Agent Memory Guard – OWASP defense for AI agent memory poisoning
OWASP reference implementation for ASI06 memory poisoning with LangChain and AutoGen integrations.
Zora — a long‑running local AI agent with provider registry and secure tool access.
Policy.toml loaded before every action prevents the context compaction failures that broke OpenClaw.
Developers running local AI agents with system access
OpenClaw · Aider · Cursor
The root cause: her constraint lived in the conversation. When the context compacted, it disappeared. The AI hadn't gone rogue; it had genuinely forgotten.
Zora's safety architecture is designed so that it can't happen. A few things that are different:
Compaction-proof rules. Policy lives in ~/.zora/policy.toml, loaded before every action, not in context. The LLM and the PolicyEngine don't share a channel.
Prompt injection defense. Every incoming message (Signal/Telegram) passes through a CaMeL dual-LLM quarantine, an isolated model with no tool access that extracts structured intent from raw text. The main agent never sees the original message.
Runtime safety layer. Every tool call is scored 0–100 for irreversibility before it executes. High-risk actions pause and route to your phone for approval via Signal or Telegram. A session risk forecaster tracks drift, salami slicing, and commitment creep across the whole session.
Locked by default. A misconfigured Zora does nothing. A misconfigured OpenClaw has full system access.
npm i -g zora-agent && zora-agent init
OWASP reference implementation for ASI06 memory poisoning with LangChain and AutoGen integrations.
First OWASP-backed security layer for ASI06 memory poisoning in agentic AI.
Deterministic agent governance with capability tokens beats probabilistic guardrails.
Agent runtime infra, but 0 stars and crowded with LangGraph and Temporal.
AST analysis blocks injection attacks before they hit your production database.
Compaction tree cuts context from 100K tokens to 3K without losing memory.