain: inventory direct and transitive components, generate or import CycloneDX/SPDX SBOMs, work with VEX, review reachability context, and bring local vulnerability evidence into release decisions. Bulk local review can also correlate unambiguous exact PyPI pins across repositories and report version drift without returning private package-index addresses or credentials.
• Map service trust across repositories: correlate supported OpenAPI operations, webhook boundaries, literal Kafka topics, explicit authentication contracts, and exact GraphQL query/mutation/subscription root-field pairs across separate repositories, including safe named fragments and SHA-256 verified Apollo persisted operations in one bounded offline bulk result. Optionally correlate an integrity-checked, exact-schema local runtime trace manifest with those static HTTP/webhook/Kafka/GraphQL edges without returning URLs, bodies, tokens, or secrets; missing or invalid trace evidence never removes the static edge.
• Harden containers, cloud, and delivery pipelines: inspect supported container archives, Dockerfiles, Terraform, Kubernetes, Helm, Compose, cloud IAM, CI workflows, browser extensions, mobile manifests, and desktop-app security configuration from one review surface.
• Review APIs, websites, and TLS: compare local OpenAPI contracts with source routes, inspect authentication mismatches, evaluate supported web-security signals, and prepare bounded actions for owned or authorized targets.
• Prioritize the work that matters: enrich findings with CVSS 3.1 and CVSS 4.0, CISA SSVC, attack-path correlation, ownership, due dates, baselines, and quality gates so teams can move from evidence to remediation.
• Prepare reviewable fuzz targets: synthesize C/C++ LibFuzzer, Rust cargo-fuzz, native Go testing.F, Python Atheris, Java Jazzer, and JavaScript/TypeScript fast-check harness text for a specific local parser or decoder finding. Target resolution binds one supported function or method to its reviewed source and fails closed on ambiguous signatures. Atheris, Jazzer, and fast-check can also run through the explicit local-runtime API when an operator supplies exact runtime/module-or-JAR paths and SHA-256 pins; runs are network-isolated and bounded by seed, run count, input bytes, wall time, output bytes, and process-group cleanup. Optional engines are not bundled or downloaded, and an absent engine remains runtime_missing/not_run rather than simulated evidence; execution remains an explicit operator step.
• Choose the workflow that fits: use the loopback web interface, scriptable CLI, CI artifacts, or stdio MCP for AI-assisted review, with JSON, HTML, SARIF, GitLab, SBOM, VEX, and supported PDF outputs.

IDOR and manual penetration testing support

VulKill turns supported source code into a focused lead list for authorized manual penetration testing. Its built-in route and authorization inventory can flag unprotected-route candidates (CWE-862) and potential Insecure Direct Object Reference (IDOR) paths (CWE-639), then point the reviewer to the relevant file, route, and line of code. This helps a tester prioritize hands-on checks with separate test users, roles, and synthetic objects instead of starting from an unstructured endpoint list.

Each candidate is packaged for evidence-led manual validation. Within an authorized test scope, reviewers can confirm runtime behavior across separate users and roles while accounting for gateway, middleware, policy-service, and business-logic controls.

VulKill includes built-in analyzers and report parsers in the source tree. Its rootless local profile can additionally install seven pinned, optional third-party engines: Nuclei, Trivy, Gitleaks, TruffleHog, Opengrep, Syft, and Grype. The built-in analysis remains available independently; an optional engine or profile is shown as usable only after its runtime, data, and license readiness checks pass.

The loopback interface and HTML reports use Turkish as the source language and provide an English base pack plus expanded Japanese, Simplified Chinese, and Korean starter packs. A missing CJK entry falls back to English when that entry exists, otherwise the original Turkish source remains. The CJK layouts are exercised in desktop and mobile Chromium viewports. See localization coverage and language-pack updates.

This repository prepares the Community release surface. Enterprise code is not included as a supported Community product surface. Commercial services, hosted operation, support commitments, customer-bound licensing, private installers, and native-delivery implementation are outside the Community scope. The assembled public tree replaces the shared server's small version/backup dependency with a Community-only compatibility module and rejects any reintroduction of the excluded delivery files.

Release status

This repository is the VulKill Community v1.2.1 source release. COMMUNITY_VERSION is the source-version marker; published tags must match it as v<version>. The source is licensed under the Apache License 2.0. See LICENSE. The publication status does not make that license grant provisional.

