avakill
AvaKill is an open-source safety “firewall” for AI agents: it intercepts tool calls, evaluates them against a YAML policy (deny-by-default, rule-based checks including shell/path/content scanning, rate limits, and approval gates), and blocks/kills dangerous operations before execution. It provides multiple enforcement paths: native agent hooks, an MCP proxy/wrapper, and OS-level sandboxing, with an optional daemon for shared evaluation and audit logging.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Strengths (from provided docs/manifest): deterministic, deny-by-default rule evaluation; multiple independent enforcement paths (hooks + MCP proxy + OS sandbox) to reduce single-point failure; content scanning for secrets/PII/prompt injection; policy signing/verification and keygen commands are mentioned. Uncertainties: TLS/auth details for any daemon/remote communication are not provided; dependency hygiene and vulnerability status are not verifiable from the provided content; secret handling behavior (e.g., logging redaction) is not explicitly described in the README excerpt.
⚡ Reliability
Best When
You need local, deterministic, policy-based guardrails around agent tool use across multiple agent runtimes (hooks/MCP/OS sandbox) with an auditable trail and configurable deny-by-default rules.
Avoid When
You cannot practically integrate/enable one of the enforcement paths (hooks/MCP wrapping/OS sandbox) or you require a hosted, managed service with centralized policy distribution and guaranteed uptime/SLA.
Use Cases
- • Blocking destructive shell commands and other high-risk tool actions from agent tool calls
- • Preventing unsafe file writes/edits to sensitive system directories
- • Detecting and blocking potential secret/PII/prompt-injection content in tool arguments/responses
- • Enforcing policy-driven approvals (human-in-the-loop) for specific operations like file writes
- • Rate limiting specific tools (e.g., web search) to reduce abuse and runaway agent behavior
- • Hardening and auditing agent tool activity across multiple agent frameworks (Python SDK and framework wrappers)
Not For
- • As a substitute for robust application security controls (authz, least privilege, backups)
- • Guaranteeing perfect safety against all novel or application-specific attack vectors
- • Managing sensitive compliance obligations if policy signing/verification and audit retention requirements are not operationally enforced
Interface
Authentication
The README describes local enforcement and policy evaluation. It also mentions policy signing/verification (Ed25519/HMAC-SHA256) and a keygen command, but no service-style auth scheme (API keys/OAuth scopes) for remote access is described in the provided content.
Pricing
No pricing/hosted tiers are described; appears to be open-source distributed via pip/PyPI under AGPL.
Agent Metadata
Known Gotchas
- ⚠ Tool name normalization may need correct mapping per agent; policy uses canonical tool names but different agents may emit different tool identifiers without proper hook/MCP wrapping.
- ⚠ Shell/file/path safety checks depend on correct argument structures and available metadata; ambiguous tool arguments could lead to false positives/denies.
- ⚠ Approval workflows require human interaction; unattended runs may stall if policies use require_approval.
- ⚠ If OS sandboxing/hardening profiles are misconfigured or not supported on a platform, the corresponding enforcement path may be unavailable.
Alternatives
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Scores are editorial opinions as of 2026-04-04.