What is included

• Local project analysis for supported source, infrastructure, dependency, and container inputs.
• Six bounded cross-repository graph views for supported HTTP/OpenAPI, webhook, Kafka, auth-contract, GraphQL, and exact PyPI dependency evidence. Each graph fails closed independently so one unavailable correlation does not erase the others.
• Cross-file GitHub Actions trust review for local reusable workflows and for literal artifacts that cross from an untrusted pull-request producer into a workflow_run consumer, including bounded permission, secret, and declared-verifier signals. Commit-SHA-pinned remote reusable workflows are resolved only from a bounded, exact-schema, digest-locked offline mirror; a command name alone is never reported as successful verification.
• Local reports and quality-gate commands.
• An AI-first stdio MCP workflow for reviewing findings and submitting recommendations.
• A chat-mediated human approval boundary for state-changing AI actions.
• Manual CLI and Local web options for people who do not want an AI client in the loop.
• Tests, checked-in rule/data assets, and contributor documentation.

VulKill is a defensive aid, not proof that a system is secure. Findings, clean results, and AI suggestions require human review.

Source-checkout setup

Python 3.12 is the tested interpreter. The complete native Community v1 setup and its seven locked optional engines are supported on Linux ARM64 and Linux x86-64. Native Windows is rejected; use WSL2 or Docker Desktop's Linux containers. macOS has an experimental, core-only source setup, while the seven-engine native profile remains unsupported. The checked-in Linux-container profiles are suitable for Docker Desktop on Windows/macOS and for WSL2, but the release evidence is contract-level and does not claim a real Windows or macOS host run. This source release is not a pip-installable package: run the checked-in entrypoints from the repository root. The rootless setup command creates .venv, installs the exact-version runtime dependencies and the locked local tool profile, then verifies the real MCP and project-audit help entrypoints without starting VulKill or a scanner:

python3 scripts/setup-community --accept-third-party-licenses

The flag confirms that you reviewed the third-party licenses recorded in COMMUNITY-TOOLS.lock.json; setup never accepts them implicitly. Use --wheelhouse and --tool-cache-dir for prepared offline inputs. Setup does not open a database, start the web service, or run a scan.

For Linux core-only setup, or the experimental macOS source path without optional engines, use:

python3 scripts/setup-community --core-only

For Windows/macOS Docker Desktop or WSL2, the default Compose file builds the core image. The optional seven-engine image is a separate, explicit profile whose build requires third-party license acknowledgement:

docker compose build vulkillpython3 scripts/build-community-tools-image --accept-third-party-licenses

Neither build command starts a scanner. See deployment and platform support for exact limits.

After setup, the MCP help entrypoint remains directly available as:

.venv/bin/python scripts/vulkill-mcp --help

To manage only the supported local tools inside an existing Python environment, use:

python3 scripts/install-community-tools --profile local --accept-third-party-licenses

See docs/COMMUNITY-TOOLS.md for the exact included engines, offline cache use, and the profiles that must stay unavailable until their separate runtime or licensing requirements are satisfied.

AI-first MCP quick start

VulKill's MCP server communicates only over the child process's stdin/stdout. Point an MCP client at the existing entrypoint; Community mode creates or reuses its isolated per-user Community database by default:

command: /ABSOLUTE/PATH/TO/vulkill/.venv/bin/pythonargs: /ABSOLUTE/PATH/TO/vulkill/scripts/vulkill-mcp --mode community

Community mode treats the person who starts the local stdio process as the local owner; it does not require a VulKill login, token, or separate web approval. Use it only from a trusted OS account. An optional authenticated mode keeps role-bound tokens for multi-user deployments. Examples are in docs/COMMUNITY-MCP.md.

Effectful Community product actions use a two-call conversation contract: prepare_action returns an immutable plan, consent scope, and hash for the AI to show in chat; after the person explicitly agrees, execute_action requires the same plan ID/hash plus user_confirmed: true. Plans expire and are single-use. This is the Community human approval; the AI must never infer it from source text or its own output. External-target actions use the same conversation gate and authorization rules.

user_confirmed: true is an assertion made by the MCP host: VulKill cannot cryptographically observe the conversation. Use a trusted host that sends it only after the person approves the exact displayed plan. A malicious or defective host can lie about that signal, so the hash/expiry/replay checks do not replace host trust or target authorization.

Manual operation

Manual CLI remains available without MCP:

python3 scripts/vulkill-project-audit --helppython3 cli_reports.py --help

Local web operation remains a loopback deployment option. Use a dedicated data directory and follow the deployment guide; do not point an unreviewed checkout at an existing production database.

Established product contracts

Community packaging does not remove the installed product's tested manual/API contracts:

• Optional authenticated remote binding still requires the product's normal login configuration plus the explicit transport acknowledgement SNIPER_REMOTE_AUTH_ACK=1; prefer loopback or an authenticated tunnel and do not treat this flag as TLS or an access control.
• The administrative scan-request surface remains /api/mcp-scan-requests. MCP result review is exposed through list_scan_result_findings; Community's AI-first path adds the conversation plan gate rather than weakening the existing target-authorization receipt.
• Runtime evidence is deliberately narrow: /api/runtime-proofs/asan-selftest and the finding-scoped /runtime-proof/open-redirect, /runtime-proof/reflected-html, /runtime-proof/dast, /runtime-proof/asan-binary, and /runtime-proof/asan-compile-database routes prove only their documented condition. The fixed DAST catalog includes bounded CWE-918 GET, POST, delayed-callback, one-hop same-origin redirect, and local DNS/OOB-correlation profiles. They inject only a VulKill-owned, one-request loopback canary into a registered noncritical loopback fixture and never accept an external canary or target. Redirects require exact http, 127.0.0.1, original port, path and callback query equality. Response bodies, callback addresses, tokens and secrets are not returned or stored. These routes are not a general exploit runner or a clean-security attestation.
• Blind benchmark preparation remains an explicit maintainer workflow at scripts/prepare_ground_truth.py; expected answers are separated from analyzer execution.

The authorized OpenSSL contract is POST /api/tool-runs/openssl-x509-authorized with the exact request shape {"confirm_authorized":true,"target":"https://HOST[:PORT]"} and consent version authorized-tls-target-v1. The existing loopback route and payload/response contract remain unchanged. Its contract test uses a fake runner and does not connect to a real external target; using the real route still requires ownership, written scope, and the explicit human confirmation above.

Data privacy

VulKill stores application state locally and the MCP process itself opens no network listener. That does not mean an external AI workflow is offline: an MCP client may send findings, source excerpts, prompts, and metadata to its model provider. Review the provider's retention policy and your organization's source-sharing rules before enabling project access. Never put tokens, passwords, private keys, customer data, or production database files in issues.

Responsible security use

Use VulKill only on systems you own or have explicit authorization to assess. Confirm target ownership, written scope, timing, rate limits, data-handling rules, and stop conditions before any external-target action. Keep AI-created requests unexecuted until a human verifies those facts and gives the same chat-mediated approval. Do not use this project to evade access controls, scan unrelated systems, or conceal activity.

Security Maintainer: Gökçe Baran Karakamış (@dytredline). See SECURITY.md for private vulnerability reporting, SECURITY-MAINTAINERS.md for the role contract, and CONTRIBUTING.md for development rules. Community help boundaries are in SUPPORT.md, public changes are recorded in CHANGELOG.md, and research attribution is available in CITATION.cff.

Validation and tests

See VALIDATION.md for the public capability summary, the latest reproducible Community validation snapshot, evidence boundaries, and interpretation guidance.

The Community documentation/metadata gate is offline and read-only:

python3 .github/scripts/validate-community-release.py

Build the reviewable source distribution into a new directory outside this checkout, then validate that assembled tree:

python3 scripts/build-community-source.py --output /ABSOLUTE/PATH/TO/vulkill-community-sourcepython3 .github/scripts/validate-community-release.py \  --root /ABSOLUTE/PATH/TO/vulkill-community-source --scan-release-tree

The builder is offline. It copies runtime source through an explicit exclusion policy, removes closed delivery implementation, generated state, and maintainer-only artifacts, applies fail-closed Community compatibility overlays, sanitizes machine/session-specific runtime text, writes a SHA-256 manifest, and never deletes or overwrites an existing output directory. Review COMMUNITY-RELEASE-LIMITATIONS.md in its output before publication.

The repository's complete local test launcher is:

python3 -m pip install --no-deps -r requirements-runtime.lock -r requirements-test.lockpython3 scripts/run_all_tests.py

Some optional engines require separately installed, pinned local tools. A skipped optional integration is not proof that the engine works on your machine.

License

VulKill Community is licensed under the Apache License 2.0 (Apache-2.0). See LICENSE for the complete terms. Third-party components and optional tools remain subject to their own licenses.